Elevation of marsh units in Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia
Elevation distribution in the Assateague Island National Seashore (ASIS) salt marsh complex and Chincoteague Bay is given in terms of mean elevation of conceptual marsh units defined by Defne and Ganju (2018). The elevation data is based on the 1-meter resolution Coastal National Elevation Database (CoNED). Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal ... |
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Elevation of marsh units in Eastern Shore of Virginia salt marshes
This data release contains coastal wetland synthesis products for the Atlantic-facing Eastern Shore of Virginia (the data release for the Chesapeake Bay-facing portion of the Eastern Shore of Virginia is found here: https://doi.org/10.5066/P997EJYB). Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and tidal range are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland ... |
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Elevation of marsh units in Plum Island Estuary and Parker River salt marsh complex, Massachusetts
This data release provides elevation distribution in the Plum Island Estuary and Parker River (PIEPR) salt marsh complex. Elevation distribution was calculated in terms of mean elevation of conceptual marsh units defined by Defne and Ganju (2018). The elevation data was based on the 1-meter gridded Digital Elevation Model and supplemented by 1-meter resampled 1/9 arc-second resolution National Elevation Data, where data gaps exist. Through scientific efforts initiated with the Hurricane Sandy Science Plan, ... |
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Elevation data for four sites in the coastal marsh at Grand Bay National Estuarine Research Reserve, Mississippi, from July 2018 through January 2020
To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ... |
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Elevation data for four sites in the coastal marsh at Grand Bay National Estuarine Research Reserve, Mississippi, from October 2016 through October 2017
To understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites in the Grand Bay National Estuarine Research Reserve, Mississippi (GNDNERR). Each site consisted of four plots located along a transect perpendicular to the marsh-estuary shoreline at 5-meter (m) increments (5, 10, 15, and 20 m from the shoreline). Each plot contained four net sedimentation tiles (NST) that were secured ... |
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Elevation of marsh units in Massachusetts salt marshes
This data release contains coastal wetland synthesis products for Massachusetts, developed in collaboration with the Massachusetts Office of Coastal Zone Management. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and tidal range, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal ... |
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Elevation of marsh units in north shore Long Island salt marsh complex, New York
This data release contains coastal wetland synthesis products for the geographic region of north shore Long Island, New York. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been ... |
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Elevation point cloud from low-altitude aerial imagery from UAS flights over Black Beach, Falmouth, Massachusetts on 18 March 2017 (LAZ file)
Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black ... |
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Elevations surveyed at Black Beach, Falmouth, Massachusetts on 18 March 2016 (text file)
Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black ... |
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Elevation of marsh units in Maine salt marshes
This data release contains coastal wetland synthesis products for the state of Maine. Metrics for resiliency, including the unvegetated to vegetated ratio (UVVR), marsh elevation, tidal range, and lifespan, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the ... |
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Elevation of marsh units in Chesapeake Bay salt marshes
This data release contains coastal wetland synthesis products for Chesapeake Bay. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and tidal range are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the intent of providing ... |
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Elevation point clouds of the north coast of Barter Island, Alaska acquired July 01 2014, September 07 2014, and July 05 2015 (LAZ file)
Six elevation point cloud files in LAZ format (compressed LAS binary data) are included in this data release: 3 raw point clouds of unclassified and unedited points and 3 modified point clouds that were spatially shifted and edited to remove outliers and spurious elevation values associated with moving water surfaces. An XYZ coordinate shift was applied to each data set in order to register the data sets to an earth-based datum established from surveyed ground control points. Points are unclassified and ... |
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Elevation of marsh units in Atlantic-facing New Jersey salt marshes
This data release contains coastal wetland synthesis products for the Atlantic-facing New Jersey salt marshes. Metrics for resiliency, including the unvegetated to vegetated ratio (UVVR), marsh elevation, and tidal range, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal ... |
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Elevation of the bedrock surface within the St. Clair River between Michigan and Ontario, Canada, 2008 (ESRI GRID, DSUELEV)
In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the ... |
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Elevation of marsh units in Blackwater salt marsh complex, Chesapeake Bay, Maryland
This data release contains coastal wetland synthesis products for the geographic region of Blackwater salt marsh complex, Chesapeake Bay, Maryland. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and others, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and ... |
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Elevation of marsh units in eastern Long Island salt marsh complex, New York (ver. 2.0, March 2024)
This data release contains coastal wetland synthesis products for the geographic region of eastern Long Island, New York, including the north and south forks, Gardiners Island, and Fishers Island. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with ... |
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Elevation of the late Wisconsinan to early Holocene regressive unconformity (Ur) beneath Vineyard and western Nantucket Sounds, Massachusetts (Esri binary grid; UTM, Zone 19N, WGS 84)
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a ... |
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Elevation of marsh units in Jamaica Bay to western Great South Bay salt marsh complex, New York
This data release contains coastal wetland synthesis products for the geographic region from Jamaica Bay to western Great South Bay, located in southeastern New York State. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with the Hurricane Sandy ... |
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Elevation of marsh units in Fire Island National Seashore and central Great South Bay salt marsh complex, New York
Elevation distribution in the Fire Island National Seashore and central Great South Bay salt marsh complex is given in terms of mean elevation of conceptual marsh units defined by Defne and Ganju (2018). The elevation data is based on the 1-meter resolution Coastal National Elevation Database (CoNED). Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands ... |
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Elevation of marsh units in Hudson Valley and New York City salt marsh complex, New York
This data release contains coastal wetland synthesis products for the geographic region of Hudson Valley and New York City, New York. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey ... |
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Elevation of marsh units in Connecticut salt marshes
This data release contains coastal wetland synthesis products for the state of Connecticut. Metrics for resiliency, including the unvegetated to vegetated ratio (UVVR), marsh elevation, tidal range, wave power, and exposure potential to environmental health stressors are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change ... |
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Elevation Data Collected in 2010 from Sabine National Wildlife Refuge, Louisiana
Data release doi:10.5066/F7BR8QBH associated with this metadata record serves as an archive of elevation data collected in August 2010 from Sabine National Wildlife Refuge (SNWR), Louisiana (U.S. Geological Survey [USGS] Field Activity Number [FAN] 10SWL01). Point (xyz) elevations were collected from historically formed open-water bodies and the surrounding emergent marsh using a combination of stop-and-go (semi-kinematic) and kinematic differential Global Positioning System (DGPS) surveying techniques. ... |
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ElevMHW: Elevation adjusted to local mean high water: Smith Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Digital elevation models (DEMs) of northern Monterey Bay, California, March 2017
This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in March 2017. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a ... |
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Digital Elevation Model (DEM) of Summerland Ledge, Florida, 2022
A digital elevation model (DEM) was created from underwater images collected at Summerland Ledge (SL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud and includes points from both classes. The DEM covers a ... |
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ElevMHW: Elevation adjusted to local mean high water: Wreck Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Digital elevation models (DEMs) of northern Monterey Bay, California, September 2017
This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in September 2017. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted ... |
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Chimney Bluffs digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Chimney Bluffs, New York in July 2017 (32-bit floating point GeoTIFF image)
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from ... |
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Digital surface model (DSM) and digital elevation model (DEM) of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01
This portion of the data release presents a digital surface model (DSM) and digital elevation model (DEM) of the exposed Los Padres Reservoir delta where the Carmel River enters the reservoir. The DSM and DEM have a resolution of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unoccupied aerial system (UAS) on 2017-11-01. The DSM represents the elevation of the highest object within the bounds of a cell, including vegetation, woody ... |
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High Resolution Digital Elevation Model (DEM) of Looe Key, Florida, 2022
A digital elevation model (DEM) was created from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud and includes points from both classes. The DEM covers a rectangular ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, April 2014
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in April 2014. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity ... |
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Quicklook Digital Elevation Model (DEM) of Looe Key, Florida, 2022
A digital elevation model (DEM) was created from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud and includes points from both classes. The DEM covers a rectangular ... |
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Post-Hurricane Florence Digital Elevation Models of coastal North Carolina
This data release presents structure-from-motion (SFM) products derived from aerial imagery surveys with precise Global Navigation Satellite System (GNSS) navigation data flown in a piloted fixed wing aircraft taken along the North Carolina coast in response to Hurricane Florence (available here https://coastal.er.usgs.gov/data-release/doi-P91KB9SF/). USGS researchers use the elevation models and orthorectified imagery to assess future coastal vulnerability, nesting habitats for wildlife, and provide data ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, July 2018
This portion of the USGS data release presents digital elevation models (DEMs) derived from bathymetric and topographic surveys conducted on the Elwha River delta in July 2018 (USGS Field Activity Number 2018-648-FA). Nearshore bathymetry data were collected using two personal watercraft (PWCs) and a kayak equipped with single-beam echosounders and survey-grade global navigation satellite systems (GNSS) receivers. Topographic data were collected on foot with survey-grade GNSS receivers mounted on backpacks. ... |
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Digital elevation models of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016
This part of the data release presents digital elevation models (DEMs) spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the DEMs were created, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were collected ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, May 2012
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in May 2012. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity ... |
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Charles Point digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (32-bit floating point GeoTIFF image)
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Digital elevation model (DEM) of Big Pine Ledge, Florida, 2021
A digital elevation model (DEM) was created from underwater images collected at Big Pine Ledge, Florida, in July 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud, and includes points from both classes. The DEM covers a rectangular area of seafloor approximately 650x120 meters (0 ... |
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Digital elevation model (DEM) of Looe Key, Florida, 2021
A digital elevation model (DEM) was created from underwater images collected at Looe Key, Florida, in July 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud, and includes points from both classes. The DEM covers a rectangular area of seafloor approximately 720x100 meters (0.072 ... |
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Cape Canaveral, Florida, multibeam bathymetry collected in 2016 by Coastal Carolina University: Processed elevation point data (XYZ)
A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data. |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, September 2010
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in September 2010. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented ... |
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FIIS2002_EAARLA_BE_z18_n88g99_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for EAARL Coastal Topography—Fire Island, New York, 2002
A digital elevation model (DEM) mosaic for Fire Island, New York, was produced from remotely sensed, geographically referenced elevation measurements collected October 25 and November 8, 2002 by the U.S. Geological Survey, in cooperation with the National Park Service (NPS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the first-generation Experimental Advanced Airborne Research Lidar (EAARL-A), a pulsed laser ranging system mounted ... |
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San Francisco Bay-Delta bathymetric/topographic digital elevation model(DEM)
A high-resolution (10-meter per pixel) digital elevation model (DEM) was created for the Sacramento-San Joaquin Delta using both bathymetry and topography data. This DEM is the result of collaborative efforts of the U.S. Geological Survey (USGS) and the California Department of Water Resources (DWR). The base of the DEM is from a 10-m DEM released in 2004 and updated in 2005 (Foxgrover and others, 2005) that used Environmental Systems Research Institute(ESRI), ArcGIS Topo to Raster module to interpolate ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, July 2016
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in July 2016. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Initial_Elevations_N.txt)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Ivan Initial Elevations
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina Initial Elevations
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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Greig Street digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (32-bit floating point GeoTIFF image)
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 11 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 12 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 1 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 20 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 2 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 3 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 6 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 7 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 8 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Seafloor Elevation and Volume Change Analyses from 2016 to 2019 Along the Florida Reef Tract, USA
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes along the Florida Reef Tract (FRT) from Miami to Marquesas Keys within a 939.4 square-kilometer area between 2016 and 2019. USGS staff used light detection and ranging (lidar)-derived data acquired by the National Oceanic and Atmospheric Administration (NOAA) during two separate lidar surveys. The first is dataset is referenced as "2016 lidar" data and was collected between ... |
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Projected Seafloor Elevation Change in the Upper Florida Keys, Florida: 25, 50, 75, and 100 years from 2002
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by measuring regional-scale changes in seafloor elevation in the Upper Florida Keys, Florida, including both coral-dominated habitats and adjacent, non-coral-dominated habitats. USGS staff used historical bathymetric data from the 1930’s and light detection and ranging (lidar)-derived data ... |
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50-Meter Digital Elevation Model of Coastal Bathymetry Collected in 2011 from the Chandeleur Islands, Louisiana (U.S. Geological Survey Field Activity Numbers 11BIM01 and 11BIM02)
As part of the Barrier Island Evolution Research Project, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off the northern Chandeleur Islands, Louisiana, in June of 2011. The overall objectives of the study are to better understand barrier-island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual timescales (1-5 years). Collection of ... |
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50-Meter Digital Elevation Model of Coastal Bathymetry Collected in 2012 from the Chandeleur Islands, Louisiana (U.S. Geological Survey Field Activity Numbers 12BIM03 and 12BIM04)
As part of the Barrier Island Evolution Research Project, scientists from the U.S. Geological Survey's St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off the northern Chandeleur Islands, Louisiana, in Julyof 2012. The overall objective of the study is to better understand barrier-island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual timescales (1-5 years). The collection of ... |
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Chandeleurs_2013_50_NAD83_NAVD88_GEOID09_DEM.tif: 50-Meter Digital Elevation Model (DEM) of Coastal Bathymetry Collected in 2013 from the Chandeleur Islands, Louisiana (U.S. Geological Survey (USGS) Field Activity Numbers (FAN) 13BIM02, 13BIM03, 13BIM04, 13BIM07, and 13BIM08.)
As part of the Barrier Island Evolution Research Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted nearshore geophysical surveys around the northern Chandeleur Islands, Louisiana, in July and August of 2013. The objective of the study is to better understand barrier-island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual timescales (1‒5 years). ... |
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St. Croix, U.S. Virgin Islands—Seafloor elevation change in Maui, St. Croix, St. Thomas, and the Florida Keys
Coral reefs serve as natural barriers that protect adjacent shorelines from coastal hazards such as storms, waves and erosion but projections indicate global degradation of coral reefs due to anthropogenic impacts and climate change will cause a transition to net erosion by mid-century. The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by measuring ... |
Info |
Projected Seafloor Elevation Change and Relative Sea Level Rise Near St. Croix, U.S. Virgin Islands 25, 50, 75, and 100 Years from 2014
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes near Buck Island and St. Croix, U.S. Virgin Islands. Changes in seafloor elevation were calculated using historical bathymetric point data from the 1980s (see Yates and others, 2017a) and light detection and ranging (lidar)-derived data acquired in 2014 (NOAA, 2015) using methods outlined in Yates and others (2017b). An elevation change analysis between the 1980s and 2014 ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_114_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_114_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_134_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_134_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_152_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_152_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_155_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_155_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_158_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_158_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_186_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_186_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_191_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_191_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_23_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_23_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_257_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_257_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_4_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_4_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_71_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_71_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_95_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_95_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
St. Thomas, U.S. Virgin Islands-Seafloor elevation change in Maui, St. Croix, St. Thomas, and the Florida Keys
Coral reefs serve as natural barriers that protect adjacent shorelines from coastal hazards such as storms, waves and erosion but projections indicate global degradation of coral reefs due to anthropogenic impacts and climate change will cause a transition to net erosion by mid-century. The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by measuring ... |
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Lidar-Derived Digital Elevation Model (DEM) Mosaic for EAARL-B Submerged Topography-Saint Thomas, U.S. Virgin Islands, 2014
A submerged topography Digital Elevation Model (DEM) mosaic for a portion of the submerged environs of Saint Thomas, U.S. Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected on March 7, 8, 11, 12, 13, 14, 17, 18, and 24, 2014 by the U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration (NOAA) Coral Reef Conservation Program. Elevation measurements were collected over the area using the second-generation ... |
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Projected Seafloor Elevation Change and Relative Sea Level Rise Near St. Thomas, U.S. Virgin Islands 25, 50, 75, and 100 Years from 2014
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes near St. Thomas, U.S. Virgin Islands. Changes in seafloor elevation were calculated using historical bathymetric point data from the 1960s and 1970s (see Yates and others, 2017a) and light detection and ranging (lidar)-derived elevation data acquired in 2014 (NOAA, 2015) using methods outlined in Yates and others (2017b). An elevation change analysis between the historical ... |
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Seafloor Elevation Change From 2017 to 2018 at a Subsection of Crocker Reef, Florida Keys-Impacts from Hurricane Irma
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes at a subsection of Crocker Reef near Islamorada, Florida (FL), within a 6.1 square-kilometer area following the landfall of Hurricane Irma in September 2017. USGS staff used USGS multibeam data collected between October 10 and December 8, 2017 (Fredericks and others, 2019) and March 8-15, 2018 (Fredericks and others, 2019) to assess changes in seafloor elevation and structure ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, September 2014
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in September 2014. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented ... |
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Upper Florida Keys-Seafloor elevation change in Maui, St. Croix, St. Thomas, and the Florida Keys
Coral reefs serve as natural barriers that protect adjacent shorelines from coastal hazards such as storms, waves and erosion but projections indicate global degradation of coral reefs due to anthropogenic impacts and climate change will cause a transition to net erosion by mid-century. The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by measuring ... |
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Lake Bluffs digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (32-bit floating point GeoTIFF image)
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Lidar-Derived Seamless Digital Elevation Model (DEM) Mosaic for Coastal Topography—Chandeleur Islands, Louisiana, 23-25 June 2016
A digital elevation model (DEM) mosaic was produced for the Chandeleur Islands, Louisiana, from remotely sensed, geographically referenced elevation measurements collected by Leading Edge Geomatics (LEG) using a Leica Chiroptera II Bathymetric and Topographic Sensor. Dewberry reports that the nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1-Unclassified, 2-Ground (includes ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, August 2012
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in August 2012. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented ... |
Info |
ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Coastal Bathymetry Data Collected in 2016 from the Chandeleur Islands, Louisiana–Interpolated Digital Elevation Model
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC), collected single beam and swath bathymetry data from the northern Chandeleur Islands, Louisiana, in June of 2016. This USGS data release includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM). This USGS data release provides 437-line kilometers (km) of processed single beam bathymetry (SBB) and interferometric bathymetry (IFB) data collected under Field Activity ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, March 2013
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in March 2013. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity ... |
Info |
ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
Sodus North digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (32-bit floating point GeoTIFF image)
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
Info |
Delineated Coastal Cliff Toes Derived from Post-Hurricane Maria Lidar Elevation Data Collected from Puerto Rico: 2018
The National Assessment of Coastal Change Hazards project aims to understand and forecast coastal landscape change. This dataset consists of delineated coastal cliff toes that may be used to assess the hazard posed by eroding coastal cliffs on the islands of Puerto Rico, Culebra, and Vieques. The delineation of cliff tops and toes can be used as an input into cliff hazard metrics and to measure overall cliff changes over time. Cliff tops and cliff toes were identified along three-dimensional (3D) transects ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Year_30_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Year_30_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
Info |
Delineated Coastal Cliff Tops Derived from Post-Hurricane Maria Lidar Elevation Data Collected from Puerto Rico: 2018
The National Assessment of Coastal Change Hazards project aims to understand and forecast coastal landscape change. This dataset consists of delineated coastal cliff tops that may be used to assess the hazard posed by eroding coastal cliffs on the islands of Puerto Rico, Culebra, and Vieques. The delineation of cliff tops and toes can be used as an input into cliff hazard metrics and to measure overall cliff changes over time. Cliff tops and cliff toes were identified along three-dimensional (3D) transects ... |
Info |
Delineated Coastal Cliff Transects Derived from Post-Hurricane Maria Lidar Elevation Data Collected from Puerto Rico: 2018
The National Assessment of Coastal Change Hazards project aims to understand and forecast coastal landscape change. This dataset consists of delineated coastal cliff transects that may be used to assess the hazard posed by eroding coastal cliffs on the islands of Puerto Rico, Culebra, and Vieques. The delineation of cliff tops and toes can be used as an input into cliff hazard metrics and to measure overall cliff changes over time. Cliff tops and cliff toes were identified along three-dimensional (3D) ... |
Info |
ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
Digital elevation model of Little Holland Tract, Sacramento-San Joaquin Delta, California, 2015
This product is a digital elevation model (DEM) for the Little Holland Tract in the Sacramento-San Joaquin River Delta, California based on U.S. Geological Survey (USGS)-collected elevation data, merged with existing topographic and bathymetric elevation data. The USGS collected topographic and bathymetric elevation data in 2015, using a combination of methods. Topographic and shallow-water bathymetric data were collected on foot using a global positioning system (GPS) backpack platform that consisted of ... |
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Ship_Horn_Island_2016_IFB_SBB_DEM_metadata: Bathymetric Digital Elevation Model (DEM) of the 2016 nearshore coastal bathymetry from West Ship Island to Horn Island, Gulf Islands National Seashore, Mississippi.
The United States Geological Survey Saint Petersburg Coastal and Marine Science Center (USGS SPCMSC), in cooperation with the United States Army Corps of Engineers (USACE) conducted bathymetric surveys of the nearshore waters surrounding Ship and Horn Islands, Gulf Islands National Seashore, Mississippi (GUIS). Camille Cut separates Ship Island into East Ship Island and West Ship Island. The objective of this study was to establish base-level elevation conditions around West Ship Island, East Ship Island, ... |
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Seafloor Elevation Change From 2016 to 2017 at Crocker Reef, Florida Keys-Impacts From Hurricane Irma
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes at Crocker Reef near Islamorada, Florida (FL), within a 33.6 square-kilometer area following the landfall of Hurricane Irma in September 2017. USGS staff used light detection and ranging (lidar)-derived data acquired by the National Oceanic and Atmospheric Administration (NOAA) between July 21 and November 21, 2016 and USGS multibeam data collected between October 10 and ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, July 2015
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in July 2015. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity ... |
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Ship_Horn_Island_2016_SBB_xyz_metadata: Bathymetric Digital Elevation Model (DEM) of the 2016 nearshore coastal bathymetry from West Ship Island to Horn Island, Gulf Islands National Seashore, Mississippi.
The United States Geological Survey Saint Petersburg Coastal and Marine Science Center (USGS SPCMSC), in cooperation with the United States Army Corps of Engineers (USACE) conducted bathymetric surveys of the nearshore waters surrounding Ship and Horn Islands, Gulf Islands National Seashore, Mississippi (GUIS). Camille Cut separates Ship Island into East Ship Island and West Ship Island. The objective of this study was to establish base-level elevation conditions around West Ship Island, East Ship Island, ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-100 Years From 2001 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-100 Years From 2001 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-100 Years From 2011 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ... |
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Shoreface Coastal Bathymetry Data Collected in June 2014 from Fire Island, New York: 50-Meter Digital Elevation Model
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, collected bathymetric data along the upper shoreface and within the wilderness breach at Fire Island, New York, in June 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the shoreface along Fire Island and model the evolution of the wilderness breach as a part of the Hurricane Sandy Supplemental Project GS2-2B ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-100 Years From 2011 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—100 Years From 2014 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—100 Years From 2014 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ... |
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Wilderness Breach Bathymetry Data Collected in June 2014 from Fire Island, New York: 25-Meter Digital Elevation Model
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, collected bathymetric data along the upper shoreface and within the wilderness breach at Fire Island, New York, in June 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the shoreface along Fire Island and model the evolution of the wilderness breach as a part of the Hurricane Sandy Supplemental Project GS2-2B ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, September 2013
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in September 2013. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented ... |
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ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, January 2015
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in January 2015. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented ... |
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ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, February 2016
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in February 2016. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented ... |
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ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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AllCases_Final_Bed_Elevations: Model Sensitivity to Sediment Parameters and Bed Composition in Delft3D: Model Output
The sensitivity to sediment parameterization and initial bed configuration on sediment transport processes and morphological evolution are assessed through process-based numerical modeling. Six sensitivity cases using a previously validated model for Dauphin Island, Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on bed level morphology, barrier island evolution, and sediment fluxes. Delft3D model output of suspended and bedload sediment fluxes, and final bed levels data are ... |
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ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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AllScenarios_Initial_and_Final_Bed_Elevations: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output
The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ... |
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Bathymetric data, stored as elevations relative to IGLD85, collected by the U.S. Geological Survey within the St. Clair River between Michigan and Ontario, Canada, 2008 (ESRI GRID, BATHY_05M)
In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the ... |
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Digital Elevation Model (DEM) of Rincon, Puerto Rico (rincon_dem)
The USGS Digital Elevation Model (DEM) data files are digital representations of cartographic information in a raster form. DEMs consist of a sampled array of elevations for a number of ground positions at regularly spaced intervals. The DEM data for 7.5-minute units correspond to the USGS 1:24,000- and 1:25,000-scale topographic quadrangle map series for all of the United States and its territories. Each 7.5-minute DEM is based on 30- by 30-meter data spacing with the Universal Transverse Mercator (UTM) ... |
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ANGD2014_BE_z20_n88g12A_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for Coastal Topography—Anegada, British Virgin Islands, 2014
A digital elevation model (DEM) mosaic was produced for Anegada, British Virgin Islands, from remotely sensed, geographically referenced elevation measurements collected by Watershed Sciences, Inc. (WSI)/Quantum Spatial using an Optech Orion M300 (1064-nm wavelength) lidar sensor on January 21, 2014. |
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Braddock East digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (32-bit floating point GeoTIFF image).
