Inferred hydrodynamic residence time in salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey
As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ... |
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Change in salinity in salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy
As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ... |
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Change in salinity exposure of salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy
As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ... |
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Change in suspended sediment concentration over the salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy
As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ... |
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Shoreline change rates in salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey
Monitoring shoreline change is of interest in many coastal areas because it enables quantification of land loss over time. Evolution of shoreline position is determined by the balance between erosion and accretion along the coast. In the case of salt marshes, erosion along the water boundary causes a loss of ecosystem services, such as habitat provision, carbon storage, and wave attenuation. In terms of vulnerability, higher shoreline erosion rates indicate higher vulnerability. This dataset ... |
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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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Conceptual salt marsh units for wetland synthesis: Edwin B. Forsythe National Wildlife Refuge, New Jersey
The salt marsh complex of the Edwin B. Forsythe National Wildlife Refuge (EBFNWR), which spans over Great Bay, Little Egg Harbor, and Barnegat Bay (New Jersey, USA), was delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location is used to determine the ridge lines that separate each marsh unit while the surface slope is used to automatically assign each unit a drainage point, where water is expected to drain ... |
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Surficial and Downcore Sedimentological and Foraminiferal Microfossil Data from St. Marks National Wildlife Refuge, Florida
In October 2019, five marsh push cores (core names appended with M for marsh push core) and 18 surface sediment samples (top 1 cm of sediment) were collected from the estuary (sample name appended G for PONAR grab) near the mouth of the St. Marks River and some of the surrounding marshes (sample name appended with S for surface), along with elevation transects and peat augers (sample name appended with R or R50, depending on length, for Russian peat auger). The purpose of the study was to 1) evaluate peat ... |
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Lifespan of Massachusetts salt marsh units
Lifespan of salt marshes in Massachusetts (MA) are calculated using conceptual marsh units defined by Ackerman and others (2022). The lifespan calculation is based on estimated sediment supply and sea-level rise (SLR) predictions after Ganju and others (2020). Sea level predictions are local estimates which correspond to the 0.3, 0.5, and 1.0 meter increase in Global Mean Sea Level (GMSL) scenarios by 2100 from Sweet and others (2022). The U.S. Geological Survey has been expanding national assessment of ... |
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Lifespan of Chesapeake Bay salt marsh units
Lifespan distribution in the Chesapeake Bay (CB) salt marsh complex is presented in terms of lifespan of conceptual marsh units defined by Ackerman and others (2022). The lifespan calculation is based on estimated sediment supply and sea-level rise (SLR) predictions after Ganju and others (2020). Sea level predictions are present day estimates at the prescribed rate of SLR, which correspond to the 0.3, 0.5, and 1.0 meter increase in Global Mean Sea Level (GMSL) scenarios by 2100 from Sweet and others (2022) ... |
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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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Lifespan of marsh units in New York salt marshes
Lifespan of salt marshes in New York are calculated using conceptual marsh units defined by Defne and Ganju (2018) and Welk and others (2019, 2020a, 2020b, 2020c). The lifespan calculation is based on estimated sediment supply and sea-level rise (SLR) predictions after Ganju and others (2020). Sea level predictions are local estimates which correspond to the 0.3, 0.5, and 1.0 meter increase in Global Mean Sea Level (GMSL) scenarios by 2100 from Sweet and others (2022). The U.S. Geological Survey has been ... |
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Exposure potential of salt marsh units in Edwin B. Forsythe National Wildlife Refuge to environmental health stressors (polygon shapefile)
Natural and anthropogenic contaminants, pathogens, and viruses are found in soils and sediments throughout the United States. Enhanced dispersion and concentration of these environmental health stressors in coastal regions can result from sea level rise and storm-derived disturbances. The combination of existing environmental health stressors and those mobilized by natural or anthropogenic disasters could adversely impact the health and resilience of coastal communities and ecosystems. This dataset displays ... |
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Raster image of exposure potential to environmental health stressors in Edwin B. Forsythe National Wildlife Refuge (32-bit GeoTIFF)
Natural and anthropogenic contaminants, pathogens, and viruses are found in soils and sediments throughout the United States. Enhanced dispersion and concentration of these environmental health stressors in coastal regions can result from sea level rise and storm-derived disturbances. The combination of existing environmental health stressors and those mobilized by natural or anthropogenic disasters could adversely impact the health and resilience of coastal communities and ecosystems. This dataset displays ... |
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Elevation of salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey
Elevation distribution in the Edwin B. Forsythe National Wildlife Refuge (EBFNWR), which spans over Great Bay, Little Egg Harbor, and Barnegat Bay in New Jersey, USA is given in terms of mean elevation of conceptual marsh units defined by Defne and Ganju (2016). The elevation data is based on the 1-meter resampled 1/9 arc-second resolution USGS National Elevation Data. As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and ... |