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, August 2019
This portion of the USGS data release presents digital elevation models (DEMs) derived from bathymetric and topographic surveys conducted on the Elwha River delta in August 2019 (USGS Field Activity Number 2019-633-FA). Nearshore bathymetry data were collected using two personal watercraft (PWCs) equipped with single-beam echosounders and survey-grade global navigation satellite systems (GNSS) receivers. Topographic data were collected on foot with survey-grade GNSS receivers mounted on backpacks. Positions ... |
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ANGD2014_EAARLB_z20_v09g12A_mosaic_metadata: Lidar-Derived Seamless (Bare Earth and Submerged) Digital Elevation Model (DEM) Mosaic for Coastal Topography—Anegada, British Virgin Islands, 2014
A seamless (bare earth and submerged) topography Digital Elevation Model (DEM) mosaic for a portion of the submerged environs of Anegada, British Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected March 19-20, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ... |
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Interpolated digital elevation model (DEM) of the nearshore around Ship, Horn, and Petit Bois Islands, Mississippi: 1916 to 1920
To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. Datasets include 1916 through 1920 soundings collected by the United States Coast and ... |
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Upper Florida Keys 1930s-2002 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the 1930’s and 2002 in the Upper Florida Keys (UFK) from Triumph Reef to Pickles Reef within a 234.2 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2017a) derived from an elevation-change analysis between two elevation datasets acquired in the ... |
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Florida Reef Tract 1930s-2016 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the 1930’s and 2016 along the Florida Reef Tract (FRT) from Miami to Key West within a 982.4 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2021) derived from an elevation-change analysis between two elevation datasets acquired in the 1930’s ... |
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Seafloor elevation change from the 1930s to 2016 along the Florida Reef Tract, USA
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes along the Florida Reef Tract (FRT) from Miami to Key West within a 982.4 square-kilometer area. USGS staff calculated changes in seafloor elevation from the 1930’s to 2016 using digitized historical hydrographic surveys (H-sheets) acquired by the U.S. Coast and Geodetic Survey (USC&GS) in the 1930’s and light detection and ranging (lidar)-derived digital elevation models ... |
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Looe Key, Florida, 1938-2004 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 1938 and 2004 at Looe Key coral reef near Big Pine Key, Florida (FL), within a 19.06 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2017a) derived from an elevation-change analysis between two elevation datasets acquired in 1938 and ... |
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3 arc second digital elevation model of the Gulf of Maine
A gap-free, region-wide combined topographic/bathymetric grid at a fixed resolution is useful for describing the topography of the seafloor and for a wide variety of oceanographic studies. Generating a bathymetric grid of this type consists of (1) locating and retrieving digital datasets from a variety of sources, (2) correcting errors and determining the dataset that best represents the topography in specific regions, (3) converting the depth data to common horizontal and vertical datums, and (4) selecting ... |
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Seafloor elevation change from 2002 to 2016 in the Upper Florida Keys
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes in the Upper Florida Keys (UFK) from Triumph Reef to Pickles Reef within a 242.4 square-kilometer area. USGS staff calculated changes in seafloor elevation from 2002 to 2016 using light detection and ranging (lidar)-derived data acquired by the USGS in 2001 and 2002 and lidar-derived data acquired by the National Oceanic and Atmospheric Administration (NOAA) in 2016 and 2017. ... |
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Upper Florida Keys 2002-2016 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2002 and 2016 in the Upper Florida Keys (UFK) from Triumph Reef to Pickles Reef within a 242.4 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Murphy and others (2021) derived from an elevation-change analysis between two elevation datasets acquired in ... |
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Looe Key, Florida, 2004-2016 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2004 and 2016 at Looe Key coral reef near Big Pine Key, Florida (FL), within a 16.37 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2019) derived from an elevation-change analysis between two elevation datasets acquired in 2004 and ... |
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Comma separated value (CSV) text files of navigation and elevation data collected by the U.S. Geological Survey during field activity 2016-030-FA offshore Sandwich Beach, MA in June 2016
The objectives of the survey were to provide bathymetric and sidescan sonar data for sediment transport studies and coastal change model development for ongoing studies of nearshore coastal dynamics along Sandwich Town Neck Beach, MA. Data collection equipment used for this investigation are mounted on an unmanned surface vehicle (USV) uniquely adapted from a commercially sold gas-powered kayak and termed the "jetyak". The jetyak design is the result of a collaborative effort between USGS and Woods Hole ... |
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Interpolated digital elevation model (DEM) of the nearshore around Ship, Horn, and Petit Bois Islands, Mississippi: 2008 to 2009
To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. Datasets include 1916 through 1920 soundings collected by the United States Coast and ... |
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Coastal bathymetry data collected between 2008 and 2009 offshore of the Mississippi and Alabama barrier islands: Processed elevation point data
During the summers of 2008 and 2009 the United States Geological Survey (USGS) conducted bathymetric surveys from West Ship Island, Mississippi, to Dauphin Island, Alabama, as part of the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility project. The survey area extended from the shoreline out to approximately two kilometers and included the adjacent passes. These findings were originally published in Dewitt and others (2012). This USGS data release includes updated elevation point ... |
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Digital elevation models (DEMs) of the beach and nearshore in Santa Cruz, California
Digital elevation models (DEMs) were produced from bathymetric and topographic measurements collected offshore of Santa Cruz, CA, from 2014 to 2024. Bathymetric data were collected using personal watercraft (PWCs) equipped with single-beam echosounders and dual frequency global navigation satellite system (GNSS) receivers. Topographic data were collected on foot with GNSS receivers mounted on backpacks. Bathymetric and topographic data were collected primarily along a series of cross-shore transects at 50-m ... |
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Beach Topography—Fire Island, New York, Pre-Hurricane Sandy, January 2012: Ground Based Lidar (1-Meter Digital Elevation Model)
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) and the U.S. Army Corps of Engineers Field Research Facility (USACE-FRF) of Duck, North Carolina collaborated to gather alongshore ground-based lidar beach topography at Fire Island, New York. This high-resolution, elevation dataset was collected on January 30, 2012, and was funded by SPCMSC. The USGS data release containing the aforementioned dataset includes the resulting, processed elevation point data (XYZ) and ... |
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Braddock West digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (32-bit floating point GeoTIFF image).
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ... |
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Surveyed ground control and elevation checkpoints acquired at Barter Island, Alaska, 2014-2016
Ground control points and checkpoints were collected during Global Positioning System (GPS) surveys conducted between September 6, 2014 and September 18, 2016 along the northern coast of Barter Island, Alaska. Data were acquired and post-processed using precise positioning and used to co-register and assess accuracy of photogrammetric data sets. |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, July 2017
This portion of the USGS data release presents digital elevation models (DEMs) derived from bathymetric and topographic surveys conducted on the Elwha River delta in July 2017 (USGS Field Activity Number 2017-638-FA). Nearshore bathymetry data were collected using two personal watercraft (PWCs) and a kayak equipped with single-beam echosounders and survey-grade global navigation satellite systems (GNSS) receivers. Topographic data were collected on foot with survey-grade GNSS receivers mounted on backpacks. ... |
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Bathymetric data, stored as elevation above IGLD85, collected by the U.S. Geological Survey within the St. Clair River offshore of Marysville, Michigan, 2008 (ESRI GRID, MVILLE_05M)
In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the ... |
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Bathymetric data, stored as elevations above IGLD85, collected by the U.S. Geological Survey within the St. Clair River offshore of Port Lambton, Ontario, 2008 (ESRI GRID, PORTL_05M)
In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the ... |
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ASIS2015_HRJQ_BE_z18_n88g12B_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for Coastal Topography—Assateague Island, Maryland and Virginia, Post-Hurricane Joaquin, 26 November 2015
A digital elevation model (DEM) mosaic was produced for Assateague Island, Maryland and Virginia, post-Hurricane Joaquin, from remotely sensed, geographically referenced elevation measurements collected by Quantum Spatial using a Leica ALS70 (1064-nm wavelength) lidar sensor. |
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Esri Format Binary Grid of the Merged Bathymetry and Elevation Data from the Corsica River Estuary, Maryland For Use with USGS Cruise 07005 (COMBELEV)
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
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Lidar point cloud, elevation models, GPS data, and imagery and orthomosaics from multispectral and true-color aerial imagery data, collected during UAS operations at Marsh Island, New Bedford, MA on October 26th, 2023
Small Uncrewed Aircraft Systems (sUAS) were used to collect aerial remote sensing data over Marsh Island, a salt marsh restoration site along New Bedford Harbor, Massachusetts. Remediation of the site will involve direct hydrological and geochemical monitoring of the system alongside the UAS remote sensing data. On October 26th, 2023, USGS personnel collected natural (RGB) color images, multispectral images, lidar, and ground control points. These data were processed to produce a high resolution lidar point ... |
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Lidar point cloud, elevation models, GPS data, and imagery and orthomosaic from true-color aerial imagery, collected during UAS operations at Marsh Island, New Bedford, MA on April 9th, 2024
Small Uncrewed Aircraft Systems (sUAS) were used to collect aerial remote sensing data over Marsh Island, a salt marsh restoration site along New Bedford Harbor, Massachusetts. Remediation of the site will involve direct hydrological and geochemical monitoring of the system alongside the UAS remote sensing data. On April 9th, 2024, USGS personnel collected natural (RGB) color images, Lidar, and ground control points. These data were processed to produce a high-resolution lidar point cloud (LPC), digital ... |
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5year_R0_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ... |
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Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012: Digital elevation model (DEM)
A DEM was produced for a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th), from remotely sensed, geographically referenced elevation measurements collected by Photo Science, Inc. (Delaware, Maryland, Virgina, and North Carolina) and Woolpert, Inc. (Fire Island, New York) using airborne lidar sensors. |
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5year_R1_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ... |
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5year_R2_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ... |
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Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012: Lidar and digital elevation model (DEM) tile index
This data represents the tile index for lidar data collected for the U.S. Geological Survey in November 2012 following Hurricane Sandy, which made landfall in the eastern United States on October 29th, 2012. The lidar LAS and derived-digital elevation model (DEM) data are divided into these tiles and filenames match the tile number. The index shows the extent of data collection (portions of the coastline of New York, Delaware, Maryland, Virginia, and North Carolina) and provides tile names to aid in ... |
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5year_R3_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ... |
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5year_R4_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ... |
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Ivan_R0_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Ground-Based XYZ Point Elevation Data Collected in May 2015 From Fire Island, New York
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from May 6 to 20, 2015. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach as a part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected with single-beam echosounders and Global Positioning ... |
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Shoreface Coastal Bathymetry Data Collected in May 2015 From Fire Island, New York: 100-Meter Digital Elevation Model
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from May 6 to 20, 2015. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach as a part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected with single-beam echosounders and Global Positioning ... |
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Single-Beam Bathymetry of the Hurricane Sandy Breach at Fire Island, New York, June 2013 (1-Meter Digital Elevation Model)
This dataset, 20130626_bathy_DEM.zip, contains a 1-meter (m) grid of June 2013 bathymetry of the breach channel, ebb shoal, and adjacent coast of the Fire Island Wilderness Breach. Scientists from the U.S. Army Corps of Engineers (USACE), in collaboration with the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), conducted a bathymetric survey from June 22-26, 2013. The survey focused on a breach (Wilderness Breach) created by Hurricane Sandy near Pelican Island, NY, ... |
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Ivan_R1_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Ivan_R2_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Ivan_R3_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Wilderness Breach Bathymetry Data Collected in May 2015 From Fire Island, New York: 50-Meter Digital Elevation Model
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from May 6 to 20, 2015. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach as a part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected with single-beam echosounders and Global Positioning ... |
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Ivan_R4_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Digital Elevation Model from Single Beam Bathymetry XYZ Data Collected in June 2015 from the Chandeleur Islands, Louisiana
As part of the Louisiana Coastal Protection and Restoration Authority (CPRA) Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a single-beam bathymetry survey around the Chandeleur Islands, Louisiana in June 2015. The goal of the program is to provide long-term data on Louisiana’s barrier islands and use this data to plan, design, evaluate, and maintain current and future barrier island ... |
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Katrina_R0_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Digital Elevation Model from Single-Beam Bathymetry XYZ Data Collected in 2015 from Raccoon Point to Point Au Fer, Louisiana
As part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the south-central coast of Louisiana, from Raccoon Point to Point Au Fer Island, in July 2015. The goal of the BICM program is to provide long-term data on Louisiana’s coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration ... |
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Katrina_R1_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Katrina_R3_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for Coastal Topography—Fire Island, New York, 07 May 2012
A digital elevation model (DEM) mosaic was produced for Fire Island, New York, from remotely sensed, geographically referenced elevation measurements collected by Photo Science, Inc. using an Optech Gemini lidar sensor flown on a Cessna 206 aircraft |
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Katrina_R4_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Sally_R0_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Sally_R1_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Sally_R2_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Sally_R3_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Crocker Reef, Florida, 2016-2017 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2016 and 2017 at Crocker Reef near Islamorada, Florida (FL), within a 33.62 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2019) derived from an elevation-change analysis between two elevation datasets acquired in 2016 and 2017 using ... |
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Looe Key, Florida, 2016-2017 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2016 and 2017 at Looe Key coral reef near Big Pine Key, Florida (FL), within a 19.74 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2019) derived from an elevation-change analysis between two elevation datasets acquired in 2016 and ... |
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Florida Reef Tract 2016-2019 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2016 and 2019 along the Florida Reef Tract (FRT) from Miami to Key West within a 939.4 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Fehr and others (2021) derived from an elevation-change analysis between two elevation datasets acquired in 2016/2017 ... |
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Sally_R4_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Katrina_R2_elevation: Modeling the impacts of sand placement strategies on barrier island evolution in a semi-enclosed bay system: model input and results
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ... |
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Lidar point cloud, elevation models, GPS data, imagery, and orthomosaics from multispectral and true-color aerial imagery data, collected during UAS operations at Marsh Island, New Bedford, MA on August 21st, 2024
Small Uncrewed Aircraft Systems (sUAS) were used to collect aerial remote sensing data over Marsh Island, a salt marsh restoration site along New Bedford Harbor, Massachusetts. Remediation of the site will involve direct hydrological and geochemical monitoring of the system alongside the UAS remote sensing data. On August 21st, 2024, USGS personnel collected natural (RGB) color images, multispectral images, thermal images, lidar, GPS check points, and ground control points. These data were processed to ... |
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Projected Seafloor Elevation Change and Relative Sea Level Rise Along the Florida Reef Tract from Miami to Boca Chica Key 25, 50, 75, and 100 Years from 2016
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes along the Florida Reef Tract (FRT) from Miami to Boca Chica Key, Florida. Changes in seafloor elevation were calculated from the 1930s to 2016 using digitized hydrographic sheet sounding data and light detection and ranging (lidar)-derived digital elevation models (DEMs) acquired by the National Oceanic and Atmospheric Administration (NOAA) in 2016 and 2017. Most of the ... |
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Interpolated digital elevation model (DEM) of the nearshore around Ship, Horn, and Petit Bois Islands, Mississippi: 2016
To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. Datasets include 1916 through 1920 soundings collected by the United States Coast and ... |
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ASIS2016_HRHM_SM_z18_n88g12B_mosaic_metadata: Lidar-Derived Seamless Digital Elevation Model (DEM) Mosaic of Coastal Topography—Assateague Island, Maryland and Virginia, Post-Hurricane Hermine, 10-12 September 2016
A digital elevation model (DEM) mosaic was produced for Assateague Island, Maryland and Virginia, post-Hurricane Hermine, from remotely sensed, geographically referenced elevation measurements collected by Quantum Spatial using a Riegl VQ-880-G (532-nm wavelength circular scan and 1064-nm wavelength linear scan) lidar sensor. |
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Footprints and producers of source data used to create central portion of the high-resolution (1 m) San Francisco Bay, California, digital elevation model (DEM)
Polygon shapefile showing the footprint boundaries, source agency origins, and resolutions of compiled bathymetric digital elevation models (DEMs) used to construct a continuous, high-resolution DEM of the central portion of San Francisco Bay. |
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Digital elevation model (DEM) of central San Francisco Bay, California, created using bathymetry data collected between 2009 and 2020 (MLLW)
A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the central portion of San Francisco Bay, was constructed from bathymetric surveys collected from 2005 to 2020. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and interferometric side-scan sonar systems. Of those 93 surveys, 75 consist of swaths of data ... |
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Crocker Reef, Florida, 2017-2018 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2017 and 2018 at Crocker Reef near Islamorada, Florida (FL), within a 6.11 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2019) derived from an elevation-change analysis between two elevation datasets acquired in 2017 and 2018 using ... |
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Multibeam Bathymetry Data Collected in 2016 from Grand Bay Alabama/Mississippi: Adjusted processed elevation point data (x,y,z)
A reconnaissance multibeam bathymetry survey was conducted by the U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Grand Bay Alabama/Mississippi on May 12, 2016 as an assessment of the shallow water capabilities of the Teledyne Reson SeaBat T50-P multibeam echosounder, and as an attempt to map the eroding marsh edges at locations of interest around the bay. This dataset, Grand_Bay_2016_MBB_Adjusted_xyz.zip, includes the resulting processed elevation point data (x,y,z ... |
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Digital elevation model (DEM) of central San Francisco Bay, California, created using bathymetry data collected between 2009 and 2020 (NAVD88)
A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the central portion of San Francisco Bay, was constructed from bathymetric surveys collected from 2005 to 2020. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and interferometric side-scan sonar systems. Of those 93 surveys, 75 consist of swaths of data ... |
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Multibeam Bathymetry Data Collected in 2016 from Grand Bay Alabama/Mississippi: Unadjusted processed elevation point data (x,y,z)
A reconnaissance multibeam bathymetry survey was conducted by the U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Grand Bay Alabama/Mississippi (AL/MS) on May 12, 2016 as an assessment of the shallow water capabilities of the Teledyne Reson SeaBat T50-P multibeam echosounder, and as an attempt to map the eroding marsh edges at locations of interest around the bay. This dataset, Grand_Bay_2016_MBB_Unadjusted_xyz.zip, includes the resulting [unadjusted] processed ... |
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Multibeam Bathymetry Data Collected in 2018 from Grand Bay and Point Aux Chenes Bay Alabama/Mississippi: Processed elevation point data (x,y,z)
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Grand Bay Alabama/Mississippi (AL/MS) October 22-23, 2018. This dataset, Grand_Bay_2018_MBB_xyz.zip, includes the processed point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. |
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Multibeam Bathymetry Data Collected in 2019 from Grand Bay and Point Aux Chenes Bay Alabama/Mississippi: Processed Elevation Point Data (x,y,z)
An Ellipsoidally Referenced Survey (ERS) using a Teledyne Reson SeaBat T50-P multibeam echosounder was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Grand Bay Alabama/Mississippi (AL/MS) May 7-10, 2019. This dataset, Grand_Bay_2019_MBES_xyz.zip, includes the processed point data (x,y,z), as derived from a 1-meter (m) bathymetric grid from two separate sensor configurations, which were acquired independently. One configuration utilized a tilted ... |
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Footprints and producers of source data used to create northern portion of the high-resolution (1 m) San Francisco Bay, California, digital elevation model (DEM)
Polygon shapefile showing the footprint boundaries, source agency origins, and resolutions of compiled bathymetric digital elevation models (DEMs) used to construct a continuous, high-resolution DEM of the northern portion of San Francisco Bay. |
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Digital elevation model (DEM) of northern San Francisco Bay, California, created using bathymetry data collected between 1999 and 2016 (MLLW)
A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the northern portion of San Francisco Bay, which includes San Pablo Bay, Carquinez Strait, and portions of Suisun Bay, was constructed from bathymetric surveys collected from 1999 to 2016. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and ... |
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Digital elevation model (DEM) of northern San Francisco Bay, California, created using bathymetry data collected between 1999 and 2016 (NAVD88)
A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the northern portion of San Francisco Bay, which includes San Pablo Bay, Carquinez Strait, and portions of Suisun Bay, was constructed from bathymetric surveys collected from 1999 to 2016. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and ... |
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Footprints and producers of source data used to create southern portion of the high-resolution (1 m) San Francisco Bay, California, digital elevation model (DEM)
Polygon shapefile showing the footprint boundaries, source agency origins, and resolutions of compiled bathymetric digital elevation models (DEMs) used to construct a continuous, high-resolution DEM of the southern portion of San Francisco Bay. |
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Digital elevation model (DEM) of south San Francisco Bay, California, created using bathymetry data collected between 2005 and 2020 (MLLW)
A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the southern portion of San Francisco Bay, was constructed from bathymetric surveys collected from 2005 to 2020. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and interferometric side-scan sonar systems. Of those 93 surveys, 75 consist of swaths of data ... |
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Digital elevation model (DEM) of south San Francisco Bay, California, created using bathymetry data collected between 2005 and 2020 (NAVD88)
A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the southern portion of San Francisco Bay, was constructed from bathymetric surveys collected from 2005 to 2020. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and interferometric side-scan sonar systems. Of those 93 surveys, 75 consist of swaths of data ... |
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Bathymetric digital elevation model (DEM) of Eastern Dry Rocks coral reef, Florida, 2021
A digital elevation model (DEM) was created from underwater images collected at Eastern Dry Rocks coral reef near Key West, Florida, in May 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was derived in Metashape (ver. 1.6.5) from the point cloud, but it excludes the 'low noise' class. The DEM covers a rectangular area of seafloor ... |
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Storm-Impact Scenario XBeach Model Inputs – Initial Bathymetry and Topography Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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ESRI Format Binary Grid of the Merged Bathymetry and Elevation Data from the Potomac River/Chesapeake Bay Area For Use With USGS Cruise 06018 (POTO_AREA)
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
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Digital Elevation Model of Oxbow Reservoir, Placer County, California, October 2022
This portion of the data release presents a digital elevation model (DEM) of portions of Oxbow Reservoir in Placer County, California. The DEM was created using topographic survey data collected on 26 October 2022, when the reservoir was partially de-watered to allow repairs to the dam infrastructure following the Mosquito Fire. Although the gates of the dam were open during this time, significant portions of the reservoir site remained inaccessible to surveyors due to the continued flow of the Middle Fork ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Initial_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Initial_Elevations_RS)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
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Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Initial_Elevations_RS_MP)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Initial_Elevations_RS_MP_PH)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Initial_Elevations_RS_PH)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Digital elevation models (DEMs) of the Elwha River delta, Washington, August 2022
This portion of the USGS data release presents digital elevation models (DEMs) derived from bathymetric and topographic surveys conducted on the Elwha River delta in August 2022 (USGS Field Activity Number 2022-638-FA). Nearshore bathymetry data were collected using two personal watercraft (PWCs) and a kayak equipped with single-beam echosounders and survey-grade global navigation satellite systems (GNSS) receivers. Topographic data were collected on foot with survey-grade GNSS receivers mounted on ... |
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Digital elevation models (DEMs) of the Elwha River delta, Washington, May 2011
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in May 2011. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity ... |
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BITH2014_CanyonlandsUNRCorridorUnits_EAARLB_BE_z15_n88g12A_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for EAARL-B Topography—Big Thicket National Preserve: Canyonlands and Upper Neches River Corridor Units, Texas, 2014
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Canyonlands and Upper Neches River Corridor Units of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 21, 23, 25, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced ... |
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BITH2014_CanyonlandsUNRCorridorUnits_EAARLB_FS_z15_n88g12A_mosaic_metadata: Lidar-derived First-Surface Digital Elevation Model (DEM) Mosaic for EAARL-B Topography—Big Thicket National Preserve: Canyonlands and Upper Neches River Corridor Units, Texas, 2014
A first-surface topography Digital Elevation Model (DEM) mosaic for the Canyonlands and Upper Neches River Corridor Units of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 21, 23, 25, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced ... |
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ElevMHW: Elevation adjusted to local mean high water: Assateague Island, MD & VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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BITH2014_LittlePineIslandBayouCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for EAARL-B Topography—Big Thicket National Preserve: Little Pine Island Bayou Corridor Unit, Texas, 2014
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Little Pine Island Bayou Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 15, 21, 22, 26, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar ... |
Info |
Digital elevation models (DEMs) of the Elwha River delta, Washington, August 2011
This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in August 2011. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented ... |
Info |
BITH2014_LittlePineIslandBayouCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: Lidar-Derived First-Surface Digital Elevation Model (DEM) Mosaic for EAARL-B Topography—Big Thicket National Preserve: Little Pine Island Bayou Corridor Unit, Texas, 2014
A first-surface topography Digital Elevation Model (DEM) mosaic for the Little Pine Island Bayou Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 15, 21, 22, 26, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar ... |
Info |
ElevMHW: Elevation adjusted to local mean high water: Assawoman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
Digital elevation models (DEMs) of northern Monterey Bay, California, October 2014
This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in October 2014. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at ... |
Info |
ElevMHW: Elevation adjusted to local mean high water: Cape Hatteras, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-25 Years From 2001 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-25 Years From 2001 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-25 Years From 2011 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-25 Years From 2011 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida-25 Years From 2014 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—25 Years From 2014 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-50 Years From 2001 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ... |
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30 meter Esri binary grids of predicted elevation with respect to projected sea levels for the Northeastern U.S. from Maine to Virginia for the 2020s, 2030s, 2050s and 2080s (Albers, NAD 83)
The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-50 Years From 2001 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ... |
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30 meter Esri binary grids of probability of predicted elevation with respect to projected sea levels for the Northeastern U.S. from Maine to Virginia for the 2020s, 2030s, 2050s and 2080s (Albers, NAD 83)
The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-50 Years From 2011 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-50 Years From 2011 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ... |
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Digital elevation model (DEM) of Black Beach, Falmouth, Massachusetts on 18 March 2016 (32-bit GeoTIFF)
Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—50 Years From 2014 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ... |
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Lower Florida Keys-Seafloor elevation change in Maui, St. Croix, St. Thomas, and the Florida Keys
Coral reefs serve as natural barriers that protect adjacent shorelines from coastal hazards such as storms, waves and erosion but projections indicate global degradation of coral reefs due to anthropogenic impacts and climate change will cause a transition to net erosion by mid-century. The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by measuring ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—50 Years From 2014 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ... |
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Seafloor Elevation Change From 2004 to 2016 at Looe Key, Florida Keys
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes at Looe Key near Big Pine Key, Florida (FL), within a 16.4 square-kilometer area between 2004 and 2016. USGS staff used light detection and ranging (lidar)-derived data acquired by the U.S. Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX) between December 1 and 31, 2004 (USACE-JALBTCX) and the National Oceanic and ... |
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Continuous and optimized 3-arcsecond elevation model for the United States east coast (32-bit GeoTiff, geographic, NAD83)
Investigations of coastal change and coastal resources often require continuous elevation profiles from the seafloor to coastal terrestrial landscapes. Differences in elevation data collection in the terrestrial and marine environments result in separate elevation products that may not share a vertical datum. This data release contains the compilation of multiple elevation products into a continuous digital elevation model at a resolution of 3-arcseconds (approximately 90 meters) from the terrestrial ... |
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Continuous and optimized 3-arcsecond elevation model for the United States west coast (32-bit GeoTiff, geographic, NAD83)
Investigations of coastal change and coastal resources often require continuous elevation profiles from the seafloor to coastal terrestrial landscapes. Differences in elevation data collection in the terrestrial and marine environments result in separate elevation products that may not share a vertical datum. This data release contains the assimilation of multiple elevation products into a continuous digital elevation model at a resolution of 3-arcseconds (approximately 90 meters) from the terrestrial ... |
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Seafloor Elevation Change From 2016 to 2017 at Looe Key, Florida Keys-Impacts From Hurricane Irma (version 2.0)
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes at Looe Key near Big Pine Key, Florida (FL), within a 19.7 square-kilometer area following Hurricane Irma's landfall in September 2017. USGS staff used light detection and ranging (lidar)-derived data acquired by the National Oceanic and Atmospheric Administration (NOAA) between July 21 and November 21, 2016 and USGS multibeam data collected December 12-17, 2017 (Fredericks ... |
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Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-75 Years From 2001 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-75 Years From 2001 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-75 Years From 2011 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-75 Years From 2011 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—75 Years From 2014 Based on Historical Rates of Mean Elevation Change
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ... |
Info |
Maui, Hawaii-Seafloor elevation change in Maui, St. Croix, St. Thomas, and the Florida Keys
Coral reefs serve as natural barriers that protect adjacent shorelines from coastal hazards such as storms, waves and erosion but projections indicate global degradation of coral reefs due to anthropogenic impacts and climate change will cause a transition to net erosion by mid-century. The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by measuring ... |
Info |
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—75 Years From 2014 Based on Historical Rates of Mean Erosion
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ... |
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Projected Seafloor Elevation Change and Relative Sea Level Rise Surrounding Maui, Hawaii 25, 50, 75, and 100 Years from 1999
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes surrounding Maui, Hawaii. Changes in seafloor elevation were calculated using historical bathymetric point data from the 1960s (see Yates and others, 2017a) and light detection and ranging (lidar)-derived data acquired in 1999 (NOAA, 2013) using methods outlined in Yate and others (2017b). An elevation change analysis between the 1960s and 1999 data was performed to quantify ... |
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ElevMHW: Elevation adjusted to local mean high water: Cape Lookout, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Snap Raster used to create interpolated digital elevation models (DEMs) in the nearshore around Ship, Horn, and Petit Bois Islands, Mississippi: 1916 to 1920, 2008 to 2009 and 2016
To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. This USGS data release includes three digital elevation models (DEMs) for 1916 to 1920, 2008 ... |
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Digital elevation models (DEMs) of northern Monterey Bay, California, March 2015
This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in March 2015. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a ... |
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ElevMHW: Elevation adjusted to local mean high water: Coast Guard Beach, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Cobb Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Fisherman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
Digital elevation models (DEMs) of northern Monterey Bay, California, September and October 2015
This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in September and October 2015. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS ... |
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ElevMHW: Elevation adjusted to local mean high water: Metompkin Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Monomoy Island, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
ElevMHW: Elevation adjusted to local mean high water: Myrtle Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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A seamless, high-resolution, coastal digital elevation model (DEM) for Southern California
A seamless, three-meter digital elevation model (DEM) was constructed for the entire Southern California coastal zone, extending 473 km from Point Conception to the Mexican border. The goal was to integrate the most recent, high-resolution datasets available (for example, Light Detection and Ranging (Lidar) topography, multibeam and single beam sonar bathymetry, and Interferometric Synthetic Aperture Radar (IfSAR) topography) into a continuous surface from at least the 20-m isobath to the +20-m elevation ... |
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Digital elevation models (DEMs) of northern Monterey Bay, California, March 2016
This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in March 2016. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a ... |
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Hydro-flattened Elevation Area Outlines for DEMs of the North-Central California Coast (Hydro_flattened_water.shp)
A GIS polygon shapefile outlining the extent of small lakes or ponds within the terrain that were assigned a hydo-flattened elevation during lidar post-processing. DEM elevations within these small areas reflect water surface elevations, not bathymetric elevations. |
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ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Breton2014_IFB_SBB_100_NAD83_NAVD88_UTM16N_GEOID09_DEM: A geotiff of the 100-meter cell size digital elevation model derived from the processed interferometric swath, single beam bathymetry, and Lidar data points.
As part of the Barrier Island Monitoring Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off Breton and Gosier Islands, Louisiana, in July and August of 2014. To assist the United States Fish and Wildlife Service (USFWS) with restoration planning efforts, the USGS was tasked with answering fundamental questions about the physical environment of the southern Chandeleur Islands, including the geology, ... |
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ElevMHW: Elevation adjusted to local mean high water: Parker River, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Digital elevation model (DEM) of Big Pine Ledge, Florida, 2022
A digital elevation model (DEM) was created from underwater images collected at Big Pine Ledge (BPL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.8.5) from the point cloud and includes points from both classes. The DEM covers a ... |
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ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Digital elevation models (DEMs) of northern Monterey Bay, California, September and October 2016
This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in September and October 2016. Bathymetry data were collected using a personal watercraft (PWC) and small boat, each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using ... |
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ElevMHW: Elevation adjusted to local mean high water: Ship Shoal Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (July 21, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (September 8, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (September 11, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Orthoimagery of Big Pine Ledge, Florida, 2021
A seabed orthoimage was developed from underwater images collected at Big Pine Ledge, Florida, in July 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 650x120 meters (0.078 square kilometers) in size. It was created using image-averaging methods and saved as a tiled GeoTIFF raster at 5-millimeter resolution. |
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Bathymetry from multibeam echosounder data collected offshore of Cape Mendocino, California
This part of USGS Data Series 781 (Golden, 2019) presents 2-m-resolution bathymetry data for the Offshore of Cape Mendocino, California, map area. Bathymetry data were collected by Fugro Pelagos in 2007 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounder systems. The data were processed by the California State University Monterey Bay Seafloor Mapping Lab. The bathymetry data are available as a georeferenced TIFF image. |
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Swath bathymetry data collected in 2013 off the islands of Maui and Kaho`olawe, Hawaii, during field activity A-01-13-HW
1-m resolution bathymetry data were collected during a February 2013 SWATHPlus survey offshore of the Hawaiian Islands of Maui and Kaho`olawe. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC), with fieldwork activity number A-01-13-HW. The 1-m bathymetry data are provided as a GeoTIFF file. |
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Point cloud data of Big Pine Ledge, Florida, 2021
A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Big Pine Ledge, Florida, in July 2021 using the SQUID-5 camera system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, and RGB colors derived from the color-corrected imagery. LAS (and its compressed form, LAZ) is an open format developed for the efficient use of point cloud lidar data. |
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Nearshore Single-Beam Bathymetry Data: Madeira Beach, Florida, February 2017
In February 2017, the United States Geological Survey Saint Petersburg Coastal and Marine Science Center (USGS SPCMSC) conducted multibeam and single-beam bathymetric surveys of the nearshore waters off Madeira Beach, Florida. These data were collected as part of a regional study designed to better understand coastal processes on barrier islands and sandy beaches. Results from this study will be incorporated with observations from other regional studies in order to validate operational water level and ... |
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Nearshore bathymetry of the Columbia River littoral cell, Washington and Oregon, 2022
This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell and mouth of the Columbia River, Washington and Oregon, in 2022 (USGS Field Activity Number 2022-641-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of either an Odom Echotrac CV-100 or CEE Hydrosystems Ceescope single-beam ... |
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Beach topography of the Columbia River littoral cell, Washington and Oregon, 2022
This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2022 (USGS Field Activity Number 2022-641-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used ... |
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Nearshore bathymetry of the Columbia River littoral cell, Washington and Oregon, 2023
This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell and mouth of the Columbia River, Washington and Oregon, in 2023 (USGS Field Activity Number 2023-644-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of either an Odom Echotrac CV-100 or CEE Hydrosystems Ceescope single-beam ... |
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Beach topography of the Columbia River littoral cell, Washington and Oregon, 2023
This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2023 (USGS Field Activity Number 2023-644-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used ... |
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Lifespan of marsh units in Maine salt marshes
This data release contains coastal wetland synthesis products for the state of Maine. Metrics for resiliency, including the unvegetated to vegetated ratio (UVVR), marsh elevation, tidal range, and lifespan, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the ... |
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USGS CoastCam at Isla Verde, Puerto Rico: 2018-2019 GNSS Topography Survey Data
This data release presents the post-processed Global Navigation Satellite System (GNSS) ground-survey data acquired during the installation of the Argus camera at Isla Verde, Puerto Rico. The data contains topographic survey data collected during the installation of the camera. Data were collected on foot by a person equipped with a GNSS antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ). The GNSS measurements were made using Post-Processed Kinematic (PPK) corrections ... |
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Nearshore Multibeam Bathymetry Data: Madeira Beach, Florida, February 2017
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Madeira Beach, Florida February 13-17, 2017. This dataset, Madeira_Beach_2017_MBES_1m_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. |
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2001 Gulf Coast USGS/NASA ATM Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2005 East Coast (DE, MD, NJ, NY, NC, and VA) USACE NCMP Topobathy Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2012 Post-Hurricane Sandy Long Island, New York USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2016 USACE Post-Hurricane Matthew Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2016 Massachusetts NOAA Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2017 Georgia through New York USACE NCMP Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ... |
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2017 Florida West Coast NOAA Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches.Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 Alabama and Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 East Coast (VA, NC, SC) USACE NCMP Post-Florence Topobathy Lidar-Derived Dune Crest, Toe, and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 East Coast (NC) USACE NCMP Topobathy Lidar Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 Mississippi and Alabama USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2019 North Carolina and Virginia USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (L=lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2019 North Carolina and Virginia Post-Dorian USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2020 New Jersey and New York USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2021 New York State Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ... |
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2022 New Jersey and New York USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ... |
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2020 New Jersey USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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1998 MA, NY, MD, and VA USGS/NASA ATM2 Lidar-derived dune crest, toe and shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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GNSS Topography Survey Data Collected from Tres Palmas, Rincón, Puerto Rico
This data release presents the post-processed Global Navigation Satellite System (GNSS) ground-survey data acquired during the installation of a camera system at Tres Palmas, Rincón, Puerto Rico (PR). The data contains topographic survey data collected during the installation of the camera. Data were collected on foot, by a person equipped with a GNSS antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ). The GNSS measurements were made using Post-Processed Kinematic (PPK) ... |
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CoconutIsland_2023_MBES: High-resolution Geophysical and Imagery Data Collected in May 2023 Near Fort Hase, Marine Corps Base Hawaii
An Ellipsoidally Referenced Survey (ERS) using a Norbit Winghead multibeam echosounder, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Coconut Island, on the island of Oahu, May 7, 2023. This dataset, CoconutIsland_2023_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 0.25 meter (m) bathymetric grid and the dataset CoconutIsland_2023_MBES_Backscatter.zip includes the acoustic backscatter intensity ... |
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FtHase_2023_MBES: High-resolution Geophysical and Imagery Data Collected in May 2023 Near Fort Hase, Marine Corps Base Hawaii
An Ellipsoidally Referenced Survey (ERS) using a Norbit Winghead multibeam echosounder, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Fort Hase Marine Corps Base Hawaii (MCBH), on the island of Oahu, May 4-12, 2023. This dataset, FtHase_2023_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid and the dataset FtHase_2023_MBES_Backscatter.zip includes the acoustic backscatter ... |
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USGS CoastCam at Waiakāne, Moloka'i, Hawai'i: 2018 GNSS Topography Survey Data
This data release presents the post-processed global navigation satellite system (GNSS) ground-survey data acquired during the installation of the Argus camera at Waiakāne, Moloka'i, Hawai'i. The data contains topographic survey data collected during the installation of the camera. Data were collected on foot by a person equipped with a GNSS antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ). The GNSS measurements were made using Post-Processed Kinematic (PPK) ... |
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2014 Post-Hurricane Sandy SC to NY NOAA NGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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ATLANTIC - Coastal Vulnerability to Sea-Level Rise: A Preliminary Database for the U.S. Atlantic Coast
The goal of this project is to provide a preliminary overview, at a National scale, the relative susceptibility of the Nation's coast to sea-level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of ... |
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GULF - Coastal Vulnerability to Sea-Level Rise: U.S. Gulf Coast
The goal of this project is to quantify, at the National scale, the relative susceptibility of the Nation's coast to sea-level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of regions where ... |
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PACIFIC - Coastal Vulnerability to Sea-Level Rise: U.S. Pacific Coast
The goal of this project is to quantify, at the National scale, the relative susceptibility of the Nation's coast to sea-level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of regions where ... |
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2 meter Arc Raster grid of bathymetry acquired along cross lines using a SEA Ltd. SWATHplus-H interferometric sonar within Barnegat Bay New Jersey by the U.S. Geological Survey in 2011, 2012, and 2013 (Esri binary grid, UTM 18N, WGS 84)
Water quality in the Barnegat Bay-Little Egg Harbor estuary along the New Jersey coast is the focus of a multidisciplinary research project begun in 2011 by the U.S. Geological Survey (USGS) in partnership with the New Jersey Department of Environmental Protection. This narrow estuary is the drainage for the Barnegat Watershed and flushed by just three inlets connecting it to the Atlantic Ocean, is experiencing degraded water quality, algal blooms, loss of seagrass, and increases in oxygen -depletion events ... |
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10-m interval contours of smoothed multibeam bathymetry of Massachusetts Bay (MB_10MCTR9X9.SHP, Geographic, NAD83)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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5-m interval contours of smoothed multibeam bathymetry of Massachusetts Bay (MB_5MCTR9X9.SHP, Geographic, NAD83)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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10-m resolution image of shaded relief multibeam bathymetry in Massachusetts Bay, pseudocolored by backscatter intensity (MB_BACKPC10M.TIF)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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10-m resolution grid of multibeam bathymetry in Massachusetts Bay (MB_BATHY10M)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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10-m resolution image of shaded relief multibeam bathymetry in Massachusetts Bay, colored by water depth (MB_BATHYCLR10M.TIF)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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10-m resolution image of shaded relief multibeam bathymetry in Massachusetts Bay (MB_SRELIEF10M.TIF)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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1-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 1 (Q1_1MCTR.SHP)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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5-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 1 (Q1_5MCTR.SHP)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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6-m resolution grid of multibeam bathymetry in western Massachusetts Bay map Quadrangle 1 (Q1_BATHY6M)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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6-m resolution gray-scale image of shaded-relief multibeam bathymetry in western Massachusetts Bay map Quadrangle 1 (Q1_SRELIEF.TIF)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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1-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 2 (Q2_1MCTR.SHP)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
Info |
5-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 2 (Q2_5MCTR.SHP)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
Info |
6-m resolution grid of multibeam bathymetry in western Massachusetts Bay map Quadrangle 2 (Q2_BATHY6M)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
Info |
6-m resolution gray-scale image of shaded-relief multibeam bathymetry in western Massachusetts Bay map Quadrangle 2 (Q2_SRELIEF.TIF)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
Info |
1-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 3 (Q3_1MCTR.SHP)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
Info |
5-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 3 (Q3_5MCTR.SHP)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
Info |
6-m resolution grid of multibeam bathymetry in western Massachusetts Bay map Quadrangle 3 (Q3_BATHY6M)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
Info |
1-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangles 1-3 (WMB_1MCTR.SHP)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
Info |
6-m resolution grid of multibeam bathymetry of western Massachusetts Bay map Quadrangles 1-3 (WMB_BATHY6M)
The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ... |
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10 m bathymetric contours for the Southwest Washington Study area (BATHY)
Two 21-day field operations were conducted in 1997 and 1998 in the estuaries and on the inner continental shelf off the northern Oregon and southern Washington coast. These cruises aboard the R/V Corliss were run in order to generate reconnaissance maps of the seafloor geology and the shallow subsurface stratigraphy using sidescan-sonar and seismic-reflection mapping techniques. The 1998 cruise also collected sediment grab samples, bottom photographs, and video images to verify the sidescan-sonar imagery ... |
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5 meter bathymetric contours derived from data collected during U.S. Geological Survey Geophysical Surveys of Bear Lake, Utah-Idaho, September, 2002 cruise 02031(02031_BATHY_5M)
Bear Lake is a tectonic lake that has existed for at least several hundred thousand years. The lake basin is a relatively simple half graben, a spoon-shaped depression tilted toward the main fault on the east side of the lake. The U.S. Geological Survey, in cooperation with researchers from several universities, has been studying the sediments of Bear Lake since 1996. The general purpose of this effort is to reconstruct past limnological conditions and regional climate on a range of timescales, from ... |
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Geophysical Surveys of Bear Lake, Utah-Idaho, September 2002 - Bathymetric Grid (BATHYGRD.TIF)
Bear Lake is a tectonic lake that has existed for at least several hundred thousand years. The lake basin is a relatively simple half graben, a spoon-shaped depression tilted toward the main fault on the east side of the lake. The U.S. Geological Survey, in cooperation with researchers from several universities, has been studying the sediments of Bear Lake since 1996. The general purpose of this effort is to reconstruct past limnological conditions and regional climate on a range of timescales, from ... |
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Surface Representing the Floor of Lake Mead and the surrounding area: UTM Projection 10m cellsize
Lake Mead is a large interstate reservoir located in the Mojave Desert of southeastern Nevada and northwestern Arizona. It was impounded in 1935 by the construction of Hoover Dam and is one of a series of multi-purpose reservoirs on the Colorado River. The lake extends 183 km from the mouth of the Grand Canyon to Black Canyon, the site of Hoover Dam, and provides water for residential, commercial, industrial, recreational, and other non-agricultural users in communities across the southwestern United ... |
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Pulley Ridge Swath Bathymetry Grid - filtered (ALLPR_FILCROP.GRD, UTM 17N, NAD83)
Pulley Ridge is a series of drowned barrier islands that extends almost 200 km in 60-100 m water depths. This drowned ridge is located on the Florida Platform in the southeastern Gulf of Mexico about 250 km west of Cape Sable, Florida. This barrier island chain formed during the initial stage of the Holocene marine transgression. These islands were then submerged and left abandoned near the outer edge of the Florida Platform. The southern portion of Pulley Ridge hosts zooxanthellate scleractinian corals, ... |
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Nahant to Gloucester, Massachusets Depth to Bedrock (bedrock_depth)
These data are high-resolution seismic reflection profile data of the seafloor offshore of Massachusetts, from Nahant to Gloucester. Approximately 1,175 kms of seismic reflection profile data were collected using a Knudsen 320b chirp system Data were processed using SIOSEIS (Scripps Institute of Oceanography) and Seismic Unix (Colorado School of Mines) to produce segy files and jpg images of the profiles. Data were then imported into Landmark SeisWorks, an interactive computer system where horizons were ... |
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Nahant to Gloucester, Massachusetts Maximum Likelihood Bottom Classification (mlclass5)
These data are high-resolution maximum likelihood classification of the seafloor offshore of Massachusetts, from Nahant to Gloucester. Approximately 127 km² of the inner shelf were mapped in the nearshore region between the 10m and 40-m isobath. |
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Nahant to Gloucester, Massachusetts Swath Bathymetry of the South Essex Survey Area (se_5mbath)
These data are high-resolution bathymetric soundings of the seafloor offshore of Massachusetts, from Nahant to Gloucester. Approximately 127 km² of the inner shelf were mapped in the nearshore region between the 10m and 40-m isobath. |
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Nahant to Gloucester, Massachusetts Bathymetric Slope in degrees (slopedeg_fm3)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program. Woods Hole Science Center. Project data were collected during two separate surveys in the Fall of 2003 (RAFA03007) and the Spring of 2004 (RAFA04002). Bathymetric data were collected with a SEA/Submetrix 2000 series interferometric 234 kHz sonar. The sonar was pole-mounted on the R/V Rafael. Survey line spacing was 100m |
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Hillshade of Swath Bathymetry collected by the USGS offshore of the Grand Strand, South Carolina, 1999-2003 (BATHY_HILLSH, grid)
In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ... |
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Bathymetric Contours within the inner shelf of Long Bay, South Carolina (CON_1M, 1 meter interval: Polyline shapefile)
In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ... |
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Multibeam Bathymetry 2 meter/pixel of Boston Harbor and Approaches (bh_2mmbbath)
These data are high-resolution bathymetric measurements of the seafloor from Boston Harbor and the harbor approaches, Massachusetts. Approximately 170 km² of sidescan sonar and bathymetric data were collected by the National Oceanic and Atmospheric Administration (NOAA) Ship Whiting in 2000 and 2001 and reprocessed and gridded by the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS). |
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Hillshade of Multibeam Bathymetry 2 meter/pixel of Boston Harbor and Approaches (bh_2mmbhsf)
These data are high-resolution bathymetric measurements of the seafloor from Boston Harbor and the harbor approaches, Massachusetts. Approximately 170 km² of sidescan sonar and bathymetric data were collected by the National Oceanic and Atmospheric Administration (NOAA) Ship Whiting in 2000 and 2001 and reprocessed and gridded by the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS). |
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ArcInfo Grid of the 30 meter pixel Composite Bathymetry of Boston Harbor and Approaches (BH_30MBATH, UTM 19, WGS84)
These data are high-resolution bathymetric measurements of the seafloor from Boston Harbor and the harbor approaches, Massachusetts. Approximately 170 km square of sidescan sonar and bathymetric data were collected by the National Oceanic and Atmospheric Administration (NOAA) Ship Whiting in 2000 and 2001 and reprocessed and gridded by the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS). |
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Shaded-relief GeoTIFF image of a portion of Cape Cod and the surrounding sea floor
In order to test hypotheses about groundwater flow under and into estuaries and the Atlantic Ocean, geophysical surveys, geophysical probing, submarine groundwater sampling, and sediment coring were conducted by U.S. Geological Survey (USGS) scientists at Cape Cod National Seashore (CCNS) from 2004 through 2006. Coastal resource managers at CCNS and elsewhere are concerned about nutrients that are entering coastal waters via submarine groundwater discharge, which are contributing to eutrophication and ... |
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25m Hillshaded Bathymetric ArcRaster Grid of Apalachicola Bay and St. George Sound, FL (APBAY25HS)
These data were collected under a cooperative mapping program between the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration Coastal Services Center (NOAA\CSC), and the Apalachicola National Estuarine Research Reserve (NERR). The primary objectives of this program were to collect marine geophysical data to develop a suite of seafloor maps to better define the extent of oyster habitats, the overall seafloor geology of the bay and provide updated information for management of ... |
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2 meter ArcRaster grid of the Swath Bathymetry of Apalachicola Bay, Florida (APBAY2MBATH)
These data were collected under a cooperative mapping program between the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration Coastal Services Center (NOAA\CSC), and the Apalachicola National Estuarine Research Reserve (NERR). The primary objectives of this program were to collect marine geophysical data to develop a suite of seafloor maps to better define the extent of oyster habitats, the overall seafloor geology of the bay and provide updated information for management of ... |
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2m GeoTIFF of Swath Bathymetry of Apalachicola Bay, Florida (APBAY2M_BATH.tif)
These data were collected under a cooperative mapping program between the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration Coastal Services Center (NOAA\CSC), and the Apalachicola National Estuarine Research Reserve (NERR). The primary objectives of this program were to collect marine geophysical data to develop a suite of seafloor maps to better define the extent of oyster habitats, the overall seafloor geology of the bay and provide updated information for management of ... |
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25m Bathymetric ArcRaster Grid of Apalachicola Bay and St. George Sound, Florida (APBAYBATH25M)
These data were collected under a cooperative mapping program between the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration Coastal Services Center (NOAA\CSC), and the Apalachicola National Estuarine Research Reserve (NERR). The primary objectives of this program were to collect marine geophysical data to develop a suite of seafloor maps to better define the extent of oyster habitats, the overall seafloor geology of the bay and provide updated information for management of ... |
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2 meter ArcRaster Grid of Swath Bathymetry of St. George Sound, Florida (STG2MBath)
These data were collected under a cooperative mapping program between the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration Coastal Services Center (NOAA\CSC), and the Apalachicola National Estuarine Research Reserve (NERR). The primary objectives of this program were to collect marine geophysical data to develop a suite of seafloor maps to better define the extent of oyster habitats, the overall seafloor geology of the bay and provide updated information for management of ... |
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2m GeoTIFF image of Swath Bathymetry of St. George Sound, Florida (STGSND2M_BATH.TIF)
These data were collected under a cooperative mapping program between the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration Coastal Services Center (NOAA\CSC), and the Apalachicola National Estuarine Research Reserve (NERR). The primary objectives of this program are to collect marine geophysical data and develop a suite of seafloor maps to better define the extent of oyster habitats and the overall seafloor geology of the bay to provide updated information for management of ... |
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10 meter bathymetric contours of the Cape Ann - Salisbury Beach MA Survey Area (BATHCNTR_10M, geographic, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ... |
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5 meter ArcRaster grid of swath bathymetry of inshore area of Cape Ann - Salisbury Beach Massachusetts survey area (BATH_IS5m, UTM Zone 19, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ... |
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5 meter ArcRaster grid of multibeam bathymetry of the offshore area of Cape Ann - Salisbury Beach Massachusetts Survey Area (BATH_OS5m, UTM Zone 19, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ... |
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5 meter color-hillshaded relief GeoTIFF of both the inshore and offshore area of Cape Ann - Salisbury Beach Survey Area (CABATH5M_GEOG.TIF, Geographic, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ... |
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5 meter ArcRaster Bathymetric grid of both the inshore and offshore area of Cape Ann - Salisbury Beach Survey Area (CABATH5M, UTM Zone 19, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ... |
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5 meter ArcRaster Bathymetric Hillshade of both the inshore and offshore portions of the Cape Ann - Salisbury Beach Massachusetts Survey Area (CABATH5MHS, UTM Zone 19, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ... |
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Bathymetric data collected by the U.S. Geological Survey offshore of the Chandeleur Islands, LA, 2006-2007 (BATHY_GRD.ASC, ESRI ASCII GRID)
In 2006 and 2007, the U.S. Geological Survey, in partnership with Louisiana Department of Natural Resources and the University of New Orleans, conducted geologic mapping to characterize the sea floor and shallow subsurface stratigraphy offshore of the Chandeleur Islands in Eastern Louisiana. The mapping was carried out during two cruises on the R/V Acadiana. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (234 kHz), Klein 3000 dual frequency sidescan sonar, and an ... |
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Hillshaded relief produced from bathymetric data collected by the U.S. Geological Survey offshore of the Chandeleur Islands, LA, 2006-2007 (BATHY_HILLSH.ASC, ESRI ASCII GRID)
In 2006 and 2007, the U.S. Geological Survey, in partnership with Louisiana Department of Natural Resources and the University of New Orleans, conducted geologic mapping to characterize the sea floor and shallow subsurface stratigraphy offshore of the Chandeleur Islands in Eastern Louisiana. The mapping was carried out during two cruises on the R/V Acadiana. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (234 kHz), Klein 3000 dual frequency sidescan sonar, and an ... |
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1-meter contours produced from bathymetric data collected by the U.S. Geological Survey offshore of the Chandeleur Islands, LA, 2006-2007 (cont_1m, polyline)
In 2006 and 2007, the U.S. Geological Survey, in partnership with Louisiana Department of Natural Resources and the University of New Orleans, conducted geologic mapping to characterize the sea floor and shallow subsurface stratigraphy offshore of the Chandeleur Islands in Eastern Louisiana. The mapping was carried out during two cruises on the R/V Acadiana. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (234 kHz), Klein 3000 dual frequency sidescan sonar, and an ... |
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Location of radiocarbon age dates sampled from vibracores collected by the U.S. Geological Survey within Apalachicola Bay, Florida, 2007 (APP-07_AgeDates, points)
In 2007, the U.S. Geological Survey collected 24 vibracores within Apalachicola Bay, Florida. The vibracores were collected using a Rossfelder electric percussive (P-3) vibracore system during a cruise on the R/V Gilbert. Selection of the core sites was based on a geophysical survey that was conducted during 2005 and 2006 in collaboration with the National Oceanic and Atmospheric Administration’s (NOAA) Coastal Services Center (CSC) and the Apalachicola Bay National Estuarine Research Reserve. Available ... |
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Location and analysis information of vibracores collected by the U.S. Geological Survey within Apalachicola Bay, Florida, 2007 (APP-07_CoreLocations, points)
In 2007, the U.S. Geological Survey collected 24 vibracores within Apalachicola Bay, Florida. The vibracores were collected using a Rossfelder percussive (P-3) electric vibracore system during a cruise on the R/V Gilbert. Selection of the core sites was based on a geophysical survey that was conducted during 2005 and 2006 in collaboration with the National Oceanic and Atmospheric Administration’s (NOAA) Coastal Services Center (CSC) and the Apalachicola Bay National Estuarine Research Reserve. Available ... |
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Location and analysis of grain-size data sampled from vibracores collected by the U.S. Geological Survey within Apalachicola Bay, Florida, 2007 (APP-07_GrainSize, points)
In 2007, the U.S. Geological Survey collected 24 vibracores within Apalachicola Bay, Florida. The vibracores were collected using a Rossfelder electric percussive (P-3) vibracore system during a cruise on the R/V Gilbert. Selection of the core sites was based on a geophysical survey that was conducted during 2005 and 2006 in collaboration with the National Oceanic and Atmospheric Administration’s (NOAA) Coastal Services Center (CSC) and the Apalachicola Bay National Estuarine Research Reserve. Available ... |
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Location and analysis of microfossil samples from vibracores collected by the U.S. Geological Survey within Apalachicola Bay, Florida, 2007 (APP-07_Microfossils, points)
In 2007, the U.S. Geological Survey collected 24 vibracores within Apalachicola Bay, Florida. The vibracores were collected using a Rossfelder electric percussive (P-3) vibracore system during a cruise on the R/V Gilbert. Selection of the core sites was based on a geophysical survey that was conducted during 2005 and 2006 in collaboration with the National Oceanic and Atmospheric Administration’s (NOAA) Coastal Services Center (CSC) and the Apalachicola Bay National Estuarine Research Reserve. Available ... |
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10 meter bathymetric contours of the Duxbury-Hull MA Survey Area (DH_BATHCNTR_10m shapefile, Geographic, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine ... |
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Bathymetric data collected by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts between Duxbury and Hull (DH_bathy5m, Esri binary grid, UTM Zone 19, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine ... |
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ASCII grid of bathymetry data collected by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts between Duxbury and Hull with data gaps (DH_bathy_wgaps.asc, ARC/INFO ASCII GRID, UTM Zone 19, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine ... |
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Hillshaded relief produced from bathymetric data collected by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts between Duxbury and Hull (DH_hlshd5m, Esri binary grid, UTM Zone 19, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine ... |
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Text files of the navigation logged with HYPACK Software during surveys 06012 and 07001 conducted by the U.S. Geological Survey offshore of Massachusetts between Duxbury and Hull (DH_HYPACK_NAV)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine ... |
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Processed Continuous Resistivity Profile (CRP) Data Below the Sediment Water Interface From the Potomac River/Chesapeake Bay collected from Sept. 6, 2006 to Sept. 8, 2006 on USGS Cruise 06018 (MRG2006_ALLZYZ.SHP)
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
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Navigation and Bathymetry Points of Ship Position During Continuous Resistivity Profile Data Collection in the Potomac River/Chesapeake Bay on Sept. 6, 2006 on USGS Cruise 06018 (RESGPSPNTS_JD249.SHP)
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
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Navigation, Bathymetry and Temperature Points at the Ship Position During Continuous Resistivity Profile Data Collection in the Potomac River/Chesapeake Bay on Sept. 7, 2006 on USGS Cruise 06018 (RESGPSPNTS_JD250.SHP)
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
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Navigation, Bathymetry and Temperature Point at the Ship Position During Continuous Resistivity Profile Data Collection in the Potomac River/Chesapeake Bay on Sept. 8, 2006 on USGS Cruise 06018 (RESGPSPNTS_JD251.SHP)
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
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Processed Continuous Resistivity Profile Data Collected in the Potomac River/Chesapeake Bay on Sept. 6, 2006
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
Info |
Raw and Modified Raw Continuous Resistivity Profile Data Collected in the Potomac River/Chesapeake Bay on Sept. 6, 2006
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
Info |
Processed Continuous Resistivity Profile Data Collected in the Potomac River/Chesapeake Bay on Sept. 7, 2006
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
Info |
Raw and Modified Raw Continuous Resistivity Profile Data Collected in the Potomac River/Chesapeake Bay on Sept. 7, 2006
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
Info |
Processed Continuous Resistivity Profile Data Collected in the Potomac River/Chesapeake Bay on Sept. 8, 2006
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
Info |
Raw and Modified Raw Continuous Resistivity Profile Data Collected in the Potomac River/Chesapeake Bay on Sept. 8, 2006
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
Info |
SHIP NAVIGATION: ANSI Text File of the Navigation and Bathymetry Recorded by the Ship's Differential Global Positioning System (DGPS) in the Potomac River/Chesapeake Bay from Sept. 6 to Sept. 8, 2006 - USGS Cruise 06018
In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ... |
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Bathymetric depth contours at 5 meter intervals of interferometric sonar data collected offshore of Massachusetts within northern Cape Cod Bay (CCB_5MCNTR Esri Shapefile, Geographic, WGS84).
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat ... |
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Text files of the navigation logged with HYPACK Software during surveys 07002, and 08002 conducted by the U.S. Geological Survey offshore of Massachusetts within northern Cape Cod Bay (CCB_Hypack_Nav)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat ... |
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5-meter bathymetric contours generated from swath bathymetric data collected by the U.S. Geological Survey within the St. Clair River between Michigan and Ontario, Canada, 2008 (ESRI VECTOR SHAPEFILE, CON_5M)
In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the ... |
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Text files of the Differential Global Positioning System (DGPS) and Real-Time Kinematic (RTK) navigation logged with HYPACK software by the U.S. Geological Survey during Cruise 08016 within the St. Clair River between Michigan and Ontario, Canada, 2008
In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the ... |
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Modified Processed Continous Resistivity Profile Data Collected in the Corsica River Estuary, Maryland on May 15 and May 16 on USGS Cruise 07005
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
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Processed Continuous Resistivity Profile Data Collected in the Corsica River Estuary, Maryland on May 15, 2007 on USGS Cruise 07005
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
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Raw and Modified Raw Continuous Resistivity Profile Data Collected in the Corsica River Estuary, Maryland on May 15, 2007 on USGS Cruise 07005
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
Info |
Processed Continuous Resistivity Profile Data Collected in the Corsica River Estuary, Maryland on May 16, 2007 on USGS Cruise 07005
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
Info |
Raw and Modified Raw Continuous Resistivity Profile Data Collected in the Corsica River Estuary, Maryland on May 16, 2007 on USGS Cruise 07005
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
Info |
Processed Continuous Resistivity Profile Data Collected in the Corsica River Estuary, Maryland on May 17, 2007 on USGS Cruise 07005
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
Info |
Raw and Modified Raw Continuous Resistivity Profile Data Collected in the Corsica River Estuary, Maryland on May 17, 2007 on USGS Cruise 07005
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
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Ship Trackline along which Continuous Resistivity Profile Data were Collected in the Corsica River Estuary, Maryland on May 15, 2007 on USGS Cruise 07005 (RESGPSLNS_JD135.SHP)
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
Info |
Ship Trackline along which Continuous Resistivity Profile Data were Collected in the Corsica River Estuary, Maryland on May 16, 2007 on USGS Cruise 07005 (RESGPSLNS_JD136.SHP)
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
Info |
Ship Trackline along which Continuous Resistivity Profile Data were Collected in the Corsica River Estuary, Maryland on May 17, 2007 on USGS Cruise 07005 (RESGPSLNS_JD137.SHP)
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
Info |
Navigation and Bathymetry Points of Ship Position During Continuous Resistivity Profile Data Collection in the Corsica River Estuary, Maryland on May 15, 2007 on USGS Cruise 07005 (RESGPSPNTS_JD135.SHP)
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
Info |
Navigation and Bathymetry Points of Ship Position During Continuous Resistivity Profile Data Collection in the Corsica River Estuary, Maryland on May 16, 2007 on USGS Cruise 07005 (RESGPSPNTS_JD136.SHP)
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
Info |
Navigation and Bathymetry Points of Ship Position During Continuous Resistivity Profile Data Collection in the Corsica River Estuary, Maryland on May 17, 2007 on USGS Cruise 07005 f(RESGPSPNTS_JD137.SHP)
Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine the importance of nutrient delivery to Chesapeake Bay via this pathway. Resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge from this primarily agricultural watershed that may be contributing to eutrophication, harmful algal blooms, and fish kills. An interdisciplinary U.S. Geological Survey (USGS) science team ... |
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1-meter contours produced from swath bathymetry collected by the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL offshore of the Gulf Islands, MS, 2010 (ESRI polyline shapefile, tmunro_1m_bathycontours_MLLW.shp)
In 2010, the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL, in partnership with the U.S. Army Corps of Engineers, Mobile District conducted geologic mapping to characterize the seafloor and shallow subsurface stratigraphy offshore of the Gulf Islands of Mississippi. The mapping was carried out during two cruises in March, 2010 on the R/V Tommy Munro of Biloxi, MS. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (both 234 kHz and 468 kHz systems), ... |
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Swath bathymetry collected by the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL offshore of the Gulf Islands, MS, 2010 (ESRI binary grid, tmunro_50m)
In 2010, the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL, in partnership with the U.S. Army Corps of Engineers, Mobile District conducted geologic mapping to characterize the seafloor and shallow subsurface stratigraphy offshore of the Gulf Islands of Mississippi. The mapping was carried out during two cruises in March, 2010 on the R/V Tommy Munro of Biloxi, MS. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (both 234 kHz and 468 kHz systems), ... |
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40 meter ESRI binary grid of single beam and swath bathymetry of inner continental shelf north of Cape Hatteras, NC to Virginia border (nhatt, UTM Zone 18N, WGS 84)
The northeastern North Carolina coastal system, from False Cape, Virginia, to Cape Lookout, North Carolina, has been studied by a cooperative research program that mapped the Quaternary geologic framework of the estuaries, barrier islands, and inner continental shelf. This information provides a basis to understand the linkage between geologic framework, physical processes, and coastal evolution at time scales from storm events to millennia. The study area attracts significant tourism to its parks and ... |
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Structure grid of the depth to the Pliocene surface (Q0), inner shelf and back-barrier from Virginia border to Cape Lookout, North Carolina (q0depth,ESRI binary grid, 200 m cell size, UTM Zone 18N, WGS 84)
The northeastern North Carolina coastal system, from False Cape, Virginia, to Cape Lookout, North Carolina, has been studied by a cooperative research program that mapped the Quaternary geologic framework of the estuaries, barrier islands, and inner continental shelf. This information provides a basis to understand the linkage between geologic framework, physical processes, and coastal evolution at time scales from storm events to millennia. The study area attracts significant tourism to its parks and ... |
Info |
40 meter ESRI binary grid of swath bathymetry of inner continental shelf south of Cape Hatteras, NC to Cape Lookout, NC (shatt, UTM Zone 18N, WGS84)
The northeastern North Carolina coastal system, from False Cape, Virginia, to Cape Lookout, North Carolina, has been studied by a cooperative research program that mapped the Quaternary geologic framework of the estuaries, barrier islands, and inner continental shelf. This information provides a basis to understand the linkage between geologic framework, physical processes, and coastal evolution at time scales from storm events to millennia. The study area attracts significant tourism to its parks and ... |
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Raw continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 12, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
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Processed continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 13, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Raw and modified raw continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 13, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
RES2DINV format continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 13, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Processed continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 14, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Raw and modified raw continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 14, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
RES2DINV format continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 14, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Processed continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 15, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Raw and modified raw continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 15, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
RES2DINV format continuous resistivity profiling data collected in the Indian River Bay, Delaware, on April 15, 2010, on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Raw HYPACK navigation logged during U.S. Geological Survey Field Activity 2010-006-FA in Indian River Bay, Delaware, in April 2010
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
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Esri Binary grid of the bathymetry of Indian River Bay, Delaware, generated from fathometer data acquired in April 2010 during U.S. Geological Survey Field Activity 2010-006-FA (IRB_BATHY, UTM, Zone 18, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Point shapefile of navigation and best depth values at ship positions during continuous resistivity profiling data collection in the Indian River Bay, Delaware, on April 13, 2010, on U.S. Geological Survey Field Activity 2010-006-FA (JD103GPS_BESTDEPTH.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Parsed HYPACK navigation from April 13, 2010 of U.S. Geological Survey Field Activity 2010-006-FA in Indian River Bay, Delaware (JD103HYPACK.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Point shapefile of navigation and best depth values at ship positions during continuous resistivity profiling data collection in the Indian River Bay, Delaware, on April 14, 2010, on U.S. Geological Survey Field Activity 2010-006-FA (JD104GPS_BESTDEPTH.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Parsed HYPACK navigation from April 14, 2010 of U.S. Geological Survey Field Activity 2010-006-FA in Indian River Bay, Delaware (JD104HYPACK.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Point shapefile of navigation and best depth values at ship positions during continuous resistivity profiling data collection in the Indian River Bay, Delaware, on April 15, 2010, on U.S. Geological Survey Field Activity 2010-006-FA (JD105GPS_BESTDEPTH.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Parsed HYPACK navigation from April 15, 2010 of U.S. Geological Survey Field Activity 2010-006-FA in Indian River Bay, Delaware (JD105HYPACK.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Point shapefile of processed continuous resistivity profiling data below the sediment water interface collected in the Indian River Bay, Delaware, on April 13, 2010, on U.S. Geological Survey Field Activity 2010-006-FA (MRGAPR13_ALLXYZRES.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Point shapefile of processed continuous resistivity profiling data below the sediment water interface collected in the Indian River Bay, Delaware, on April 14, 2010, on U.S. Geological Survey Field Activity 2010-006-FA (MRGAPR14_ALLXYZRES.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Point shapefile of processed continuous resistivity profiling data below the sediment water interface collected in the Indian River Bay, Delaware, on April 15, 2010, on U.S. Geological Survey Field Activity 2010-006-FA (MRGAPR15_ALLXYZRES.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Point shapefile of continuous resistivity profiling data below the sediment water interface processed with a varying water conductivity value from Indian River Bay, Delaware, on U.S. Geological Survey Field Activity 2010-006-FA in April 2010 (MRGWCON_ALLXYZRES.SHP, Geographic, WGS 84)
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Continuous resistivity profiling data processed with multiple water conductivity values from Indian River Bay, Delaware, during April 2010 on U.S. Geological Survey Field Activity 2010-006-FA
A geophysical survey to delineate the fresh-saline groundwater interface and associated sub-bottom sedimentary structures beneath Indian River Bay, Delaware, was carried out in April 2010. This included surveying at higher spatial resolution in the vicinity of a study site at Holts Landing, where intensive onshore and offshore studies were subsequently completed. The total length of continuous resistivity profiling (CRP) survey lines was 145 kilometers (km), with 36 km of chirp seismic lines surveyed around ... |
Info |
Processed continuous resistivity profile (CRP) data below the sediment water interface from Great South Bay on Long Island, New York, collected by the U.S. Geological Survey from May 19 to May 22, 2008 (ALLGSB_RESBSED_MAY08.SHP)
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
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Processed continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 19, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Raw continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 19, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
RES2DINV format continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 19, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Processed continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 20, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Raw continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 20, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
RES2DINV format continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 20, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Processed continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 21, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Raw continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 21, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
RES2DINV format continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 21, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Processed continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 22, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Raw continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 22, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
RES2DINV format continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on May 22, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Processed continuous resistivity profile (CRP) data below the sediment water interface from Great South Bay on Long Island, New York, collected by the U.S. Geological Survey from Sept. 22 to Sept. 25, 2008 (ALLGSB_RESBSED_SEPT08.SHP)
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Processed continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 22, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Raw and modified raw continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 22, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
RES2DINV format continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 22, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Processed continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 23, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Raw and modified raw continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 23, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
RES2DINV format continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 23, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Processed continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 24, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Raw and modified raw continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 24, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
RES2DINV format continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 24, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Processed continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 25, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Raw and modified raw continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 25, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
RES2DINV format continuous resistivity profile data collected by the U.S. Geological Survey in Great South Bay on Long Island, New York, on Sept. 25, 2008
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Navigation, bathymetry, and water temperature points of ship position during continuous resistivity profile data collection by the U.S. Geological Survey in Great South Bay on Long Island, New York, in May and September 2008 (RESGPSPNTS_GSBAY.SHP)
An investigation of submarine aquifers adjacent to the Fire Island National Seashore and Long Island, New York, was conducted to assess the importance of submarine groundwater discharge (SGD) as a potential nonpoint source of nitrogen delivery to Great South Bay. More than 200 kilometers (km) of continuous resistivity profiling (CRP) data were collected to image the fresh-saline groundwater interface in sediments beneath the bay. In addition, groundwater sampling was performed at sites (1) along the ... |
Info |
Processed continuous resistivity profile data collected in Northport Harbor on Long Island, New York on May 12, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
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Raw and modified raw continuous resistivity profile data collected in Northport Harbor on Long Island, New York on May 12, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
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Processed continuous resistivity profile data collected in Northport Harbor on Long Island, New York on May 13, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
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Raw and modified raw continuous resistivity profile data collected in Northport Harbor on Long Island, New York on May 13, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
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Processed continuous resistivity profile data collected in Northport Harbor on Long Island, New York on May 14, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
Raw and modified raw continuous resistivity profile data collected in Northport Harbor on Long Island, New York on May 14, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
Processed continuous resistivity profile data collected in Manhasset Bay on Long Island, New York on May 15, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
Raw and modified raw continuous resistivity profile data collected in Manhasset Bay on Long Island, New York on May 15, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
RES2DINV format continuous resistivity profile data collected in Manhasset Bay on Long Island, New York on May 15, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
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Processed continuous resistivity profile data collected in Manhasset Bay on Long Island, New York on May 16, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
Raw and modified raw continuous resistivity profile data collected in Manhasset Bay on Long Island, New York on May 16, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
Processed continuous resistivity profile data collected in Manhasset Bay on Long Island, New York on May 17, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
Raw and modified raw continuous resistivity profile data collected in Manhasset Bay on Long Island, New York on May 17, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
RES2DINV format continuous resistivity profile data collected in Manhasset Bay on Long Island, New York on May 17, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
Navigation, bathymetry, and water temperature points of ship position during continuous resistivity profile data collection in Manhasset Bay on Long Island, New York in May, 2008 (RESGPSPNTS_MANHASSET.SHP)
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
Info |
Navigation, bathymetry, and water temperature points of ship position during continuous resistivity profile data collection in Northport Harbor on Long Island, New York in May, 2008 (RESGPSPNTS_NORTHPORT.SHP)
An investigation of coastal groundwater systems was performed along the North Shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
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Interpolated swath bathymetry collected by the U.S. Geological Survey - Woods Hole Coastal and Marine Science Center surrounding the nearshore of the Elizabeth Islands, MA, 2010 (ei_2hm_fill, ESRI grd)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Interpolated swath bathymetry hillshaded image collected by the U.S. Geological Survey - Woods Hole Coastal and Marine Science Center surrounding the nearshore of the Elizabeth Islands, MA, 2010 (ei_2hm_fillhs.tif, GeoTIFF)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Uninterpolated swath bathymetry collected by the U.S. Geological Survey - Woods Hole Coastal and Marine Science Center surrounding the nearshore of the Elizabeth Islands, MA, 2010 (ei_2hm_nofill, ESRI grd)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Interpolated swath bathymetry shaded relief image collected by the U.S. Geological Survey - Woods Hole Coastal and Marine Science Center surrounding the nearshore of the Elizabeth Islands, MA, 2010 (ei_2hm_shdrlf_image_dd.tif, GeoTIFF)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Interpolated swath bathymetry contours collected by the U.S. Geological Survey - Woods Hole Coastal and Marine Science Center surrounding the nearshore of the Elizabeth Islands, MA, 2010 (ei_contours_1m_dd, ESRI polyline shapefile)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Text files of the navigation logged with HYPACK Software during survey 2009-002-FA conducted in Buzzards Bay and Vineyard Sound by the U.S. Geological Survey offshore of Massachusetts in 2009.
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish habitat ... |
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Text files of the navigation logged with HYPACK Software during survey 2010-004-FA conducted in Buzzards Bay and Vineyard Sound by the U.S. Geological Survey offshore of Massachusetts in 2010.
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish habitat ... |
Info |
Text files of the navigation logged with HYPACK Software during survey 2011-004-FA conducted in Buzzards Bay and Vineyard Sound by the U.S. Geological Survey offshore of Massachusetts in 2011.
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish habitat ... |
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Depth contours derived from swath bathymetry data collected in Buzzards Bay by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts in 2004, 2009, 2010, and 2011 (BB_5mCntr Esri Polyline Shapefile, Geographic, WGS84).
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish habitat ... |
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5 meter ArcRaster grid of bathymetry data collected in Buzzards Bay by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts in 2004, 2009, 2010, and 2011 (BB_bathy5m, UTM Zone 19N, Esri BINARY GRID)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish habitat ... |
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5 meter ArcRaster grid of hillshaded bathymetry data collected in Buzzards Bay by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts in 2004, 2009, 2010, and 2011 (BB_hlshd5m, UTM Zone 19N, Esri BINARY GRID)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish habitat ... |
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ESRI Binary 75-m Grid of the Sea floor of Apalachicola Bay Excluding Manmade features based on Swath Bathymetry and Seismic-Reflection Profiles Collected in 2006 from U.S. Geological Survey Cruise 06001 (APALACH_SF, UTM, Zone 16, WGS84)
Apalachicola Bay and St. George Sound contain the largest oyster fishery in Florida, and the growth and distribution of the numerous oyster reefs here are the combined product of modern estuarine conditions and the late Holocene evolution of the bay. A suite of geophysical data and cores were collected during a cooperative study by the U.S. Geological Survey, the National Oceanic and Atmospheric Administration Coastal Services Center, and the Apalachicola National Estuarine Research Reserve to refine the ... |
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Point Shapefile of Interpreted Base of Mud Isopach Based on Seismic-Reflection Profiles Collected in Apalachicola Bay in 2006 from U.S. Geological Survey Cruise 06001 (BASEMUD_GEOG.SHP, Geographic, WGS84)
Apalachicola Bay and St. George Sound contain the largest oyster fishery in Florida, and the growth and distribution of the numerous oyster reefs here are the combined product of modern estuarine conditions and the late Holocene evolution of the bay. A suite of geophysical data and cores were collected during a cooperative study by the U.S. Geological Survey, the National Oceanic and Atmospheric Administration Coastal Services Center, and the Apalachicola National Estuarine Research Reserve to refine the ... |
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ESRI Binary 75-m Grid of the Base of the Mud Isopach of Apalachicola Bay based on Seismic-Reflection Profiles Collected in 2006 from U.S. Geological Survey Cruise 06001 (BASEMUDISO, UTM, Zone 16, WGS84)
Apalachicola Bay and St. George Sound contain the largest oyster fishery in Florida, and the growth and distribution of the numerous oyster reefs here are the combined product of modern estuarine conditions and the late Holocene evolution of the bay. A suite of geophysical data and cores were collected during a cooperative study by the U.S. Geological Survey, the National Oceanic and Atmospheric Administration Coastal Services Center, and the Apalachicola National Estuarine Research Reserve to refine the ... |
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ESRI Binary 75-m Grid of the Base of the Mud Depth Surface of Apalachicola Bay based on Seismic-Reflection Profiles Collected in 2006 from U.S. Geological Survey Cruise 06001 (BASEMUD_SURF, UTM, Zone 16, WGS84)
Apalachicola Bay and St. George Sound contain the largest oyster fishery in Florida, and the growth and distribution of the numerous oyster reefs here are the combined product of modern estuarine conditions and the late Holocene evolution of the bay. A suite of geophysical data and cores were collected during a cooperative study by the U.S. Geological Survey, the National Oceanic and Atmospheric Administration Coastal Services Center, and the Apalachicola National Estuarine Research Reserve to refine the ... |
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Point Shapefile of the Interpreted Flooding Surface Isopach Based on Seismic-Reflection Profiles Collected in Apalachicola Bay in 2006 from U.S. Geological Survey Cruise 06001 (FLOODISO_GEOG.SHP, Geographic, WGS84)
Apalachicola Bay and St. George Sound contain the largest oyster fishery in Florida, and the growth and distribution of the numerous oyster reefs here are the combined product of modern estuarine conditions and the late Holocene evolution of the bay. A suite of geophysical data and cores were collected during a cooperative study by the U.S. Geological Survey, the National Oceanic and Atmospheric Administration Coastal Services Center, and the Apalachicola National Estuarine Research Reserve to refine the ... |
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ESRI Binary 75-m Grid of the Flooding Surface in Apalachicola Bay based on Seismic-Reflection Profiles Collected in 2006 from U.S. Geological Survey Cruise 06001 (FLOODSURF, UTM, Zone 16, WGS84)
Apalachicola Bay and St. George Sound contain the largest oyster fishery in Florida, and the growth and distribution of the numerous oyster reefs here are the combined product of modern estuarine conditions and the late Holocene evolution of the bay. A suite of geophysical data and cores were collected during a cooperative study by the U.S. Geological Survey, the National Oceanic and Atmospheric Administration Coastal Services Center, and the Apalachicola National Estuarine Research Reserve to refine the ... |
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ESRI Binary 75-m Grid of the Lowstand Surface in Apalachicola Bay based on Seismic-Reflection Profiles Collected in 2006 from U.S. Geological Survey Cruise 06001 (LOWFILCLIP, UTM, Zone 16, WGS84)
Apalachicola Bay and St. George Sound contain the largest oyster fishery in Florida, and the growth and distribution of the numerous oyster reefs here are the combined product of modern estuarine conditions and the late Holocene evolution of the bay. A suite of geophysical data and cores were collected during a cooperative study by the U.S. Geological Survey, the National Oceanic and Atmospheric Administration Coastal Services Center, and the Apalachicola National Estuarine Research Reserve to refine the ... |
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Point Shapefile of Interpreted Lowstand Horizon Based on Seismic-Reflection Profiles Collected in Apalachicola Bay in 2006 from U.S. Geological Survey Cruise 06001 (LOWSTAND_GEOG.SHP, Geographic, WGS84)
Apalachicola Bay and St. George Sound contain the largest oyster fishery in Florida, and the growth and distribution of the numerous oyster reefs here are the combined product of modern estuarine conditions and the late Holocene evolution of the bay. A suite of geophysical data and cores were collected during a cooperative study by the U.S. Geological Survey, the National Oceanic and Atmospheric Administration Coastal Services Center, and the Apalachicola National Estuarine Research Reserve to refine the ... |
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Point Shapefile of the Interpreted Seafloor Horizon Based on Seismic-Reflection Profiles Collected in Apalachicola Bay in 2006 from U.S. Geological Survey Cruise 06001 (SEAFLOOR_GEOG.SHP, Geographic, WGS84)
Apalachicola Bay and St. George Sound contain the largest oyster fishery in Florida, and the growth and distribution of the numerous oyster reefs here are the combined product of modern estuarine conditions and the late Holocene evolution of the bay. A suite of geophysical data and cores were collected during a cooperative study by the U.S. Geological Survey, the National Oceanic and Atmospheric Administration Coastal Services Center, and the Apalachicola National Estuarine Research Reserve to refine the ... |
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Bathymetric depth contours at 5 meter intervals derived from interferometric sonar data collected offshore of Massachusetts within Vineyard Sound by the U.S. Geological Survey in 2009, 2010, and 2011 (VS_5MCNTR_V2, Esri Shapefile, Geographic, WGS84).
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, ... |
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Revised 5 meter ArcRaster grid of bathymetry acquired using a SEA Ltd. SWATHplus-M interferometric sonar offshore of Massachusetts within Vineyard Sound by the U.S. Geological Survey in 2009, 2010, and 2011 (VS_BATH5M_V2, Esri BINARY GRID, UTM 19N, WGS84).
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, ... |
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30-m Hillshaded relief image produced from swath interferometric, multibeam, and lidar datasets (navd_bath_30m.tif GeoTIFF Image; UTM, Zone 19N, WGS 84)
These data are qualitatively derived interpretive polygon shapefiles and selected source raster data defining surficial geology, sediment type and distribution, and physiographic zones of the sea floor from Nahant to Northern Cape Cod Bay. Much of the geophysical data used to create the interpretive layers were collected under a cooperative agreement among the Massachusetts Office of Coastal Zone Management (CZM), the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, the National Oceanic ... |
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30-m Topography and bathymetry grid produced from swath interferometric, multibeam, and lidar datasets (navd_bath_30m Esri binary grid, UTM Zone 19N, WGS84)
These data are qualitatively derived interpretive polygon shapefiles and selected source raster data defining surficial geology, sediment type and distribution, and physiographic zones of the sea floor from Nahant to Northern Cape Cod Bay. Much of the geophysical data used to create the interpretive layers were collected under a cooperative agreement among the Massachusetts Office of Coastal Zone Management (CZM), the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, the National Oceanic ... |
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Raw HYPACK navigation logs (text) collected by the U.S. Geological Survey from Muskeget Channel, MA, 2010 (2010-072-FA_hypack)
These data were collected in a collaboration between the Woods Hole Oceanographic Institution and the U.S. Geological Survey (USGS). The primary objective of this program was to collect baseline bathymetry for Muskeget Channel, Massachusetts, and identify areas of morphologic change within and around the channel. Repeat surveys in select areas were collected one month apart to monitor change. These data were collected to support an assessment of the effect on sediment transport that a tidal instream energy ... |
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Swath bathymetry gridded data (survey 1) collected by the U.S. Geological Survey surrounding Muskeget Channel, MA, October 2010 (Esri grid, UTM Zone 19N, WGS 84, 2-m resolution, survey1_2m)
These data were collected in a collaboration between the Woods Hole Oceanographic Institution and the U.S. Geological Survey (USGS). The primary objective of this program was to collect baseline bathymetry for Muskeget Channel, Massachusetts, and identify areas of morphologic change within and around the channel. Repeat surveys in select areas were collected one month apart to monitor change. These data were collected to support an assessment of the effect on sediment transport that a tidal instream energy ... |
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Swath bathymetry gridded data (survey 2) collected by the U.S. Geological Survey surrounding Muskeget Channel, MA, November 2010 (Esri grid, UTM Zone 19N, WGS 84, 2-m resolution, survey2_2m)
These data were collected in a collaboration between the Woods Hole Oceanographic Institution and the U.S. Geological Survey (USGS). The primary objective of this program was to collect baseline bathymetry for Muskeget Channel, Massachusetts, and identify areas of morphologic change within and around the channel. Repeat surveys in select areas were collected one month apart to monitor change. These data were collected to support an assessment of the effect on sediment transport that a tidal instream energy ... |
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Bathymetric Terrain Model of the U.S. Atlantic Margin (100-meter resolution) compiled by the U.S. Geological Survey (32-bit GeoTIFF, MERCATOR Projection, WGS 84)
Bathymetric terrain models of seafloor morphology are an important component of marine geological investigations. Advances in acquisition and processing technologies of bathymetric data have facilitated the creation of high-resolution bathymetric surfaces that approach the resolution of similar surfaces available for onshore investigations. These bathymetric terrain models provide a detailed representation of the Earth's subaqueous surface and, when combined with other geophysical and geological datasets, ... |
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Raw HYPACK navigation logs (text) collected by the U.S. Geological Survey from Middle Ground, MA, 2007 (2007-039-FA_hypack)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Raw HYPACK navigation logs (text) collected by the U.S. Geological Survey from Middle Ground, MA, September 22, 2009 (2009-068-FA_hypack)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Raw HYPACK navigation logs (text) collected by the U.S. Geological Survey in Vineyard Sound and Buzzards Bay, MA, July 2010 (2010-047-FA_hypack)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Raw HYPACK navigation logs (text) collected by the U.S. Geological Survey in Vineyard Sound, MA, January 5, 2011 (2010-100-FA_hypack)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Raw HYPACK navigation logs (text) collected by the U.S. Geological Survey from sand shoals of Vineyard Sound and the eastern Elizabeth Islands, MA, August 2011 (2011-013-FA_hypack)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Interpolated swath bathymetry contours collected by the U.S. Geological Survey surrounding the nearshore of the Elizabeth Islands and sand shoals of Vineyard Sound, MA, 2007-2011 (Esri polyline shapefile, Geographic, WGS 84, All_contour5m.shp)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Composite swath bathymetry gridded data collected by the U.S. Geological Survey surrounding the eastern Elizabeth Islands and northern Martha's Vineyard, MA, 2011 (Esri grid, UTM Zone19 N, WGS 84, 5-m resolution, allswathi_5m)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Swath bathymetry gridded data collected by the U.S. Geological Survey surrounding the eastern Elizabeth Islands and northern Martha's Vineyard, MA, 2011 (Esri grid, UTM Zone 19N, WGS 84, 2-m resolution, fa2011013_2m)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Swath bathymetry gridded data collected by the U.S. Geological Survey on Middle Ground Shoal, Massachusetts, 2007-2009 (Esri grid, UTM Zone 19N, WGS 84, 2-m resolution, mg-2m)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ... |
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Bathymetric Terrain Model of the Puerto Rico Trench and Northeastern Caribbean Region Compiled by the U.S. Geological Survey From Multibeam Bathymetric Data Collected Between 2002 and 2013 (PRBATHOFR150, Esri Binary Grid, UTM19, WGS 84).
Bathymetric terrain models (BTMs) of seafloor morphology are an important component of marine geological investigations. Advances in technologies of acquiring and processing bathymetric data have facilitated the creation of high-resolution bathymetric surfaces that approach the resolution of those available for onshore investigations. These bathymetric terrain models provide a detailed representation of the Earth's subaqueous surface and when combined with other geophysical and geologic datasets, allow for ... |
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10-meter swath bathymetric grid collected by the U.S. Geological Survey offshore of Fire Island, NY in 2011 (UTM Zone 18N, WGS 84, Esri Binary Grid, FI_BATHYGRD)
The U.S. Geological Survey (USGS) mapped approximately 336 square kilometers of the lower shoreface and inner-continental shelf offshore of Fire Island, New York in 2011 using interferometric sonar and high-resolution chirp seismic-reflection systems. This report presents maps of bathymetry, acoustic backscatter, the coastal plain unconformity, the Holocene marine transgressive surface and modern sediment thickness. These spatial data support research on the Quaternary evolution of the Fire Island ... |
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10-m Bathymetry grid produced from lead-line and single-beam sonar soundings, swath interferometric, multibeam, and lidar datasets (bb_navd88_10m, Esri binary grid, UTM Zone 19N, WGS84)
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Buzzards Bay, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a result of a collaborative ... |
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NOS_5m_INT_HS.tif: 5-meter hillshaded-relief image produced from 23 multibeam hydrographic surveys collected off the Delmarva Peninsula by the National Oceanic and Atmospheric Administration's National Ocean Service between 2006 and 2011 (GeoTIFF, UTM Zone 18N, WGS 84)
Between 2006 and 2011 Science Applications International Corporation (SAIC), under contract by the National Oceanic and Atmospheric Administration's (NOAA) National Ocean Service (NOS), collected twenty-three hydrographic surveys totaling over 4100 square-kilometers of Reson multibeam bathymetric and Klein sidescan-sonar data for the purposes of updating nautical charts. Data extended from the entrance of Delaware Bay south to Parramore Island in water depths from about 3 to 35 meters below mean lower low ... |
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nos_5mint: 5-meter bathymetry grid produced from 23 multibeam hydrographic surveys collected off the Delmarva Peninsula by the National Oceanic and Atmospheric Administration's National Ocean Service between 2006 and 2011 (Esri binary grid, UTM Zone 18N, WGS 84)
Between 2006 and 2011 Science Applications International Corporation (SAIC), under contract by the National Oceanic and Atmospheric Administration's (NOAA) National Ocean Service (NOS), collected twenty-three hydrographic surveys totaling over 4100 square-kilometers of Reson multibeam bathymetric and Klein sidescan-sonar data for the purposes of updating nautical charts. Data extended from the entrance of Delaware Bay south to Parramore Island in water depths from about 3 to 35 meters below mean lower low ... |
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10-m Hillshaded-relief image of Vineyard and western Nantucket Sounds produced from lead-line and single-beam sonar soundings, swath-interferometric, multibeam, and lidar datasets (TIFF image, UTM Zone 19N, WGS84)
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and Western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a ... |
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10-m Bathymetry grid of Vineyard and western Nantucket Sounds produced from lead-line and single-beam sonar soundings, swath-interferometric, multibeam, and lidar datasets (Esri binary grid, UTM Zone 19N, WGS84)
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a ... |
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Hillshaded-relief image produced from the late Wisconsinan to early Holocene regressive unconformity (Ur) beneath Vineyard and western Nantucket Sounds, Massachusetts (GeoTIFF Image; UTM, Zone 19N, WGS 84)
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a ... |
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5-meter bathymetric data collected in 2013 by the U.S. Geological Survey south of Martha's Vineyard and north of Nantucket, Massachusetts (32-bit floating-point bathymetry GeoTIFF and depth-colored hillshaded GeoTIFF, UTM Zone 19N, WGS 84)
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea floor geology are important first steps toward protecting fish ... |
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Text files of the navigation logged with HYPACK Software during field activity 2013-003-FA in 2013 by the U.S. Geological Survey south of Martha's Vineyard and north of Nantucket, Massachusetts
These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea floor geology are important first steps toward protecting fish ... |
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Swath bathymetry 13-m-cell-size grid of quadrangle 6 on Stellwagen Bank offshore of Boston, Massachusetts collected by the U.S. Geological Survey aboard the Frederick G. Creed from 1994-1996 (custom Mercator projection, NAD 83, Esri binary grid format)
The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration's National Marine Sanctuary Program, has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary region since 1993. The area is approximately 3,700 square kilometers (km2) and is subdivided into 18 quadrangles. Seven maps, at a scale of 1:25,000, of quadrangle 6 (211 km2) depict seabed topography, backscatter, ruggedness, geology, substrate mobility, mud content, ... |
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Polyline shapefile of a portion of the 1-meter (m) contours in quadrangle 6 of the Stellwagen Bank Survey Area offshore of Boston, Massachusetts necessary to show small features not displayed by 5-m contours - based on bathymetry data collected by the U.S. Geological Survey from 1994-1996 (Geographic, NAD 83)
The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration's National Marine Sanctuary Program, has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary region since 1993. The area is approximately 3,700 square kilometers (km2) and is subdivided into 18 quadrangles. Seven maps, at a scale of 1:25,000, of quadrangle 6 (211 km2) depict seabed topography, backscatter, ruggedness, geology, substrate mobility, mud content, ... |
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2005 USGS Post-Hurricane Rita Texas and Louisiana Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 USGS Post-Hurricane ... |
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Bathymetry data for Ozette Lake, Washington collected during USGS field activity 2019-622-FA
Bathymetry data were collected during a July 2019 SWATHPlus survey of Ozette Lake, Washington. Data were collected and processed by the the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity number 2019-622-FA. The 2-m bathymetry data are provided as a GeoTIFF image. |
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Bathymetric data and grid of offshore Head of the Meadow Beach, Truro, MA on February 9, 2024
The data in this release re-map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide updated environmental context for the 2020 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-01, which are two video cameras aimed at the beach. In February and March 2024, U.S. ... |
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Ground control points Head of the Meadow Beach, Truro, MA on March 20, 2024
The data in this release re-map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide updated environmental context for the 2020 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-01, which are two video cameras aimed at the beach. In February and March 2024, U.S. ... |
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Low-altitude aerial imagery collected from a Helikite at Head of the Meadow Beach, Truro, MA on March 20, 2024
The data in this release re-map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide updated environmental context for the 2020 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-01, which are two video cameras aimed at the beach. In February and March 2024, U.S. ... |
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SfM digital surface model and orthomosaic representing Head of the Meadow Beach, Truro, MA on March 20, 2024
The data in this release re-map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide updated environmental context for the 2020 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-01, which are two video cameras aimed at the beach. In February and March 2024, U.S. ... |
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Buzzards Bay: continuous bathymetry and topography terrain model of the Massachusetts coastal zone and continental shelf, (32-bit GeoTIFF, UTM 19 NAD 83, NAVD 88 vertical datum).
Integrated terrain models covering 16,357 square kilometers of the Massachusetts coastal zone and offshore waters were built to provide a continuous elevation and bathymetry terrain model for ocean planning purposes. The area is divided into the following four geographical areas to reduce file size and facilitate publishing: Massachusetts Bay from the Massachusetts-New Hampshire border south to Provincetown and Scituate and east to Stellwagen Bank; Cape Cod Bay from Provincetown to Scituate and south to ... |
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Cape Cod Bay: continuous bathymetry and topography terrain model of the Massachusetts coastal zone and continental shelf, (32-bit GeoTIFF, UTM 19 NAD 83, NAVD 88 vertical datum).
Integrated terrain models covering 16,357 square kilometers of the Massachusetts coastal zone and offshore waters were built to provide a continuous elevation and bathymetry terrain model for ocean planning purposes. The area is divided into the following four geographical areas to reduce file size and facilitate publishing: Massachusetts Bay from the Massachusetts-New Hampshire border south to Provincetown and Scituate and east to Stellwagen Bank; Cape Cod Bay from Provincetown to Scituate and south to ... |
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Massachusetts Bay and adjacent land: continuous bathymetry and topography terrain model of the Massachusetts coastal zone and continental shelf, (32-bit GeoTIFF, UTM 19 NAD 83, NAVD 88 vertical datum).
Integrated terrain models covering 16,357 square kilometers of the Massachusetts coastal zone and offshore waters were built to provide a continuous elevation and bathymetry terrain model for ocean planning purposes. The area is divided into the following four geographical areas to reduce file size and facilitate publishing: Massachusetts Bay from the Massachusetts-New Hampshire border south to Provincetown and Scituate and east to Stellwagen Bank; Cape Cod Bay from Provincetown to Scituate and south to ... |
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Vineyard and Nantucket Sounds, southern coast of Cape Cod including Martha's Vineyard and Nantucket: continuous bathymetry and topography terrain model of the Massachusetts coastal zone and continental shelf, (32-bit GeoTIFF, UTM 19 NAD 83, NAVD 88 vertical datum).
Integrated terrain models covering 16,357 square kilometers of the Massachusetts coastal zone and offshore waters were built to provide a continuous elevation and bathymetry terrain model for ocean planning purposes. The area is divided into the following four geographical areas to reduce file size and facilitate publishing: Massachusetts Bay from the Massachusetts-New Hampshire border south to Provincetown and Scituate and east to Stellwagen Bank; Cape Cod Bay from Provincetown to Scituate and south to ... |
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Marsh Shorelines of the Massachusetts Coast from 2013-14 Topographic Lidar Data
The Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the Massachusetts coast. Seventy-six maps were produced in 1997 depicting a statistical analysis of shoreline change on ocean-facing shorelines from the mid-1800s to 1978 using multiple data sources. In 2001, a 1994 shoreline was added. More recently, in cooperation with CZM, the U.S. Geological Survey (USGS) delineated a new shoreline for Massachusetts using color ... |
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Bathymetry of the Historic Area Remediation Site in 1996 (3-m resolution Esri binary grid and 32-bit GeoTIFF, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ... |
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GeoTIFF image of the shaded-relief bathymetry of the Historic Area Remediation Site in 1996 (3-m resolution, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ... |
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Bathymetry of the Historic Area Remediation Site in 1998 (3-m resolution Esri binary grid and 32-bit GeoTIFF, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ... |
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GeoTIFF image of the shaded-relief bathymetry of the Historic Area Remediation Site in 1998 (3-m resolution, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ... |
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Bathymetry of the Historic Area Remediation Site in 2000 (3-m resolution Esri binary grid and 32-bit GeoTIFF, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ... |
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GeoTIFF image of the shaded-relief bathymetry of the Historic Area Remediation Site in 2000 (3-m resolution, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ... |
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Bathymetry of the Sandy Hook artificial reef (2-m resolution Esri binary grid and 32-bit GeoTIFF, Mercator, WGS 84)
The Sandy Hook artificial reef, located on the sea floor offshore of Sandy Hook, New Jersey was built to create habitat for marine life. The reef was created by the placement of heavy materials on the sea floor; ninety-five percent of the material in the Sandy Hook reef is rock. In 2000, the U.S. Geological Survey surveyed the area using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard (CCG) ship Frederick G. Creed. The purpose of this multibeam survey, done in cooperation with the ... |
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Ground control point and transect locations associated with images collected during unmanned aerial systems (UAS) flights over The Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ... |
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Braddock East camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ... |
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Braddock East point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (LAZ file).
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ... |
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Braddock West camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ... |
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Braddock West point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (LAZ file).
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ... |
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Bathymetry of the Hudson Canyon region (100-m resolution Esri binary grid and 32-bit GeoTIFF, Mercator, WGS 84)
The Hudson Canyon begins on the outer continental shelf off the east coast of the United States at about 100-meters (m) water depth and extends offshore southeastward across the continental slope and rise. A multibeam survey was carried out in 2002 to map the bathymetry and backscatter intensity of the sea floor of the Hudson Canyon and adjacent slope and rise. The survey covered an area approximately 205 kilometers (km) in the offshore direction, extending from about 500 m to about 4,000 m water depth, and ... |
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GeoTIFF image of shaded-relief bathymetry, illuminated from 315 degrees, of the sea floor of the Hudson Canyon region (100-m resolution, Mercator, WGS 84)
The Hudson Canyon begins on the outer continental shelf off the east coast of the United States at about 100-meters (m) water depth and extends offshore southeastward across the continental slope and rise. A multibeam survey was carried out in 2002 to map the bathymetry and backscatter intensity of the sea floor of the Hudson Canyon and adjacent slope and rise. The survey covered an area approximately 205 kilometers (km) in the offshore direction, extending from about 500 m to about 4,000 m water depth, and ... |
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GeoTIFF image of shaded-relief bathymetry, illuminated from 45 degrees, of the sea floor of the Hudson Canyon region (100-m resolution, Mercator, WGS 84)
The Hudson Canyon begins on the outer continental shelf off the east coast of the United States at about 100-meters (m) water depth and extends offshore southeastward across the continental slope and rise. A multibeam survey was carried out in 2002 to map the bathymetry and backscatter intensity of the sea floor of the Hudson Canyon and adjacent slope and rise. The survey covered an area approximately 205 kilometers (km) in the offshore direction, extending from about 500 m to about 4,000 m water depth, and ... |
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Collection, Analysis, and Age-Dating of Sediment Cores from Salt Marshes on the South Shore of Cape Cod, Massachusetts, From 2013 Through 2014
The accretion history of fringing microtidal salt marshes located on the south shore of Cape Cod, Massachusetts, was reconstructed from sediment cores collected in low and high marsh vegetation zones. The location of these marshes within protected embayments and the absence of large rivers on Cape Cod result in minimal sediment supply and a dominance of organic matter contribution to sediment peat. Age models based on 210-lead and 137-cesium were constructed to evaluate how vertical accretion and carbon ... |
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Bathymetry of the Atlantic Beach artificial reef (2-m resolution Esri binary grid and 32-bit GeoTIFF, Mercator, WGS 84)
The Atlantic Beach artificial reef, located on the sea floor 3 nautical miles south of Atlantic Beach, New York in about 20 meters water depth, was built to create habitat for marine life. The reef was originally created by placing heavy materials such as tires, automobile bodies and other vehicles, barges, and rock from a dredging project on the sea floor. In 2000, the U.S. Geological Survey surveyed the area using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard (CCG) ship ... |
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Continuous terrain model for water circulation studies, Barnegat Bay, New Jersey (10 meter resolution, 32-bit GeoTIFF, UTM 18, WGS 84)
Water quality in the Barnegat Bay estuary along the New Jersey coast is the focus of a multidisciplinary research project begun in 2011 by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection. This narrow estuary is the drainage for the Barnegat Bay watershed and flushed by just three inlets connecting it to the Atlantic Ocean, is experiencing degraded water quality, algal blooms, loss of seagrass, and increases in oxygen-depletion events. The scale of ... |
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Multibeam Echosounder, Reson T-20P deep site bathymetry (4-m), USGS field activity 2017-003-FA, Mississippi River Delta front offshore of southeastern Louisiana (32-bit GeoTIFF, UTM Zone 16N, NAD 83, NAVD 88 Vertical Datum)
High resolution bathymetric, sea-floor backscatter, and seismic-reflection data were collected offshore of southeastern Louisiana aboard the research vessel Point Sur on May 19-26, 2017, in an effort to characterize mudflow hazards on the Mississippi River Delta front. As the initial field program of a research cooperative between the U.S. Geological Survey, the Bureau of Ocean Energy Management, and other Federal and academic partners, the primary objective of this cruise was to assess the suitability of ... |
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Multibeam Echosounder, Reson T-20P MC20 site bathymetry (2-m), USGS field activity 2017-003-FA, Mississippi River Delta front offshore of southeastern Louisiana (32-bit GeoTIFF, UTM Zone 16N, NAD 83, NAVD 88 Vertical Datum)
High resolution bathymetric, sea-floor backscatter, and seismic-reflection data were collected offshore of southeastern Louisiana aboard the research vessel Point Sur on May 19-26, 2017, in an effort to characterize mudflow hazards on the Mississippi River Delta front. As the initial field program of a research cooperative between the U.S. Geological Survey, the Bureau of Ocean Energy Management, and other Federal and academic partners, the primary objective of this cruise was to assess the suitability of ... |
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Multibeam Echosounder, Reson T-20P bathymetry overview (10-m), USGS field activity 2017-003-FA, Mississippi River Delta front offshore of southeastern Louisiana (32-bit GeoTIFF, UTM Zone 16N, NAD 83, NAVD 88 Vertical Datum)
High resolution bathymetric, sea-floor backscatter, and seismic-reflection data were collected offshore of southeastern Louisiana aboard the research vessel Point Sur on May 19-26, 2017, in an effort to characterize mudflow hazards on the Mississippi River Delta front. As the initial field program of a research cooperative between the U.S. Geological Survey, the Bureau of Ocean Energy Management, and other Federal and academic partners, the primary objective of this cruise was to assess the suitability of ... |
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Multibeam Echosounder, Reson T-20P Southwest Pass site bathymetry (8-m), USGS field activity 2017-003-FA, Mississippi River Delta front offshore of southeastern Louisiana (32-bit GeoTIFF, UTM Zone 16N, NAD 83, NAVD 88 Vertical Datum)
High resolution bathymetric, sea-floor backscatter, and seismic-reflection data were collected offshore of southeastern Louisiana aboard the research vessel Point Sur on May 19-26, 2017, in an effort to characterize mudflow hazards on the Mississippi River Delta front. As the initial field program of a research cooperative between the U.S. Geological Survey, the Bureau of Ocean Energy Management, and other Federal and academic partners, the primary objective of this cruise was to assess the suitability of ... |
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Grid of the sea-floor bathymetry offshore of Fire Island Inlet, New York, in 1998 (3-m resolution Esri binary grid, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ... |
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Grid of the sea-floor bathymetry southwest of Montauk Point, New York, in 1998 (3-m resolution Esri binary grid, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ... |
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Grid of the sea-floor bathymetry offshore of Moriches Inlet, New York, in 1998 (3-m resolution Esri binary grid, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ... |
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Grid of the sea-floor bathymetry offshore of Shinnecock Inlet, New York, in 1998 (3-m resolution Esri binary grid, Mercator, WGS 84)
Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ... |
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Multibeam bathymetric data collected within Lake Powell, UT-AZ during USGS Field Activity 2017-049-FA using a dual-head Reson T20-P multibeam echosounder (32-bit GeoTIFF, UTM Zone 12N, NAD 83, NAVD 88 Vertical Datum, 2-m resolution).
High-resolution geophysical mapping of Lake Powell in the Glen Canyon National Recreation Area in Utah and Arizona was conducted between October 8 and November 15, 2017, as part of a collaborative effort between the U.S. Geological Survey and the Bureau of Reclamation to provide high-quality data needed to reassess the area-capacity tables for the Lake Powell reservoir. Seismic data collected during this survey can help to define the rates of deposition within the San Juan and Colorado Rivers, which are the ... |
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Bathymetric data collected in the Belfast Bay, Maine pockmark field using a SWATHplus-M interferometric sonar in 2006 and 2008, by the U.S. Geological Survey (32-bit floating point raster, UTM 19 WGS 84, MLLW)
The U.S. Geological Survey, Woods Hole Coastal and Marine Science Center in cooperation with the University of Maine mapped approximately 50 square kilometers of the seafloor within Belfast Bay, Maine. Three geophysical surveys conducted in 2006, 2008 and 2009 collected swath bathymetric (2006 and 2008) and chirp seismic reflection profile data (2006 and 2009). The project characterized the spatial, morphological and subsurface variability of the Belfast Bay, Maine pockmark field. Pockmarks are large ... |
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Collection, analysis, and age-dating of sediment cores from Herring River wetlands and other nearby wetlands in Wellfleet, Massachusetts, 2015–17
The Herring River estuary in Wellfleet, Cape Cod, Massachusetts, has been tidally restricted for more than a century by a dike constructed near the mouth of the river. Upstream from the dike, the tidal restriction has caused the conversion of salt marsh wetlands to various other ecosystems including impounded freshwater marshes, flooded shrub land, drained forested upland, and brackish wetlands dominated by Phragmites australis. This estuary is now managed by the National Park Service, which plans to ... |
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2013-14 Massachusetts Lidar-Derived Dune Crest Point Data
This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ... |
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2013-14 Massachusetts Lidar-Derived Dune Toe Point Data
This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ... |
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Multibeam bathymetric data collected in the eastern Gulf of Alaska during USGS Field Activity 2016-625-FA using a Reson 7160 multibeam echosounder (10 meter resolution, 32-bit GeoTIFF, UTM 8 WGS 84, WGS 84 Ellipsoid)
Marine geophysical mapping of the Queen Charlotte Fault in the eastern Gulf of Alaska was conducted in 2016 as part of a collaborative effort between the U.S. Geological Survey and the Alaska Department of Fish and Game to understand the morphology and subsurface geology of the entire Queen Charlotte system. The Queen Charlotte fault is the offshore portion of the Queen Charlotte-Fairweather Fault: a major structural feature that extends more than 1,200 kilometers from the Fairweather Range of southern ... |
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Multibeam bathymetric data collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS Field Activity 2018-001-FA, using a dual-head Reson T20-P multibeam echo sounder (32-bit GeoTIFF, UTM Zone 18N, NAD 83, NAVD 88 Vertical Datum, 4-m resolution)
The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg ... |
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Mean High Water Shorelines for the Outer Cape of Massachusetts from Nauset Inlet to Race Point (1998-2005)
This data release contains mean high water (MHW) shorelines for the Outer Cape of Cape Cod, Massachusetts, from Nauset Inlet to Race Point. From 1998-2005, the U.S. Geological Survey surveyed 45 kilometers of coastline 111 times using a ground-based system called Surveying Wide-Area Shorelines (SWASH). The SWASH system used a six-wheeled amphibious all-terrain vehicle as a platform for an array of Global Positioning System sensors. High-accuracy measurements of horizontal position, vertical position, and ... |
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Multibeam backscatter data collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS Field Activity 2018-043-FA using a dual-head Reson T20-P multibeam echosounder (8-bit GeoTIFF, UTM Zone 16N, NAD 83, 2-m resolution)
In September 2018, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, conducted high-resolution geophysical mapping and sediment sampling to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of the town ... |
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Multibeam bathymetric data collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS Field Activity 2018-043-FA using a dual-head Reson T20-P multibeam echosounder (32-bit GeoTIFF, UTM Zone 16N, NAD 83, NAVD 88 Vertical Datum, 2-m resolution)
In September 2018, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, conducted high-resolution geophysical mapping and sediment sampling to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of the town ... |
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Multibeam bathymetric trackline data collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS Field Activity 2018-043-FA using a dual-head Reson T20-P multibeam echosounder (Esri polyline shapefile, Geographic, WGS 84).
In September 2018, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, conducted high-resolution geophysical mapping and sediment sampling to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of the town ... |
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Multibeam backscatter data collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS Field Activity 2021-005-FA using a dual-head Reson T20-P multibeam echosounder (8-bit GeoTIFF, UTM Zone 16N, NAD 83, 1-m resolution)
In August 2021, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, collected high-resolution geophysical data, sediment samples, and bottom imagery to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of ... |
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Multibeam bathymetric data collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS Field Activity 2021-005-FA using a dual-head Reson T20-P multibeam echosounder (32-bit GeoTIFF, UTM Zone 16N, NAD 83, NAVD 88 Vertical Datum, 1-m resolution)
In August 2021, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, collected high-resolution geophysical data, sediment samples, and bottom imagery to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of ... |
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Multibeam trackline data collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS Field Activity 2021-005-FA using a dual-head Reson T20-P multibeam echosounder (Esri polyline shapefile, Geographic, WGS 84)
In August 2021, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, collected high-resolution geophysical data, sediment samples, and bottom imagery to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of ... |
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Geotagged lakebed images and their locations collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS Field Activity 2021-005-FA using the USGS MiniSEABOSS (JPEG images, point shapefile; GCS WGS 84)
In August 2021, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, collected high-resolution geophysical data, sediment samples, and bottom imagery to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of ... |
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Geotagged images of sediment grabs collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS Field Activity 2021-005-FA using the USGS MiniSEABOSS (JPEG images; GCS WGS 84)
In August 2021, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, collected high-resolution geophysical data, sediment samples, and bottom imagery to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of ... |
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Locations and grain-size analysis results of sediment samples collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS Field Activity 2021-005-FA using the USGS MiniSEABOSS (CSV, GCS WGS 84)
In August 2021, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, collected high-resolution geophysical data, sediment samples, and bottom imagery to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of ... |
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Ground control and transect points collected during unmanned aerial systems (UAS) flights: Plum Island Estuary and Parker River NWR (PIEPR), February 27th, 2018
Low-altitude (80 and 100 meters above ground level) digital images were taken over an area of the Plum Island Estuary and Parker River National Wildlife Refuge (NWR) in Massachusetts using 3DR Solo unmanned aircraft systems (UAS) on February 27, 2018. These images were collected as part of an effort to document marsh stability over time and quantify sediment movement using UAS technology. Each UAS was equipped with either a Ricoh GRII digital camera for natural color photos, used to produce digital ... |
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Collection, analysis, and age-dating of sediment cores from mangrove and salt marsh ecosystems in Tampa Bay, Florida, 2015
Coastal wetlands in Tampa Bay, Florida, are important ecosystems that deliver a variety of ecosystem services. Key to ecosystem functioning is wetland response to sea-level rise through accumulation of mineral and organic sediment. The organic sediment within coastal wetlands is composed of carbon sequestered over the time scale of the wetland’s existence. This study was conducted to provide information on soil accretion and carbon storage rates across a variety of coastal ecosystems that was utilized in ... |
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Collection, analysis, and age-dating of sediment cores from natural and restored salt marshes on Cape Cod, Massachusetts, 2015-16
Nineteen sediment cores were collected from five salt marshes on the northern shore of Cape Cod where previously restricted tidal exchange was restored to part of the marshes. Cores were collected in duplicate from two locations within each marsh complex: one upstream and one downstream from the former tidal restriction (typically caused by an undersized culvert or a berm). The unaltered, natural downstream sites provide a comparison against the historically restricted upstream sites. The sampled cores ... |
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Chimney Bluffs camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Chimney Bluffs, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from ... |
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Ground control point and transect locations associated with images collected during unmanned aerial systems (UAS) flights over The Lake Ontario shoreline in the vicinity of Chimney Bluffs, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from ... |
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Chimney Bluffs point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Chimney Bluffs, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from ... |
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Lifespan of marsh units in Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia
The sediment-based lifespan of salt marsh units in Assateague Island National Seashore (ASIS) and Chincoteague Bay is shown for conceptual marsh units defined by Defne and Ganju (2018). The lifespan represents the timescale by which the current sediment mass within a marsh parcel can no longer compensate for sediment export and deficits induced by sea-level rise. The lifespan calculation is based on vegetated cover, marsh elevation, sediment supply, and sea-level rise (SLR) predictions after Ganju and ... |
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Charles Point camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Charles Point point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (LAZ file)
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Greig Street camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Greig Street point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (LAZ file)
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Lake Bluffs camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Lake Bluffs point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (LAZ file)
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Ground control point and transect locations associated with images collected during unmanned aerial systems (UAS) flights over The Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Sodus North camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Sodus North point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (LAZ file)
Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ... |
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Multibeam echo sounder - GeoTIFF images for processed Reson 7160 seafloor backscatter data collected during USGS field activities 2017-001-FA and 2017-002-FA.
In spring and summer 2017, the U.S. Geological Survey’s Gas Hydrates Project conducted two cruises aboard the research vessel Hugh R. Sharp to explore the geology, chemistry, ecology, physics, and oceanography of sea-floor methane seeps and water column gas plumes on the northern U.S. Atlantic margin between the Baltimore and Keller Canyons. Split-beam and multibeam echo sounders and a chirp subbottom profiler were deployed during the cruises to map water column backscatter, sea-floor bathymetry and ... |
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Multibeam echo sounder - GeoTIFF grids for processed Reson 7160 seafloor bathymetry data collected during USGS field activities 2017-001-FA and 2017-002-FA.
In spring and summer 2017, the U.S. Geological Survey’s Gas Hydrates Project conducted two cruises aboard the research vessel Hugh R. Sharp to explore the geology, chemistry, ecology, physics, and oceanography of sea-floor methane seeps and water column gas plumes on the northern U.S. Atlantic margin between the Baltimore and Keller Canyons. Split-beam and multibeam echo sounders and a chirp subbottom profiler were deployed during the cruises to map water column backscatter, sea-floor bathymetry and ... |
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A bathymetric terrain model of multibeam sonar data collected between 2005 and 2018 along the Queen Charlotte Fault System in the eastern Gulf of Alaska from Cross Sound, Alaska to Queen Charlotte Sound, Canada. (30-meter resolution, 32-bit GeoTIFF, UTM 8 WGS 84, WGS 84 Ellipsoid)
This data publication is a compilation of six different multibeam surveys covering the previously unmapped Queen Charlotte Fault offshore southeast Alaska and Haida Gwaii, Canada. These data were collected between 2005 and 2018 under a cooperative agreement between the U.S. Geological Survey, Natural Resources Canada, and the National Oceanic and Atmospheric Administration. The six source surveys from different multibeam sonars are combined into one terrain model with a 30-meter resolution. A complementary ... |
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Multibeam bathymetric data collected in Cape Cod Bay, Massachusetts during USGS Field Activity 2019-002-FA, using a dual-head Reson T20-P multibeam echo sounder (32-bit GeoTIFF, UTM Zone 19N, NAD 83, MLLW Vertical Datum, 5-m resolution)
Accurate data and maps of sea floor geology are important first steps toward protecting fish habitat, delineating marine resources, and assessing environmental changes due to natural or human impacts. To address these concerns the U.S. Geological Survey, in cooperation with the Massachusetts Office of Coastal Zone Management (CZM), comprehensively mapped the Cape Cod Bay sea floor to characterize the surface and shallow subsurface geologic framework. Geophysical data collected include swath bathymetry, ... |
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2-meter bathymetric data collected in 2016 by the U.S. Geological Survey off Town Neck Beach in Sandwich, Massachusetts, during field activity 2016-017-FA (GeoTIFF image)
Geophysical and geological survey data were collected off Town Neck Beach in Sandwich, Massachusetts, in May and July 2016. Approximately 130 linear kilometers of subbottom (seismic-reflection) and 234-kilohertz interferometric sonar (bathymetric and backscatter) data were collected along with sediment samples, sea floor photographs, and (or) video at 26 sites within the geophysical survey area. Sediment grab samples were collected at 19 of the 26 sampling sites and video and (or) photographic imagery of ... |
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Single-Beam Bathymetry Data Collected in 2022 from Point Aux Chenes Bay, Mississippi
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS – SPCSMC), conducted a single-beam bathymetry survey within Point Aux Chenes Bay, Mississippi (MS), in June 2022 under the USGS Field Activity Number (FAN) 2022-320-FA. The data was collected from two personal watercrafts (PWC): research vessel (R/V) Shark (subFAN 22CCT09, WVR1) and R/V Chum (subFAN 22CCT10, WVR2). A re-survey of just the north and south subtidal reefs occurred in November 2022 (subFANs ... |
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4-meter resolution bathymetric grid representing single beam data collected by the U.S. Geological Survey during field activity 2016-030-FA offshore Sandwich Beach, MA in June 2016 (32-bit GeoTIFF, UTM Zone 19N, NAD83-HARN)
The objectives of the survey were to provide bathymetric and sidescan sonar data for sediment transport studies and coastal change model development for ongoing studies of nearshore coastal dynamics along Sandwich Town Neck Beach, MA. Data collection equipment used for this investigation are mounted on an unmanned surface vehicle (USV) uniquely adapted from a commercially sold gas-powered kayak and termed the "jetyak". The jetyak design is the result of a collaborative effort between USGS and Woods Hole ... |
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RES2DINV format continuous resistivity profile data collected in Manhasset Bay on Long Island, New York on May 16, 2008
An investigation of coastal groundwater systems was performed along the north shore of Long Island, New York during May 2008 to constrain nutrient delivery to Northport Harbor and Manhasset Bay by delineating locations of likely groundwater discharge. The embayments are bounded by steep moraines and are underlain by thick fine-grained sediments deposited in proglacial lakes during the last ice age. Beach sand and gravel overlie the glacial deposits along the coast. The continuous resistivity profiling (CRP) ... |
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Bathymetric change of Central San Francisco Bay, California: 1971 to 2020
This 25-m-resolution surface presents bathymetric change of Central San Francisco Bay, California (hereafter referred to as Central Bay). This surface compares a 1-m-resolution digital elevation model (DEM) of the central portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the Central Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 25-m-resolution DEM of Central Bay comprised of historic surveys from ... |
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Bathymetric change of San Pablo Bay, California: 1983 to 2015
This 25-m-resolution surface presents bathymetric change of San Pablo Bay, California, from 1983 to 2015. This surface compares a 1-m-resolution digital elevation model (DEM) of the northern portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the San Pablo Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 25-m-resolution bathymetric DEM of San Pablo Bay comprised of historic surveys from 1983 to 1986 ... |
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Bathymetric change of South San Francisco Bay, California: 1979 to 2020
This 50-m-resolution surface presents bathymetric change of South San Francisco Bay, California (hereafter referred to as South Bay). This surface compares a 1-m-resolution digital elevation model (DEM) of the southern portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the South Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 50-m-resolution DEM of South Bay comprised of historic surveys from 1979 to ... |
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Bathymetric change of Suisun Bay, California: 1988 to 2016
This 25-m-resolution surface presents bathymetric change of Suisun Bay, California, from 1988 to 2016. This surface compares a 1-m-resolution digital elevation model (DEM) of the northern portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the Suisun region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 25-m-resolution bathymetric DEM of Suisun Bay comprised of historic surveys from 1988 to 1990 (referred to as ... |
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Lifespan of marsh units in Eastern Shore of Virginia salt marshes
The lifespans of salt marshes in Atlantic-facing Eastern Shore of Virginia are calculated based on estimated sediment supply and sea-level rise (SLR) predictions, following the methodology of Ganju and others (2020). The salt marsh delineations are from Ackerman and others (2023). The SLR predictions are local estimates corresponding to increases of 0.3, 0.5 and 1.0 meter in global mean sea level (GMSL) by 2100, as projected by Sweet and others (2022). This work has been a part of the USGS’s effort to ... |
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Bathymetric data and grid of offshore Marconi Beach, Wellfleet, MA on April 23, 2024
The data in this release re-map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide updated environmental context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2024-016-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of two video cameras aimed at the beach (CoastCam CACO-02). In ... |
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Structure from motion GCPs, digital surface model, and orthomosaic representing Marconi Beach, Wellfleet, MA on March 22, 2024
The data in this release re-map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide updated environmental context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2024-016-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of two video cameras aimed at the beach (CoastCam CACO-02). In ... |
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Lifespan of marsh units in Connecticut salt marshes
The lifespans of salt marshes in Connecticut are calculated based on estimated sediment supply and sea-level rise (SLR) predictions, following the methodology of Ganju and others (2020). The salt marsh delineations are from Ackerman and others (2023). The SLR predictions are local estimates corresponding to increases of 0.3, 0.5 and 1.0 meter in global mean sea level (GMSL) by 2100, as projected by Sweet and others (2022). This work has been a part of the USGS’s effort to expand the national assessment of ... |
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Gulf of Mexico Bathymetry Contours
This GIS overlay is a component of the U. S Geological Survey, Woods Hole Field Center's, Gulf of Mexico ArcView GIS database. The Gulf of Mexico GIS database is intended to organize and display USGS held data and provide on-line (WWW) access to the data and/or metadata. |
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Digital Surface Models (DSM) from UAS surveys of the upper reservoir delta at Jenkinson Lake, El Dorado County, California
This portion of the data release presents high-resolution Digital Surface Models (DSM) of the Jenkinson Lake upper reservoir delta in El Dorado County, California. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected during surveys with unoccupied aerial systems (UAS). The surveys were on 2021-10-13, 2021-11-04, 2022-10-25, and 2023-11-13, and were generally timed to coincide with low water level in the reservoir to ... |
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Orthomosaic images from UAS surveys of the upper reservoir delta at Jenkinson Lake, El Dorado County, California
This portion of the data release presents high-resolution orthomosaic images of the Jenkinson Lake upper reservoir delta in El Dorado County, California. The orthomosaics have resolutions of 2.5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected during surveys with unoccupied aerial systems (UAS). The surveys were on 2021-10-13, 2021-11-04, 2022-10-25, and 2023-11-13, and were generally timed to coincide with low water level in the reservoir to ... |
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2002 Post-Tropical Storm Fay University of Texas Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2002 University of Texas ... |
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2002 NOAA/NASA/USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2002 Post-Hurricane Lili ... |
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2003 Pre- and Post-Hurricane Isabel USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2003 Pre- and Post ... |
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2004 Post-Hurricane Charley West Florida EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Post-Hurricane ... |
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2005 Post-Hurricane Dennis Florida U.S. Army Corps of Engineers Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 USACE Post-Dennis ... |
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2005 Post-Hurricane Katrina EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Post-Hurricane ... |
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September 2006 Post-Hurricane Wilma Florida U.S. Army Corps of Engineers Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2006 Post-Hurricane ... |
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March 2006 Mississippi and Alabama USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2006 USGS Mississippi ... |
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September 2006 Mississippi and Alabama USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2006 USGS Mississippi ... |
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September 2007 Southwest Florida Division of Emergency Management Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 Southwest Florida ... |
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June 2008 Alabama and Florida USGS EAARL Lidar-derived dune crest, toe and shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the June 2008 Louisiana, ... |
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2008 Post-Hurricane Gustav Northern Gulf of Mexico USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Post-Hurricane ... |
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2008 South Louisiana USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 South Louisiana ... |
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2009 Western Gulf of Mexico USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Western Gulf of ... |
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2010 Alabama and Florida USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Alabama and Florida ... |
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2010 Florida West Coast USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Florida West Coast ... |
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2010 Louisiana and Mississippi USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Louisiana and ... |
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2011 Northern Gulf Coast USACE Lidar-derived dune crest, toe and shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 Northern Gulf Coast ... |
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2012 Post-Hurricane Isaac USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ... |
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2013 Dauphin Island USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 Dauphin Island ... |
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2014 USGS CMGP Post-Sandy Long Island Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 USGS CMGP Post ... |
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2014 Mobile County, Alabama Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 Mobile County, ... |
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2015 Mississippi and Alabama USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2015 Mississippi and ... |
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1998 Fall Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Fall Gulf Coast ... |
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1999 Fall Texas USGS/NASA/NOAA ATM Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1999 Fall Gulf Coast ... |
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Coastal Single-beam Bathymetry Data Collected in 2022 From Breton Island, Louisiana
As part of the restoration monitoring component of the Deepwater Horizon early restoration project, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) conducted single-beam and multibeam bathymetry surveys around Breton Island, Louisiana (LA), from August 3-5, 2022, for Field Activity Number (FAN) 2022-328-FA. The purpose of data collection was to develop a baseline digital elevation model of the seafloor around Breton Island for comparison with both ... |
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Orthoimagery of Big Pine Ledge, Florida, 2022
A seabed orthoimage was developed from underwater images collected at Big Pine Ledge (BPL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 800x160 meters (m) (0.12 square kilometers [km]) in size. It was created using image-averaging methods and saved as a tiled Geographic Tagged Image ... |
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Orthomosaic of Big Pine Ledge, Florida, 2022
A seabed orthoimage was developed from underwater images collected at Big Pine Ledge (BPL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 800x160 meters (m) (0.12 square kilometers [km]) in size. It was created using image-mosaicking methods and saved as a tiled Geographic Tagged ... |
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Point cloud data of Big Pine Ledge, Florida, 2022
A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Big Pine Ledge (BPL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, and RGB colors derived from the color-corrected imagery. LIDAR Aerial Survey files (LAS) – and its compressed form, LAZ – is an open format ... |
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Orthoimagery of Summerland Ledge, Florida, 2022
A seabed orthoimage was developed from underwater images collected at Summerland Ledge (SL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 450x180 meters (m) (0.081 square kilometers [km]) in size. It was created using image-averaging methods and saved as a Geographic Tagged Image ... |
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Orthomosaic of Summerland Ledge, Florida, 2022
A seabed orthoimage was developed from underwater images collected at Summerland Ledge (SL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 450x180 meters (m) (0.081 square kilometers [km]) in size. It was created using image-mosaicing methods and saved as a Geographic Tagged Image ... |
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Point cloud data of Summerland Ledge, Florida, 2022
A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Summerland Ledge (SL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, and RGB colors derived from the color-corrected imagery. LIDAR Aerial Survey files (LAS) - and its compressed form, LAZ - is an open format ... |
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2004 Post-Hurricane Ivan Northern Gulf of Mexico EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 USGS Post-Ivan ... |
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Orthoimagery of Looe Key, Florida, 2022
A seabed orthoimage was developed from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 850x160 meters (m) (0.13 square kilometers [km]) in size. It was created using image-averaging methods and saved as Geographic Tagged Image File Format ... |
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Quicklook Orthoimage of Looe Key, Florida, 2022
A seabed orthoimage was developed from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 850x160 meters (m) (0.13 square kilometers [km]) in size. This "quicklook" version of the dataset was created using image-averaging methods and saved as ... |
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Orthomosaic of Looe Key, Florida, 2022
A seabed orthoimage was developed from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 850x160 meters (m) (0.13 square kilometers [km]) in size. It was created using image-mosaicking methods and saved as Geographic Tagged Image File Format ... |
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Point cloud data of Looe Key, Florida, 2022
A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, and RGB colors derived from the color-corrected imagery. LIDAR Aerial Survey files (LAS) - and its compressed form, LAZ - is an open format developed for ... |
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Landscape and contextual field work photos, with locations, taken in September 2023, pre and post Hurricane Lee at Head of the Meadow, Marconi, and Nauset Light beaches in CACO, MA
The data in this release map Marconi Beach, Head of the Meadow Beach, and Nauset Light Beach, in Cape Cod National Seashore (CACO), Massachusetts, before and after Hurricane Lee in September 2023. U.S Geological Survey personnel conducted field surveys to collect topographic data using global navigation satellite systems (GNSS) at all three beaches. In addition, at Nauset Light Beach, an uncrewed aerial system (UAS) was used to collect images with a Ricoh GRII camera for use in structure from motion ... |
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Digital surface models representing Nauset Light Beach, Eastham, MA on September 14 and 20, 2023, pre and post Hurricane Lee
The data in this release map Marconi Beach, Head of the Meadow Beach, and Nauset Light Beach, in Cape Cod National Seashore (CACO), Massachusetts, before and after Hurricane Lee in September 2023. U.S Geological Survey personnel conducted field surveys to collect topographic data using global navigation satellite systems (GNSS) at all three beaches. In addition, at Nauset Light Beach, an uncrewed aerial system (UAS) was used to collect images with a Ricoh GRII camera for use in structure from motion ... |
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Ground control points and GPS data collected in September 2023, pre and post Hurricane Lee at Head of the Meadow, Marconi, and Nauset Light beaches in CACO, MA
The data in this release map Marconi Beach, Head of the Meadow Beach, and Nauset Light Beach, in Cape Cod National Seashore (CACO), Massachusetts, before and after Hurricane Lee in September 2023. U.S Geological Survey personnel conducted field surveys to collect topographic data using global navigation satellite systems (GNSS) at all three beaches. In addition, at Nauset Light Beach, an uncrewed aerial system (UAS) was used to collect images with a Ricoh GRII camera for use in structure from motion ... |
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Low-altitude aerial imagery collected from a UAS at Nauset Light Beach, Eastham, MA on September 14 and 20, 2023, pre and post Hurricane Lee
The data in this release map Marconi Beach, Head of the Meadow Beach, and Nauset Light Beach, in Cape Cod National Seashore (CACO), Massachusetts, before and after Hurricane Lee in September 2023. U.S Geological Survey personnel conducted field surveys to collect topographic data using global navigation satellite systems (GNSS) at all three beaches. In addition, at Nauset Light Beach, an uncrewed aerial system (UAS) was used to collect images with a Ricoh GRII camera for use in structure from motion ... |
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Swath bathymetry 13-m-cell-size grid of quadrangle 5 on Stellwagen Bank offshore of Boston, Massachusetts collected by the U.S. Geological Survey aboard the CCGS Frederick G. Creed from 1994-1996
The U.S. Geological Survey (USGS), in cooperation with the National Marine Sanctuary Program of the National Oceanic and Atmospheric Administration (NOAA), has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The interpretive datasets and source information presented here are for quadrangle 5, which is one of 18 similarly sized segments of the 3,700 square kilometer (km2) SBNMS region. The seabed of the SBNMS region is a glaciated ... |
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Portion of the 1-meter (m) contours in quadrangle 5 of the Stellwagen Bank Survey Area offshore of Boston, Massachusetts based on bathymetry data collected by the U.S. Geological Survey from 1994-1996
The U.S. Geological Survey (USGS), in cooperation with the National Marine Sanctuary Program of the National Oceanic and Atmospheric Administration (NOAA), has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The interpretive datasets and source information presented here are for quadrangle 5, which is one of 18 similarly sized segments of the 3,700 square kilometer (km2) SBNMS region. The seabed of the SBNMS region is a glaciated ... |
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Bathymetry from multibeam echosounder data collected offshore of Eureka, California
This 2-m-resolution bathymetry data for the Offshore of Eureka, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). Bathymetry data were collected by Fugro Pelagos in 2007 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounder systems. The data were processed by the California State University Monterey Bay Seafloor Mapping Lab. The bathymetry data are available as a georeferenced TIFF image. |
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Sediment thickness from seismic reflection data collected offshore of Eureka, California
This 100-m-resolution sediment thickness data raster for the Offshore of Eureka, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). Seismic data were collected by the USGS in 2009 using a mini-sparker seismic systems installed on the Humboldt State University R/V Coral Sea. The data were processed by the USGS into segy format files. The data are available as a georeferenced TIFF image. |
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Bathymetry of Whales Tail Marsh tidal creeks, South San Francisco Bay, California, 2023
Bathymetric data collected in Whales Tail Marsh tidal creeks, South San Francisco Bay, California, in 2023 with a shallow draft vessel equipped with a single-beam sonar system and global navigation satellite system (GNSS) receiver. The bathymetric data are provided in a comma-separated text file. |
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Topographic data from two marshes and adjacent shallows in Northern San Francisco Bay, California, 2022-2023
Topographic data were collected in the Corte Madera Marsh, San Pablo National Wildlife Refuge Marsh, and at the time-series stations in the shallows adjacent to each marsh in Northern San Francisco Bay between April 2022 and September 2023. The topographic data were acquired using global satellite navigation system receivers that were either mounted on backpacks and hiked over the marsh surface or mounted on a survey rod held shipside against a deployed platform or on the water surface. Sometimes an ... |
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Acoustic-backscatter data for Jenkinson Lake, California collected during USGS field activity 2022-649-FA
Here August 2022 1-m resolution acoustic-backscatter data are provided for Jenkinson Lake, California. Acoustic-backscatter data were collected during three separate SWATHPlus surveys of Jenkinson Lake. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity numbers 2022-604-FA (January 2022), 2022-649-FA (August 2022), and 2023-634-FA (July 2023). Data are provided as a GeoTIFF image. |
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Bathymetry data for Jenkinson Lake, California collected during USGS field activity 2022-649-FA
Here August 2022 1-m resolution bathymetry data of Jenkinson Lake, California are provided for the entire lake and 0.5-m resolution bathymetry data are provided for the shallower upper basin. Bathymetry data were collected during three separate SWATHPlus surveys of Jenkinson Lake. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity numbers 2022-604-FA (January 2022), 2022-649-FA (August 2022), and 2023-634-FA (July ... |
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Acoustic-backscatter data for Jenkinson Lake, California collected during USGS field activity 2022-604-FA
Here January 2022 1-m resolution acoustic-backscatter data are provided for Jenkinson Lake, California. Acoustic-backscatter data were collected during three separate SWATHPlus surveys of Jenkinson Lake. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity numbers 2022-604-FA (January 2022), 2022-649-FA (August 2022), and 2023-634-FA (July 2023). Data are provided as a GeoTIFF image. |
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Bathymetry data for Jenkinson Lake, California collected during USGS field activity 2022-604-FA
Here January 2022 1-m resolution bathymetry data of Jenkinson Lake, California are provided for the entire lake and 0.5-m resolution bathymetry data are provided for the shallower upper basin. Bathymetry data were collected during three separate SWATHPlus surveys of Jenkinson Lake. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity numbers 2022-604-FA (January 2022), 2022-649-FA (August 2022), and 2023-634-FA ... |
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Acoustic-backscatter data for Jenkinson Lake, California collected during USGS field activity 2023-634-FA
Here July 2023 1-m resolution acoustic-backscatter data are provided for Jenkinson Lake, California. Acoustic-backscatter data were collected during three separate SWATHPlus surveys of Jenkinson Lake. Data were collected and processed by the the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity numbers 2022-604-FA (January 2022), 2022-649-FA (August 2022), and 2023-634-FA (July 2023). Data are provided as a GeoTIFF image. |
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Bathymetry data for Jenkinson Lake, California collected during USGS field activity 2023-634-FA
Here July 2023 1-m resolution bathymetry data of Jenkinson Lake, California are provided for the entire lake and 0.5-m resolution bathymetry data are provided for the shallower upper basin. Bathymetry data were collected during three separate SWATHPlus surveys of Jenkinson Lake. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity numbers 2022-604-FA (January 2022), 2022-649-FA (August 2022), and 2023-634-FA (July ... |
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SWASH Model Water Level Time Series at Wrightsville Beach, NC, USA for ILM site
This data release contains model output of water level elevations resulting from deterministic simulations at Wrightsville Beach, North Carolina (NC), USA. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Birchler and others (2024). |
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SWASH Model Water Level Time Series at Wrightsville Beach, NC, USA for MHX site
This data release contains model output of water level elevations resulting from deterministic simulations at Wrightsville Beach, North Carolina (NC), USA. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Birchler and others (2024). |
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SWASH Model Water Level Time Series at Wrightsville Beach, NC, USA for PIER site
This data release contains model output of water level elevations resulting from deterministic simulations at Wrightsville Beach, North Carolina (NC), USA. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Birchler and others (2024). |
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5 m Bathymetric Contours for Long Island Sound (LIS1992)
This bathymetric contour data set was derived from a gridded data set obtained from URI (B.Tyce, G. Hatcher). They used the "Gridder" program to obtain the grid. This gridded data set was generated from the original NOS soundings from 9 track tape that was cleaned up and edited at URI. This work was done with the intention of producing the color poster called "Long Island Sound Estuary" (Connecticut Dept. of Environmental Protection"), 1993. The accuracy is questionable. |
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1 m Digital Bathymetric Contours from NOAA Charts as Organized for the LISSGIS Library (LISBATHY)
The Long Island Sound Study (LISS) compiled data from a number of different sources, integrated new data, and assembled a comprehensive spatial database for areas of the States of Connecticut, New York, and portions of Rhode Island which border Long Island Sound. |
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2014 East Coast New Hampshire USACE/NAE ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Sandy
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 East Coast New ... |
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08ACH03_first_return_metadata: EAARL Coastal Topography-Louisiana, Alabama, and Florida, June 2008
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ... |
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08ACH03_last_return_metadata: EAARL Coastal Topography-Louisiana, Alabama, and Florida, June 2008
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ... |
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14CCT01_metadata: Sedimentary Data From Grand Bay, Alabama/Mississippi, 2014-2016
This data release is an archive of sedimentary field and laboratory analytical data collected in Grand Bay, Alabama/Mississippi from 2014-2016 by scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC). This work, a component of the SPCMSC’s Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, provides the necessary data to quantify sedimentation rates and sediment sources for the marsh and estuary. The SSIEES project ... |
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16CCT03_metadata: Sedimentary Data From Grand Bay, Alabama/Mississippi, 2014-2016
This data release is an archive of sedimentary field and laboratory analytical data collected in Grand Bay, Alabama/Mississippi from 2014-2016 by scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC). This work, a component of the SPCMSC’s Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, provides the necessary data to quantify sedimentation rates and sediment sources for the marsh and estuary. The SSIEES project ... |
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Terrestrial-Based Lidar Beach Topography of Fire Island, New York, May 2015 - DEM data
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collected terrestrial-based light detection and ranging (T-lidar) elevation data at Fire Island, New York. The data were collected on May 18, 2015 as part of the ongoing beach monitoring within Hurricane Sandy Supplemental Project GS2-2B, and will be used to document and assess the morphological storm response and post-storm ... |
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Terrestrial-Based Lidar Beach Topography of Fire Island, New York, May 2015 - XYZ Data
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collected terrestrial-based light detection and ranging (T-lidar) elevation data at Fire Island, New York. The data were collected on May 18, 2015 as part of the ongoing beach monitoring within Hurricane Sandy Supplemental Project GS2-2B, and will be used to document and assess the morphological storm response and post-storm ... |
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ANGD2014_EAARLB_z20_v09g12A_metadata: Lidar-Derived Seamless (Bare Earth and Submerged) Point Cloud for Coastal Topography—Anegada, British Virgin Islands, 2014
ASCII XYZ point cloud data for a portion of the environs of Anegada, British Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected March 19-20, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ... |
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ASIS2003_EAARLA_BE_z18_n88g99_metadata: EAARL Coastal Topography--Northern Assateague Island National Seashore, Maryland and Virginia, 2003: Bare Earth
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over northern Assateague Island National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground ... |
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ASIS2003_EAARLA_BE_z18_n88g99_mosaic_metadata: EAARL Coastal Topography--Northern Assateague Island National Seashore, Maryland and Virginia, 2003: Bare Earth
A bare-earth topography Digital Elevation Model (DEM) mosaic for the northern half of Assateague Island National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over northern Assateague Island National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research ... |
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ASIS2005_EAARLA_BE_z18_n88g12B_metadata: EAARL Coastal Topography--Assateague Island National Seashore, Maryland and Virginia, 2005: Bare Earth
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Assateague Island National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, ... |
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ASIS2005_EAARLA_BE_z18_n88g12B_mosaic_metadata: EAARL Coastal Topography--Assateague Island National Seashore, Maryland and Virginia, 2005: Bare Earth
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Assateague Island National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Assateague Island National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed ... |
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ASIS2005_EAARLA_FS_z18_n88g12B_metadata: EAARL Coastal Topography--Assateague Island National Seashore, Maryland and Virginia, 2005: First Surface
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Assateague Island National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, ... |
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ASIS2005_EAARLA_FS_z18_n88g12B_mosaic_metadata: EAARL Coastal Topography--Assateague Island National Seashore, Maryland and Virginia, 2005: First Surface
A first-surface topography Digital Elevation Model (DEM) mosaic for the Assateague Island National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Assateague Island National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed ... |
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ASIS2015_HRJQ_BE_z18_n88g12B_classified_metadata: Lidar-Derived Classified Bare-Earth Point-Cloud for Coastal Topography—Assateague Island, Maryland and Virginia, Post-Hurricane Joaquin, 26 November 2015
Binary point-cloud data were produced for Assateague Island, Maryland and Virginia, post-Hurricane Joaquin, from remotely sensed, geographically referenced elevation measurements collected by Quantum Spatial using a Leica ALS70 (1064-nm wavelength) lidar sensor. |
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ASIS2016_HRHM_SM_z18_n88g12B_classified_metadata: Lidar-Derived Classified Point-Cloud for Coastal Topography—Assateague Island, Maryland and Virginia, Post-Hurricane Hermine, 10-12 September 2016
Binary point-cloud data were produced for Assateague Island, Maryland and Virginia, post-Hurricane Hermine, from remotely sensed, geographically referenced elevation measurements collected by Quantum Spatial using a Riegl VQ-880-G (532-nm wavelength circular scan and 1064-nm wavelength linear scan) lidar sensor. |
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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Interpretive Video Previews
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ... |
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BITH2014_BeaumontLNRUnits_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Beaumont and Lower Neches River Units, Texas, 2014
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Beaumont and Lower Neches River Units of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 22, 23, 25, 26, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced ... |
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BITH2014_BeaumontLNRUnits_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Beaumont and Lower Neches River Units, Texas, 2014
A first-surface topography Digital Elevation Model (DEM) mosaic for the Beaumont and Lower Neches River Units of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 22, 23, 25, 26, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental ... |
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BITH2014_BigSandyCreekCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Corridor Unit, Texas, 2014
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Big Sandy Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 29, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a ... |
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BITH2014_BigSandyCreekCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Corridor Unit, Texas, 2014
A first-surface topography Digital Elevation Model (DEM) mosaic for the Big Sandy Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 29, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B) ... |
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BITH2014_BigSandyCreekUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Unit, Texas, 2014
A bare-earth topography digital elevation model (DEM) mosaic for the Big Sandy Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ranging ... |
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BITH2014_BigSandyCreekUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Unit, Texas, 2014
A first-surface topography digital elevation model (DEM) mosaic for the Big Sandy Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ... |
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BITH2014_LanceRosierUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Lance Rosier Unit, Texas, 2014
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Lance Rosier Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 15, 21, 22, 25, 26, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed ... |
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BITH2014_LanceRosierUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Lance Rosier Unit, Texas, 2014
A first-surface topography Digital Elevation Model (DEM) mosaic for the Lance Rosier Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 15, 21, 22, 25, 26, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a ... |
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BITH2014_LowerNechesRiverCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Lower Neches River Corridor Unit, Texas, 2014
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Lower Neches River Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 23, 25, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne ... |
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BITH2014_LowerNechesRiverCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Lower Neches River Corridor Unit, Texas, 2014
A first-surface topography Digital Surface Model (DSM) mosaic for the Lower Neches River Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 23, 25, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne ... |
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BITH2014_MenardCreekCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Menard Creek Corridor Unit, Texas, 2014
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Menard Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 21 and 22, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging ... |
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BITH2014_MenardCreekCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Menard Creek Corridor Unit, Texas, 2014
A first-surface topography Digital Surface Model (DSM) mosaic for the Menard Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 21 and 22, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging ... |
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BITH2014_NBJGBUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Neches Bottom and Jack Lore Baygall Unit, Texas, 2014
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Neches Bottom and Jack Lore Baygall Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 21, 23, 25, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne ... |
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BITH2014_NBJGBUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Neches Bottom and Jack Lore Baygall Unit, Texas, 2014
A first-surface topography Digital Elevation Model (DEM) mosaic for the Neches Bottom and Jack Lore Baygall Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 21, 23, 25, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne ... |
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BITH2014_TurkeyCreekUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Turkey Creek Unit, Texas, 2014
A bare-earth topography digital elevation model (DEM) mosaic for the Turkey Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 25, 26, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed ... |
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BITH2014_TurkeyCreekUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Turkey Creek Unit, Texas, 2014
A first-surface topography digital elevation model (DEM) mosaic for the Turkey Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 25, 26, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a ... |
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BITH2014_VillageCreekCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Village Creek Corridor Unit, Texas, 2014
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Village Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 23, 26, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL ... |
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BITH2014_VillageCreekCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography—Big Thicket National Preserve: Village Creek Corridor Unit, Texas, 2014
A first-surface topography Digital Surface Model (DSM) mosaic for the Village Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 23, 26, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar ... |
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Topobathymetric Lidar Survey of Breton and Gosier Islands, Louisiana, January 16 and 18, 2014 - Point-cloud Data
This dataset contains binary point-cloud data, produced from remotely sensed, geographically referenced topobathymetric measurements collected by Photo Science, Inc., encompassing the Breton and Gosier Island, LA study areas. The original area of interest was buffered by 100 meters to ensure complete coverage, resulting in approximately 75 square miles of lidar data. The Breton Island Lidar project called for the planning, acquisition, processing, and derivative products of topobathymetric lidar data, ... |
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Topobathymetric Lidar Survey of Breton and Gosier Islands, Louisiana, January 16 and 18, 2014 - DEM Data
This dataset contains binary point-cloud data and a Digital Elevation Model (DEM), produced from remotely sensed, geographically referenced topobathymetric measurements collected by Photo Science, Inc., encompassing the Breton Island, LA study area. The original area of interest was buffered by 100 meters to ensure complete coverage, resulting in approximately 75 square miles of lidar data. The Breton Island Lidar project called for the planning, acquisition, processing, and derivative products of ... |
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CACO2002_EAARLA_BE_z19_n88g12B_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: Bare Earth
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation ... |
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CACO2002_EAARLA_BE_z19_n88g12B_mosaic_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: Bare Earth
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Cape Cod National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system ... |
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CACO2002_EAARLA_FS_z19_n88g12B_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: First Surface
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation ... |
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CACO2002_EAARLA_FS_z19_n88g12B_mosaic_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: First Surface
A first-surface topography Digital Elevation Model (DEM) mosaic for the Cape Cod National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging ... |
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Chenier_Plain_2017_SBB_200m_DEM_metadata: Nearshore Single-Beam Bathymetry XYZ Data Collected in 2017 from the Chenier Plain, Louisiana
As a part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the Chenier Plain, Louisiana from Marsh Island to Sabine Pass. The goal of the BICM program is to provide long-term data on Louisiana's coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in ... |
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Chenier_Plain_2017_SBB_ITRF00_Trackline_metadata: Nearshore Single-Beam Bathymetry XYZ Data Collected in 2017 from the Chenier Plain, Louisiana
As a part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the Chenier Plain, Louisiana from Marsh Island to Sabine Pass. The goal of the BICM program is to provide long-term data on Louisiana’s coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described ... |
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Chenier_Plain_2017_SBB_XYZ_metadata: Nearshore Single-Beam Bathymetry XYZ Data Collected in 2017 from the Chenier Plain, Louisiana
As a part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the Chenier Plain, Louisiana from Marsh Island to Sabine Pass. The goal of the BICM program is to provide long-term data on Louisiana's coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in ... |
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CRKR2014_EAARLB_z17_n88g12A_metadata: EAARL-B Submerged Topography—Crocker Reef, Florida, 2014
ASCII XYZ point cloud data for a portion of the submerged environs of Crocker Reef, Florida, were produced from remotely sensed, geographically referenced elevation measurements collected on April 13 and 22, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. ... |
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CRKR2014_EAARLB_z17_n88g12A_mosaic_metadata: EAARL-B Submerged Topography—Crocker Reef, Florida, 2014
A submerged topography digital elevation model (DEM) mosaic for a portion of the submerged environs of Crocker Reef, Florida, was produced from remotely sensed, geographically referenced elevation measurements collected on April 13 and 22, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation ... |
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ds765_General_metadata: Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012
Derived products of a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th), were produced by the U.S. Geological Survey (USGS) from remotely sensed, geographically referenced elevation measurements collected by Photo Science, Inc. (Delaware, Maryland, Virgina, and North Carolina) and Woolpert, Inc. (Fire Island, New York) using airborne lidar sensors. Post ... |
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ds765_metadata: Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012
Dune features (dune crest and toe elevations) and mean-high-water shoreline data for a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th), were produced by the U.S. Geological Survey (USGS) from remotely sensed, geographically referenced elevation measurements collected by Photo Science and Woolpert using using airborne lidar sensors. Binary point-cloud ... |
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DS888-metadata: EAARL-B Coastal Topography—Fire Island, New York, pre-Hurricane Sandy, 2012: Seamless (Bare Earth and Submerged)
American Standard Code Information Interchange XYZ and binary point-cloud data, as well as a seamless (bare-earth and submerged) digital elevation model for part of Fire Island, New York, pre-Hurricane Sandy (October 2012 hurricane), were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ranging system ... |
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DS888_PRSF_tile_extents: EAARL-B Coastal Topography—Fire Island, New York, pre-Hurricane Sandy, 2012: Seamless (Bare Earth and Submerged)
This shapefile was produced from 53 2-kilometer by 2-kilometer tile extents of remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface ... |
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EasternLA2008_EAARLA_BE_n88g03_metadata: EAARL Coastal Topography–Eastern Louisiana Barrier Islands, 09 March 2008: Bare Earth
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high ... |
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EasternLA2008_EAARLA_BE_n88g03_mosaic_metadata: EAARL Coastal Topography–Eastern Louisiana Barrier Islands, 09 March 2008: Bare Earth
A Digital Elevation Model (DEM) mosaic was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system ... |
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FIIS2002_EAARLA_BE_z18_n88g99_metadata: Lidar-Derived Bare-Earth XYZ for EAARL Coastal Topography—Fire Island, New York, 2002
ASCII XYZ data for Fire Island, New York, was produced from remotely sensed, geographically referenced elevation measurements collected October 25 and November 8, 2002 by the U.S. Geological Survey, in cooperation with the National Park Service (NPS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the first-generation Experimental Advanced Airborne Research Lidar (EAARL-A), a pulsed laser ranging system mounted onboard an aircraft to ... |
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KEYS2016_SM_z17_n88g12B_classified_metadata: Coastal Topography-Upper Florida Keys Reef Tract, Florida, 26-30 June 2016
Binary point-cloud data were produced for a portion of the upper Florida Keys reef tract, Florida, from remotely sensed, geographically referenced elevation measurements collected by Leading Edge Geomatics (LEG) using a Leica Chiroptera II Bathymetric and Topographic Sensor. Dewberry reports that the nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1-Unclassified, 2-Ground ... |
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KEYS2016_SM_z17_n88g12B_mosaic_metadata: Coastal Topography-Upper Florida Keys Reef Tract, Florida, 26-30 June 2016
A digital elevation model (DEM) mosaic was produced for a portion of the upper Florida Keys reef tract, Florida, from remotely sensed, geographically referenced elevation measurements collected by Leading Edge Geomatics (LEG) using a Leica Chiroptera II Bathymetric and Topographic Sensor. Dewberry reports that the nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1 ... |
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LINY2011_HRIR_BE_z18_n88g09_classified_metadata: Coastal Topography—Long Island, New York, Post-Hurricane Irene, 30 August 2011
Binary point-cloud data were produced for Long Island, New York, from remotely sensed, geographically referenced elevation measurements collected by Woolpert, Inc. using an Leica ALS50-II lidar sensor flown on a Cessna 404 aircraft. These data were collected post-Hurricane Irene on August 30, 2011. |
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LINY2011_HRIR_BE_z18_n88g09_mosaic_metadata: Coastal Topography—Long Island, New York, Post-Hurricane Irene, 30 August 2011
A digital elevation model (DEM) mosaic was produced for Long Island, New York, from remotely sensed, geographically referenced elevation measurements collected by Woolpert, Inc. using an Leica ALS50-II lidar sensor flown on a Cessna 404 aircraft. These data were collected post-Hurricane Irene on August 30, 2011. |
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MS_AL_Benthic_Foram_CENSUS_metadata: Benthic foraminiferal data from the eastern Mississippi Sound salt marshes and estuaries
Microfossil (benthic foraminifera) and coordinate/elevation data were obtained from sediments collected in the coastal zones of Mississippi and Alabama, including marsh and estuarine environments of eastern Mississippi Sound and Mobile Bay, in order to develop a census for coastal environments and to aid in paleoenvironmental reconstruction. These data provide a baseline dataset for use in future wetland and estuarine change studies and assessments, both descriptive and predictive types. The data presented ... |
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MS_AL_Cores_Foram_CENSUS_metadata: Benthic foraminiferal data from sedimentary cores collected in the Grand Bay (Mississippi) and Dauphin Island (Alabama) salt marshes
Microfossil (benthic foraminifera) data from coastal areas were collected from state and federally managed lands within the Grand Bay National Estuarine Research Reserve and Grand Bay National Wildlife Refuge, Grand Bay, Mississippi/Alabama; federally managed lands of Bon Secour National Wildlife Refuge on Cedar Island and Little Dauphin Island, Alabama; and municipally managed land around Dauphin Island, Alabama. Samples were analyzed and quantified for foraminiferal census in order to document changes to ... |
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MS_AL_Cores_XYZ_metadata: Benthic foraminiferal data from sedimentary cores collected in the Grand Bay (Mississippi) and Dauphin Island (Alabama) salt marshes
Microfossil (benthic foraminifera) data from coastal areas were collected from state and federally managed lands within the Grand Bay National Estuarine Research Reserve and Grand Bay National Wildlife Refuge, Grand Bay, Mississippi/Alabama; federally managed lands of Bon Secour National Wildlife Refuge on Cedar Island and Little Dauphin Island, Alabama; and municipally managed land around Dauphin Island, Alabama. Samples were analyzed and quantified for foraminiferal census in order to document changes to ... |
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MS_AL_XYZ_metadata: Benthic foraminiferal data from the eastern Mississippi Sound salt marshes and estuaries
Microfossil (benthic foraminifera) and coordinate/elevation data were obtained from sediments collected in the coastal zones of Mississippi and Alabama, including marsh and estuarine environments of eastern Mississippi Sound and Mobile Bay, in order to develop a census for coastal environments and to aid in paleoenvironmental reconstruction. These data provide a baseline dataset for use in future wetland and estuarine change studies and assessments, both descriptive and predictive types. The data presented ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 2010 Simulation With 0.5-meter of Sea Level Rise
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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ST1_Final_DEM_metadata: Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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ST2_Final_DEM_metadata: Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration measures for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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ST3_Final_DEM_metadata: Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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ST4_Final_DEM_metadata: Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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STCR2014_EAARLB_v09g12B_metadata: EAARL-B Submerged Topography–Saint Croix, U.S. Virgin Islands, 2014
ASCII XYZ point cloud data for a portion of the submerged environs of Saint Croix, U.S. Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected on March 11, 19, and 21, 2014 by the U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration (NOAA) Coral Reef Conservation Program. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a ... |
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STCR2014_EAARLB_v09g12B_mosaic_metadata: EAARL-B Submerged Topography–Saint Croix, U.S. Virgin Islands, 2014
A submerged topography Digital Elevation Model (DEM) mosaic for a portion of the submerged environs of Saint Croix, U.S. Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected on March 11, 19, and 21, 2014 by the U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration (NOAA) Coral Reef Conservation Program. Elevation measurements were collected over the area using the second-generation Experimental Advanced ... |
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Acoustic-backscatter data for Ozette Lake, Washington collected during USGS field activity 2019-622-FA
2-m resolution acoustic-backscatter data were collected during a July 2019 SWATHPlus survey of Ozette Lake, Washington. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity number 2019-622-FA. The 2-m acoustic-backscatter data are provided as a GeoTIFF image. |
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Coastal Multibeam Bathymetry Data Collected in August 2022 From Breton Island, Louisiana
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, Gulf side of Breton Island, Louisiana (LA), from August 2-5, 2022. This dataset, Breton_2022_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. |
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AllCases_Sediment_Fluxes: Model Sensitivity to Sediment Parameters and Bed Composition in Delft3D: Model Output
The sensitivity to sediment parameterization and initial bed configuration on sediment transport processes and morphological evolution are assessed through process-based numerical modeling. Six sensitivity cases using a previously validated model for Dauphin Island, Alabama were modeled using Delft3D (developed by Deltares) to understand impacts on bed level morphology, barrier island evolution, and sediment fluxes. Delft3D model output of suspended and bedload sediment fluxes, and final bed levels data are ... |
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Bathymetry, topography, and sediment grain-size data from the Elwha River delta, Washington
This data release contains bathymetry and topography data from surveys performed on the Elwha River delta between 2010 and 2017. Sediment grain-size data are available for selected surveys performed after May 2012. This data release will be updated as additional bathymetry, topography, and surface-sediment grain-size data from future surveys become available. |
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Central San Francisco Bay bathymetric change: 1855 to 1979
This data release provides a series of four bathymetric change grids generated from historical bathymetric surveys collected in central San Francisco Bay, CA from the 1855 to 1979. The National Ocean Service (NOS) and its predecessor, the United States Coast and Geodetic Survey, collected hydrographic surveys in 1855, 1895, 1920, 1947, and 1979. Surface modeling software was used to generate bathymetric DEMs of each of these surveys. The bathymetric DEMs were then adjusted to account for gridding ... |
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Central San Francisco Bay bathymetry: 1855 to 1979
This data release provides a series of five bathymetric digital elevation models (DEMs) of central San Francisco Bay, CA generated from single-beam hydrographic surveys collected from 1855 to 1979. The DEMs were constructed based upon historical United States Coast and Geodetic Survey and National Ocean Service (NOS) surveys collected in 1855, 1895, 1920, 1947, and 1979. Depth soundings from the pre-1930s surveys were manually digitized and georeferenced while the later surveys were obtained in digital ... |
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San Pablo Bay bathymetric change: 1856 to 1983
This data release provides a series of five bathymetric change grids generated from historical bathymetric surveys collected in San Pablo Bay, CA from the 1856 to 1983. The National Ocean Service (NOS) and its predecessor, the United States Coast and Geodetic Survey, collected hydrographic surveys in 1856, 1887, 1898, 1922, 1951, and 1983. Surface modeling software was used to generate bathymetric DEMs of each of these surveys. The bathymetric DEMs were then adjusted to account for gridding interpolation ... |
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San Pablo Bay bathymetry: 1856 to 1983
This data release provides a series of six bathymetric digital elevation models (DEMs) of San Pablo Bay, CA generated from single-beam hydrographic surveys collected from 1856 to 1983. The DEMs were constructed based upon historical United States Coast and Geodetic Survey and National Ocean Service (NOS) surveys collected in 1856, 1887, 1898, 1922, 1951, and 1983. Depth soundings from the pre-1930s surveys were manually digitized and georeferenced while the later surveys were obtained in digital format, and ... |
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South San Francisco Bay bathymetric change: 1858 to 2005
This data release provides a series of five bathymetric change grids generated from historical bathymetric surveys collected in south San Francisco Bay, CA from the 1858 to 2005. The National Ocean Service (NOS) and its predecessor, the United States Coast and Geodetic Survey, collected hydrographic surveys in 1858, 1898, 1931, 1956, and 1983 plus Sea Surveyor, Inc. collected a survey in 2005. Surface modeling software was used to generate bathymetric DEMs of each of these surveys. The bathymetric DEMs were ... |
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South San Francisco Bay bathymetry: 1858 to 2005
This data release provides a series of six bathymetric digital elevation models (DEMs) of south San Francisco Bay, CA generated from single-beam hydrographic surveys collected from 1858 to 2005. The DEMs were constructed based upon historical United States Coast and Geodetic Survey and National Ocean Service (NOS) surveys collected in 1858, 1898, 1931, 1956, and 1983 as well as a survey collected by Sea Surveyor, Inc. in 2005. Depth soundings from the pre-1930s surveys were manually digitized and ... |
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Suisun Bay bathymetric change: 1866 to 1990
This data release provides a series of four bathymetric change grids generated from historical bathymetric surveys collected in Suisun Bay, CA from the 1866 to 1990. The National Ocean Service (NOS) and its predecessor, the United States Coast and Geodetic Survey, collected hydrographic surveys in 1866, 1886, 1923, 1941, and 1990. Surface modeling software was used to generate bathymetric DEMs of each of these surveys. The bathymetric DEMs were then adjusted to account for gridding interpolation bias and ... |
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Suisun Bay bathymetry: 1866 to 1990
This data release provides a series of five bathymetric digital elevation models (DEMs) of Suisun Bay, CA generated from single-beam hydrographic surveys collected from 1866 to 1990. The DEMs were constructed based upon historical United States Coast and Geodetic Survey and National Ocean Service (NOS) surveys collected in 1866, 1886, 1923, 1941, and 1990. Depth soundings from the pre-1930s surveys were manually digitized and georeferenced while the later surveys were obtained in digital format, and all ... |
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Nearshore bathymetry data from the Elwha River delta, Washington, August 2019
This portion of the USGS data release presents bathymetric data collected during surveys performed on the Elwha River delta, Washington in 2019 (USGS Field Activity Number 2019-633-FA). Bathymetric data were collected using personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, August 2019
This part of the data release presents topography data from the Elwha River delta collected in August 2019. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Swath bathymetry 13-m-cell-size grid of quadrangle 2 on Stellwagen Bank offshore of Boston, Massachusetts collected by the U.S. Geological Survey aboard the CCGS Frederick G. Creed from 1994-1996
The U.S. Geological Survey (USGS), in cooperation with the National Marine Sanctuary Program of the National Oceanic and Atmospheric Administration (NOAA), has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The interpretive datasets and source information presented here are for quadrangle 2, which is one of 18 similarly-sized quadrangles that comprise the 3,700 square kilometer (km2) SBNMS region. The seabed of the SBNMS region is a ... |
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Portion of the 1-meter (m) contours in quadrangle 2 of the Stellwagen Bank Survey Area offshore of Boston, Massachusetts based on bathymetry data collected by the U.S. Geological Survey from 1994-1996
The U.S. Geological Survey (USGS), in cooperation with the National Marine Sanctuary Program of the National Oceanic and Atmospheric Administration (NOAA), has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The interpretive datasets and source information presented here are for quadrangle 2, which is one of 18 similarly-sized quadrangles that comprise the 3,700 square kilometer (km2) SBNMS region. The seabed of the SBNMS region is a ... |
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Peat Thickness Measurements from Grand Bay, Mississippi and Alabama
Location and elevation data were collected along with peat auger cores during six U.S. Geological Survey (USGS) field activities from 2013-2018 in and around Grand Bay, Mississippi (MS) and Alabama (AL) and used in models described by Smith and others (2024). Peat auger cores were described, photographed, and the thickness of the peat unit was measured with a measuring tape. Following collection, the distance from the core location to various geomorphic boundaries (e.g., upland, marsh shoreline, water edge, ... |
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Aerial images from a UAS survey of the debris flow at South Fork Campground, Sequoia National Park, CA
This portion of the data release presents aerial images of the debris flow at South Fork Campground in Sequoia National Park. The images were acquired during an uncrewed aerial systems (UAS) survey on 30 April 2024, conducted under authorization from the National Park Service. The imagery was acquired with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted to the UAS using a fixed mount, in an approximately nadir orientation. The camera was set to acquire images at 1 hertz, ... |
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Digital Surface Model (DSM) from UAS survey of the debris flow at South Fork Campground, Sequoia National Park, CA
This portion of the data release presents a high-resolution Digital Surface Models (DSM) of the debris flow at South Fork Campground in Sequoia National Park. The DSM has a resolution of 10 centimeters per pixel and was derived from structure-from-motion (SfM) photogrammetry using aerial imagery acquired during an uncrewed aerial systems (UAS) survey on 30 April 2024, conducted under authorization from the National Park Service. The raw imagery was acquired with a Ricoh GR II digital camera featuring a ... |
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Orthomosaic imagery from the UAS survey of the debris flow at South Fork Campground, Sequoia National Park, CA
This portion of the data release presents a high-resolution orthomosaic image of the debris flow at South Fork Campground in Sequoia National Park. The orthomosaic has a resolution of 3 centimeters per pixel and was derived from structure-from-motion (SfM) photogrammetry using aerial imagery acquired during an uncrewed aerial systems (UAS) survey on 30 April 2024, conducted under authorization from the National Park Service. The raw imagery was acquired with a Ricoh GR II digital camera featuring a global ... |
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Topographic point cloud from UAS survey of the debris flow at South Fork Campground, Sequoia National Park, CA
This portion of the data release presents a topographic point cloud of the debris flow at South Fork Campground in Sequoia National Park. The point cloud was derived from structure-from-motion (SfM) photogrammetry using aerial imagery acquired during an uncrewed aerial systems (UAS) survey on 30 April 2024, conducted under authorization from the National Park Service. The raw imagery was acquired with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed autonomous ... |
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Aerial video acquired during the UAS survey of the debris flow at South Fork Campground, Sequoia National Park, CA
This portion of the data release presents aerial video acquired during the uncrewed aerial systems (UAS) survey of the debris flow at South Fork Campground in Sequoia National Park, conducted under authorization from the National Park Service. The video shows low-altitude oblique and nadir perspectives of the lower 1.3 kilometers of the debris flow. The video is being included as part of the data release to provide additional context for the geohazards assessment of the area. |
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Ground control point locations and topographic GNSS measurements collected during the UAS survey of the debris flow at South Fork Campground, Sequoia National Park, CA
This portion of the data release presents topographic Global Navigation Satellite System (GNSS) measurements acquired during the UAS survey of the debris flow at South Fork Campground in Sequoia National Park. The data contain the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing, as well as topographic measurements collected using a backpack-mounted GNSS rover. For the GCPs, 23 temporary points consisting of a combination of small square tarps with ... |
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Overlapping seabed images collected at Big Pine Ledge coral reef, Florida, 2021
A total of 70,585 underwater images were collected at Big Pine Ledge, Florida, in July 2021, using the novel SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The SQUID-5 is a towed surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey (USGS), and records images in the Tagged Image File Format (.tif) to maintain the highest resolution and bit depth. Each image includes imagery header metadata (including, but ... |
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Overlapping seabed images collected at Big Pine Ledge coral reef, Florida, 2022
A total of 118,965 underwater images were collected at Big Pine Ledge, Florida, in July 2022, using the novel SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The SQUID-5 is a towed surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey (USGS), and records images in the Tagged Image File Format (.tif) to maintain the highest resolution and bit depth. Each image includes imagery header metadata (including, but ... |
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Overlapping seabed images collected at Looe Key coral reef, Florida, 2022
A total of 195,839 underwater images were collected at Looe Key, Florida, in July 2022, using the novel SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The SQUID-5 is a towed surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey (USGS), and records images in the Tagged Image File Format (.tif) to maintain the highest resolution and bit depth. Each image includes imagery header metadata (including, but not ... |
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Overlapping seabed images collected at Summerland Ledge coral reef, Florida, 2022
A total of 61,262 underwater images were collected at Summerland Ledge, Florida, in July 2022, using the novel SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The SQUID-5 is a towed surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey (USGS), and records images in the Tagged Image File Format (.tif) to maintain the highest resolution and bit depth. Each image includes imagery header metadata (including, but ... |
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SfM Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) – Field data from periodic surveys of the Florida Keys and other select shallow water environments
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) and Processes Impacting Seafloor Change and Ecosystem Services (PISCES) projects collect underwater imagery of coral reefs and other scientifically interesting, submerged environments using the novel SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. This sensor collects imagery with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three ... |
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Multibeam bathymetric data collected in the vicinity of Woods Hole, Massachusetts, during USGS Field Activity 2021-037-FA using a dual-head Teledyne Seabat T20-R multibeam echo sounder (32-bit GeoTIFF, UTM Zone 19N, WGS 84, GEOID 18 (MSL) Vertical Datum, 50cm resolution)
In November 2021, the U.S. Geological Survey collected high-resolution multibeam sonar data in the vicinity of Eel Pond, in Woods Hole, Massachusetts using a dual-head Teledyne Seabat T20-R multibeam echo sounder (MBES). The main objective of this survey was to evaluate new sonar system features prior to their use in future field activities. In addition to bathymetry and relative acoustic backscatter data, normalized acoustic backscatter data were also collected. Unlike relative backscatter data, normalized ... |
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RGB and thermal imagery, SfM products, and GPS data collected during UAS operations at Marsh Island, New Bedford, MA on July 2nd, 2024
Small Uncrewed Aircraft Systems (sUAS) were used to collect aerial remote sensing data over Marsh Island, a salt marsh restoration site along New Bedford Harbor, Massachusetts. Remediation of the site will involve direct hydrological and geochemical monitoring of the system alongside the UAS remote sensing data. On July 2nd, 2024, USGS personnel and interns collected natural (RGB) color and infrared (thermal) images and ground control points. These data were processed to produce a high resolution ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 17, 2018, from Jensen Beach, Florida
On July 17, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180717.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 07, 2018, from Jensen Beach, Florida
On August 07, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180807.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 22, 2019, from Jensen Beach, Florida
On May 22, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190522.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 23, 2019, from Jensen Beach, Florida
On May 23, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190523.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 27, 2019, from Jensen Beach, Florida
On June 27, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190627.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 28, 2019, from Jensen Beach, Florida
On June 28, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190628.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 25, 2019, from Jensen Beach, Florida
On July 25, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190725.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 26, 2019, from Jensen Beach, Florida
On July 26, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190726.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 20, 2021, from Juno Beach, Florida
On May 20, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210520.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 21, 2021, from Juno Beach, Florida
On May 21, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210521.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 24, 2021, from Juno Beach, Florida
On June 24, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210624.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 25, 2021, from Juno Beach, Florida
On June 25, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210625.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 15, 2021, from Juno Beach, Florida
On July 15, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210715.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 16, 2021, from Juno Beach, Florida
On July 16, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210716.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 05, 2021, from Juno Beach, Florida
On August 05, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210805.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 06, 2021, from Juno Beach, Florida
On August 06, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210806.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 26, 2022, from Juno Beach, Florida
On May 26, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220526.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 27, 2022, from Juno Beach, Florida
On May 27, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220527.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 16, 2022, from Juno Beach, Florida
On June 16, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220616.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 17, 2022, from Juno Beach, Florida
On June 17, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220617.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 21, 2022, from Juno Beach, Florida
On July 21, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220721.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 22, 2022, from Juno Beach, Florida
On July 22, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220722.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 20, 2019, from Jupiter Island, Florida
On May 20, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190520.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 21, 2019, from Jupiter Island, Florida
On May 21, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190521.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 25, 2019, from Jupiter Island, Florida
On June 25, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190625.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 26, 2019, from Jupiter Island, Florida
On June 26, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190626.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 23, 2019, from Jupiter Island, Florida
On July 23, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190723.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 24, 2019, from Jupiter Island, Florida
On July 24, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190724.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 27, 2019, from Jupiter Island, Florida
On August 27, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190827.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 28, 2019, from Jupiter Island, Florida
On August 28, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190828.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 16, 2020, from Jupiter Island, Florida
On June 16, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20200616.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 17, 2020, from Jupiter Island, Florida
On June 17, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20200617.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 18, 2021, from Jupiter Island, Florida
On May 18, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210518.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 19, 2021, from Jupiter Island, Florida
On May 19, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210519.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 22, 2021, from Jupiter Island, Florida
On June 22, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210622.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 23, 2021, from Jupiter Island, Florida
On June 23, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210623.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 13, 2021, from Jupiter Island, Florida
On July 13, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210713.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 14, 2021, from Jupiter Island, Florida
On July 14, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210714.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 03, 2021, from Jupiter Island, Florida
On August 03, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210803.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 04, 2021, from Jupiter Island, Florida
On August 04, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210804.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 24, 2022, from Jupiter Island, Florida
On May 24, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220524.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 25, 2022, from Jupiter Island, Florida
On May 25, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220525.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 14, 2022, from Jupiter Island, Florida
On June 14, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220614.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 15, 2022, from Jupiter Island, Florida
On June 15, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220615.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 19, 2022, from Jupiter Island, Florida
On July 19, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220719.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 20, 2022, from Jupiter Island, Florida
On July 20, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220720.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 09, 2018, from Melbourne Beach, Florida
On May 09, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180509.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 13, 2018, from Melbourne Beach, Florida
On June 13, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180613.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 18, 2018, from Melbourne Beach, Florida
On July 18, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180718.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 08, 2018, from Melbourne Beach, Florida
On August 08, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180808.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 30, 2019, from Melbourne Beach, Florida
On May 30, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190530.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 31, 2019, from Melbourne Beach, Florida
On May 31, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190531.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 18, 2019, from Melbourne Beach, Florida
On June 18, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190618.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 19, 2019, from Melbourne Beach, Florida
On June 19, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190619.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 16, 2019, from Melbourne Beach, Florida
On July 16, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190716.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 17, 2019, from Melbourne Beach, Florida
On July 17, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190717.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 20, 2019, from Melbourne Beach, Florida
On August 20, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190820.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 21, 2019, from Melbourne Beach, Florida
On August 21, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190821.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on September 10, 2019, from Melbourne Beach, Florida
On September 10, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190910.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on September 11, 2019, from Melbourne Beach, Florida
On September 11, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190911.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 25, 2020, from Melbourne Beach, Florida
On June 25, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20200625.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 26, 2020, from Melbourne Beach, Florida
On June 26, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20200626.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 25, 2021, from Melbourne Beach, Florida
On May 25, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210525.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 26, 2021, from Melbourne Beach, Florida
On May 26, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210526.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 15, 2021, from Melbourne Beach, Florida
On June 15, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210615.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 16, 2021, from Melbourne Beach, Florida
On June 16, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210616.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 20, 2021, from Melbourne Beach, Florida
On July 20, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210720.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 21, 2021, from Melbourne Beach, Florida
On July 21, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210721.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 10, 2021, from Melbourne Beach, Florida
On August 10, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210810.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 11, 2021, from Melbourne Beach, Florida
On August 11, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210811.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on September 08, 2021, from Melbourne Beach, Florida
On September 08, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210908.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on September 09, 2021, from Melbourne Beach, Florida
On September 09, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210909.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 19, 2022, from South Hutchinson Beach, Florida
On May 19, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220519.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 20, 2022, from South Hutchinson Beach, Florida
On May 20, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220520.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 22, 2022, from South Hutchinson Beach, Florida
On June 22, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220622.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 23, 2022, from South Hutchinson Beach, Florida
On June 23, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220623.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 24, 2022, from South Hutchinson Beach, Florida
On June 24, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220624.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 12, 2022, from South Hutchinson Beach, Florida
On July 12, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220712.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on July 13, 2022, from South Hutchinson Beach, Florida
On July 13, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220713.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 02, 2022, from South Hutchinson Beach, Florida
On August 02, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220802.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on August 03, 2022, from South Hutchinson Beach, Florida
On August 03, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220803.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on September 01, 2022, from South Hutchinson Beach, Florida
On September 01, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220901.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on May 08, 2018, from Jensen Beach, Florida
On May 08, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180508.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ... |
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Sea Turtle Nesting Decision Points and Cross-Shore Beach Profile Data Collected on June 12, 2018, from Jensen Beach, Florida
On June 12, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180612.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ... |
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Bathymetry from multibeam echosounder data collected offshore of Morro Bay, California
This part of USGS Data Series 781 (Golden, 2019) presents 2-m-resolution bathymetry data for the Offshore of Morro Bay, California, map area. Bathymetry data were collected by Fugro Pelagos in 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounder systems. The data were post-processed by the California State University Monterey Bay Seafloor Mapping Lab and the University of California Santa Cruz Center for Integrated Spatial Research. The bathymetry ... |
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High-resolution Chirp seismic-reflection data from USGS cruise 2018-641-FA, collected in south-central California in support of the Bureau of Ocean Energy Management (BOEM)-funded California Deepwater Investigations and Groundtruthing (Cal DIG I) offshore alternative energy project from 2018-08-29 to 2018-09-20
High-resolution Chirp seismic-reflection data were collected offshore south-central California as part of a geophysical survey aboard the NOAA Ship Rainier during two legs at sea, the first from 8/28/2018 to 9/7/2018 and the second from 9/10/2018 to 9/21/2018. The data were collected using an Edgetech 512i towfish with a 1-6 kHz sweep. Consistently high winds and rough seas prevented additional Chirp data collection and caused noisy data in some cases, especially during the second leg of the survey, which ... |
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High-resolution multi-channel seismic-reflection data from USGS cruise 2018-641-FA, collected in south-central California in support of the Bureau of Ocean Energy Management (BOEM)-funded California Deepwater Investigations and Groundtruthing (Cal DIG I) offshore alternative energy project from 2018-08-29 to 2018-09-20
Multi-channel seismic (MCS) reflection data were collected as part of a geophysical survey aboard the NOAA Ship Rainier during two legs at sea, the first from 8/28/2018 to 9/7/2018 and the second from 9/10/2018 to 9/21/2018. The data were collected using a SIG 2-Mille minisparker and a 64-channel streamer, although the majority of the survey was conducted using a 56-channel setup due to technical issues with one 8-channel section early on in the survey. The MCS data were processed to post-stack time ... |
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Structure-from-Motion bathymetric maps from the Florida Keys, 2019
Structure-from-Motion (SfM) bathymetric maps were created using seafloor images collected using the new 5-camera system SfM Quantitative Underwater Imaging Device with Five Cameras (SQUID-5). Images were collected during July 2019 by towing the SQUID-5 in 3 to 4 meters of water off of Islamorada in the Florida Keys during 3 days. The five cameras were synchronized together and with a survey-grade Global Positioning System (GPS). Images were collected over diverse benthic settings, including living and ... |
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Structure-from-Motion point clouds from the Florida Keys, 2019
Structure-from-Motion (SfM) point clouds were created from seafloor images collected using the new 5-camera system SfM Quantitative Underwater Imaging Device with Five Cameras (SQUID-5). Images were collected in July 2019 by towing the SQUID-5 in 3 to 4 meters of water off of Islamorada in the Florida Keys during 3 days. The five cameras were synchronized together and with a survey-grade Global Positioning System (GPS). Images were collected over diverse benthic settings, including living and senile reefs, ... |
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Acoustic backscatter data collected in 2008 offshore Tijuana River Estuary, California, during USGS Field Activity S-5-08-SC
These metadata describe acoustic backscatter data collected during a 2008 SWATHPlus-M survey offshore Tijuana River Estuary, California. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity number S-5-08-SC. The acoustic backscatter data are provided as a GeoTIFF image. |
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Bathymetry data collected in 2008 offshore Tijuana River Estuary, California during USGS Field Activity S-5-08-SC
These metadata describe bathymetry data collected during a 2008 SWATHPlus-M survey offshore Tijuana River Estuary, California. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity number S-5-08-SC. The bathymetry data are provided as GeoTIFF images in UTM, zone 11, NAD83 coordinates, vertically referenced to both NAVD88 and WGS84. A standard deviation grid is also provided. |
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Acoustic-backscatter data collected in 2016 offshore the Elwha River mouth, Washington, during USGS Field Activity 2016-605-FA
These metadata describe acoustic-backscatter data collected during a 2016 SWATHPlus-M survey offshore the Elwha River mouth, Strait of Juan de Fuca, Washington. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity number 2016-605-FA. The acoustic-backscatter data are provided as a GeoTIFF image in UTM, zone 10, NAD83 coordinates. |
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Bathymetry data collected in 2016 offshore the Elwha River mouth, Washington, during USGS Field Activity 2016-605-FA
These metadata describe bathymetry data collected during a 2016 SWATHPlus-M survey offshore the Elwha River mouth, Strait of Juan de Fuca, Washington. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity number 2016-605-FA. The bathymetry data are provided as a GeoTIFF image in UTM, zone 10, NAD83 coordinates, vertically referenced to NAVD88. |
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Bathymetry from multibeam echosounder data collected offshore of Point Estero, California
This part of USGS Data Series 781 (Golden, 2019) presents 2-m-resolution bathymetry data for the Offshore of Point Estero, California, map area. Bathymetry data were collected by Fugro Pelagos in 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounder systems. The data were post-processed by the California State University Monterey Bay Seafloor Mapping Lab and the University of California Santa Cruz Center for Integrated Spatial Research. The ... |
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Nearshore bathymetry data from the Elwha River delta, Washington, May 2011, collected from personal watercraft
This part of the data release presents bathymetry data from the Elwha River delta collected in May 2011 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, May 2011
This part of the data release presents topography data from the Elwha River delta collected in May 2011. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Acoustic Backscatter of the Sacramento River, from the Feather River to Knights Landing, California in February 2011
This part of the data release presents acoustic backscatter data collected on February 1, 2011, in the Sacramento River from the confluence of the Feather River to Knights Landing. The data were collected by the USGS Pacific Coastal and Marine Science Center (PCMSC) team with collaboration and funding from the U.S. Army Corp of Engineers. This project used interferometric sidescan sonar to characterize the riverbed and channel banks along a 12 mile reach of the Sacramento River, California (River Mile 79 ... |
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Standard deviation of the bathymetric DEM of the Sacramento River, from the Feather River to Knights Landing, California in February 2011
This part of the data release contains a grid of standard deviations of bathymetric soundings within each 0.5 m x 0.5 m grid cell. The bathymetry was collected on February 1, 2011, in the Sacramento River from the confluence of the Feather River to Knights Landing. The standard deviations represent one component of bathymetric uncertainty in the final digital elevation model (DEM), which is also available in this data release. The bathymetry data were collected by the USGS Pacific Coastal and Marine ... |
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Bathymetric DEM of the Sacramento River, from the Feather River to Knights Landing, California in February 2011
This part of the data release presents a digital elevation model (DEM) created from bathymetry data collected on February 1, 2011, in the Sacramento River from the confluence of the Feather River to Knights Landing. The data were collected by the USGS Pacific Coastal and Marine Science Center (PCMSC) team with collaboration and funding from the U.S. Army Corps of Engineers. This project used interferometric sidescan sonar to characterize the riverbed and channel banks along a 12 mile reach of the Sacramento ... |
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Nearshore bathymetry data from the Elwha River delta, Washington, August 2011, collected from personal watercraft
This part of the data release presents bathymetry data from the Elwha River delta collected in August 2011 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, August 2011
This part of the data release presents topography data from the Elwha River delta collected in August 2011. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Nearshore bathymetry data from northern Monterey Bay, California, October 2014
This part of the data release presents bathymetry data from northern Monterey Bay, California collected in October 2014 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from northern Monterey Bay, California, October 2014
This part of the data release presents topography data from northern Monterey Bay, California collected in October 2014. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. |
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Nearshore bathymetry data from northern Monterey Bay, California, March 2015
This part of the data release presents bathymetry data from northern Monterey Bay, California collected in March 2015 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Terrestrial lidar data from northern Monterey Bay, California, March 2015
This part of the data release presents topography data from northern Monterey Bay, California collected in March 2015 with a terrestrial lidar scanner. |
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Topography data from northern Monterey Bay, California, March 2015
This part of the data release presents topography data from northern Monterey Bay, California collected in March 2015. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. |
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Nearshore bathymetry data from northern Monterey Bay, California, September and October 2015
This part of the data release presents bathymetry data from northern Monterey Bay, California collected in September and October 2015 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Terrestrial lidar data from northern Monterey Bay, California, September 2015
This part of the data release presents topography data from northern Monterey Bay, California collected in September 2015 with a terrestrial lidar scanner. |
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Topography data from northern Monterey Bay, California, September and October 2015
This part of the data release presents topography data from northern Monterey Bay, California collected in September and October 2015. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. |
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Nearshore bathymetry data from northern Monterey Bay, California, March 2016
This part of the data release presents bathymetry data from northern Monterey Bay, California collected in March 2016 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Terrestrial lidar data from northern Monterey Bay, California, March 2016
This part of the data release presents topography data from northern Monterey Bay, California collected in March 2016 with a terrestrial lidar scanner. |
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Topography data from northern Monterey Bay, California, March 2016
This part of the data release presents topography data from northern Monterey Bay, California collected in March 2016. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. |
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Terrestrial lidar data from northern Monterey Bay, California, October 2016
This part of the data release presents topography data from northern Monterey Bay, California collected in October 2016 with a terrestrial lidar scanner. |
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Nearshore bathymetry data from northern Monterey Bay, California, September 2016
This part of the data release presents bathymetry data from northern Monterey Bay, California collected in September 2016 using a personal watercraft (PWC) and small boat. The survey vessels were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from northern Monterey Bay, California, September 2016
This part of the data release presents topography data from northern Monterey Bay, California collected in September 2016. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. |
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Nearshore bathymetry data from northern Monterey Bay, California, March 2017
This part of the data release presents bathymetry data from northern Monterey Bay, California collected in March 2017 using personal watercraft (PWC). The survey vessels were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Terrestrial lidar data from northern Monterey Bay, California, March 2017
This part of the data release presents topography data from northern Monterey Bay, California collected in March 2017 with a terrestrial lidar scanner. |
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Topography data from northern Monterey Bay, California, March 2017
This part of the data release presents topography data from northern Monterey Bay, California collected in March 2017. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. |
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Nearshore bathymetry data from northern Monterey Bay, California, September 2017
This part of the data release presents bathymetry data from northern Monterey Bay, California collected in September 2017 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Terrestrial lidar data from northern Monterey Bay, California, September 2017
This part of the data release presents topography data from northern Monterey Bay, California collected in September 2017 with a terrestrial lidar scanner. |
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Topography data from northern Monterey Bay, California, September 2017
This part of the data release presents topography data from northern Monterey Bay, California collected in September 2017. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. |
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Nearshore bathymetry data from the Elwha River delta, Washington, April 2014, collected from personal watercraft
This part of the data release presents bathymetry data from the Elwha River delta collected in April 2014 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, April 2014
This part of the data release presents topography data from the Elwha River delta collected in April 2014. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Acoustic backscatter data collected in 2007 from the San Miguel Passage in the Channel Islands, California
This portion of the data release presents acoustic backscatter data from the San Miguel Passage, in the Channel Islands, California. The data were collected in August 2007 by the U.S. Geological Survey, Pacific Coastal and Marine Science Center (USGS, PCMSC) using a 234.5 kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonar mounted on the NOAA, Channel Islands National Marine Sanctuary R/V Shearwater as part of the research cruise S-2-07-SC. Data were collected in water depths up to 89 meters. ... |
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Bathymetry data collected in 2007 from the San Miguel Passage in the Channel Islands, California
This portion of the data release presents bathymetry data from the San Miguel Passage, in the Channel Islands, California. Bathymetry data were collected in the San Miguel Passage, Channel Islands, California in August 2007 by the U.S. Geological Survey, Pacific Coastal and Marine Science Center (USGS, PCMSC). Collection was accomplished using a 234.5 kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonar mounted on the NOAA, Channel Islands National Marine Sanctuary R/V Shearwater as part of the ... |
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Nearshore bathymetry data from the Elwha River delta, Washington, May 2012, collected from personal watercraft
This part of the data release presents bathymetry data from the Elwha River delta collected in May 2012 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, May 2012
This part of the data release presents topography data from the Elwha River delta collected in May 2012. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Nearshore bathymetry data from the Elwha River delta, Washington, September 2010
This part of the data release presents bathymetry data from the Elwha River delta collected in September 2010 using a personal watercraft (PWC) and a small boat. Both survey vessels were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, September 2010
This part of the data release presents topography data from the Elwha River delta collected in September 2010. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Nearshore bathymetry data from the Elwha River delta, Washington, July 2016, collected from kayak
This part of the data release presents bathymetry data from the Elwha River delta collected in July 2016 using a kayak. The kayak was equipped with a single-beam echosounder and a survey-grade global navigation satellite system (GNSS) receiver. |
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Nearshore bathymetry data from the Elwha River delta, Washington, July 2016, collected from personal watercraft
This part of the data release presents bathymetry data from the Elwha River delta collected in July 2016 using two personal watercraft (PWCs). The PWCs were equipped with single beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, July 2016
This part of the data release presents topography data from the Elwha River delta collected in July 2016. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Multichannel sparker seismic-reflection data between Cross Sound and Dixon Entrance, offshore southeastern Alaska, collected from 2016-05-17 to 2016-06-12 during field activity 2016-625-FA
Multichannel sparker (MCS) seismic-reflection data were collected along the Queen Charlotte-Fairweather Fault between Cross Sound and Dixon Entrance, offshore southeastern Alaska from 2016-05-17 to 2016-06-12. Data were collected aboard the Alaska Department of Fish and Game R/V Medeia, and recorded using a 32 channel GeoEel digital streamer, an Applied Acoustics power supply, and a SIG SLP 790 Sparker Electrode. MCS profiles were collected coincident with multibeam data collected at higher survey speeds (5 ... |
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Multibeam bathymetry data between Cross Sound and Dixon Entrance, offshore southeastern Alaska, collected from 2016-05-17 to 2016-06-12 during field activity 2016-625-FA
Multibeam bathymetry data were collected along the Queen Charlotte-Fairweather Fault between Icy Point and Dixon Entrance, offshore southeastern Alaska from 2016-05-17 to 2016-06-12. Data were collected aboard the Alaska Department of Fish and Game R/V Medeia using a Reson SeaBat 7160 multibeam echosounder, Reson 7k Control Center, and HYPACK. This data release contains approximately 4,600 square kilometers of multibeam bathymetry and backscatter data, organized into zip files for each Julian Day of the ... |
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Nearshore bathymetry data from the Elwha River delta, Washington, September 2014, collected from personal watercraft
This part of the data release presents bathymetry data from the Elwha River delta collected in September 2014 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, September 2014
This part of the data release presents topography data from the Elwha River delta collected in September 2014. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Nearshore bathymetry data from the Elwha River delta, Washington, August 2012
This part of the data release presents bathymetry data from the Elwha River delta collected in August 2012 using a personal watercraft (PWC) and the R/V Frontier. Both survey vessels were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, August 2012
This part of the data release presents topography data from the Elwha River delta collected in August 2012. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Nearshore bathymetry data from the Elwha River delta, Washington, March 2013, collected from personal watercraft
This part of the data release presents bathymetry data from the Elwha River delta collected in March 2013 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. |
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Topography data from the Elwha River delta, Washington, March 2013
This part of the data release presents topography data from the Elwha River delta collected in March 2013. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks. |
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Topographic measurements of Little Holland Tract, Sacramento-San Joaquin Delta, California, 2015, using backpack GPS
Topographic data were collected by the U.S. Geological Survey (USGS) in 2015 for Little Holland Tract in the Sacramento-San Joaquin River Delta, California. The data were collected on foot using a global positioning system (GPS) backpack platform that consisted of survey-grade Trimble R10 and R7 global navigation satellite system (GNSS) receivers with Zephyr 2 antennas. Orthometric elevations relative to NAVD88 were computed using the National Geodetic Survey Geoid12a, and the final data were projected in ... |
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Bathymetric measurements of Little Holland Tract, Sacramento-San Joaquin Delta, California, 2015, from personal watercraft
Bathymetric data were collected by the U.S. Geological Survey (USGS) in 2015 for Little Holland Tract in the Sacramento-San Joaquin River Delta, California. The data were collected using a personal watercraft (PWC) platform that consisted of Trimble R7 Global Navigation Satellite System (GNSS) receivers with Zephyr 2 antennas, combined with Odom Echotrac CV-100 single-beam echosounders and 200 kHz transducers. Data was post-processed to remove spurious data points. Raw depths w |