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Raster image of mean tidal range in the Edwin B. Forsythe National Wildlife Refuge, New Jersey (32-bit GeoTIFF)
Biomass production is positively correlated with mean tidal range in salt marshes along the Atlantic coast of the United States of America. Recent studies support the idea that enhanced stability of the marshes can be attributed to increased vegetative growth due to increased tidal range. This dataset displays the spatial variation mean tidal range (i.e. Mean Range of Tides, MN) in the Edwin B. Forsythe National Wildlife Refuge (EBFNWR), which spans over Great Bay, Little Egg Harbor, and Barnegat Bay in New ... |
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Mean tidal range in salt marsh units of Edwin B. Forsythe National Wildlife Refuge, New Jersey (polygon shapefile)
Biomass production is positively correlated with mean tidal range in salt marshes along the Atlantic coast of the United States of America. Recent studies support the idea that enhanced stability of the marshes can be attributed to increased vegetative growth due to increased tidal range. This dataset displays the spatial variation mean tidal range (i.e. Mean Range of Tides, MN) in the Edwin B. Forsythe National Wildlife Refuge (EBFNWR), which spans over Great Bay, Little Egg Harbor, and Barnegat Bay in New ... |
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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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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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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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2023-310-FA_Oahu_Polecam_Imagery: High-resolution Geophysical and Imagery Data Collected in May 2023 Near Fort Hase, Marine Corps Base Hawaii
Underwater images totaling 78,924 in number were collected offshore Fort Hase, Marine Corps Base Hawaii (MCBH) and Coconut Island, Oahu, Hawaii, during May 2023, using the Polecam system developed by the U.S. Geological Survey (USGS). The Polecam system is a single downward-looking underwater Teledyne FLIR camera with a Computar V1228-MPY lens and with a rigidly-attached Global Navigation Satellite System (GNSS) antenna mounted above and forward of the camera's central axis. The Polecam system captured ... |
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Suggested Polygon of the Coral Essential Fish Habitat Associated with Pulley Ridge
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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Suggested Polygon of the Habitat Area of Particular Concern Associated with Pulley Ridge
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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Approximate Bounds of the Zooxanthellate Coral-Rich Area Associated with Pulley Ridge
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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Late Pleistocene coral ages and elevations from south Florida
This data release compiles Uranium-series (U-series) data and descriptive collection information (such as sample/core identifier, location, elevation, etc.) for late Pleistocene coral subsamples from coral reef cores previously collected throughout the Florida Keys (Florida) by U.S. Geological Survey (USGS) researchers. The samples were collected under scientific research permits from the Florida Keys National Marine Sanctuary (FKNMS) and U.S. National Park Service (NPS) and all samples are currently ... |
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Late Holocene and Living Coral Composition of Pompano Ridge, FL
Pompano Ridge is a coral reef located on the southeast Florida nearshore ridge complex, ~600 meters (m) off the coast of northern Broward County in southeast Florida (26°13 North, 80°5 West). This data release compiles data collected on the late Holocene and living coral composition of Pompano Ridge. The data are described in detail in Modys and others (2024). The samples were collected under Scientific Activity Licenses (SAL) from the Florida Fish and Wildlife Conservation Commission (SAL-18-1650(A) ... |
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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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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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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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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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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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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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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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Underwater temperature data collected from off-shore coral reefs of the Florida Keys, U.S.A. (Version 3)
The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ... |
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Underwater temperature data collected from off-shore coral reefs of the Florida Keys, U.S.A. (Version 4)
The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ... |
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Underwater temperature data collected from off-shore coral reefs of the Florida Keys, U.S.A. (Version 5)
The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ... |
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Underwater temperature data collected from off-shore coral reefs of the Florida Keys, U.S.A. (Version 6)
The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ... |
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Underwater temperature on off-shore coral reefs of the Florida Keys, U.S.A. (Version 7)
The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ... |
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Conductivity, temperature, and depth (CTD) data from nearshore coral reef locations along the west coast of Hawaii Island (2010-2014)
Conductivity-Temperature-Depth (CTD) profile data were collected along transects across study areas of west and east Hawaii Island between 2010 and 2014. Measurements were made over a range of tide and weather conditions and help characterize the spatial extent and variability in estuarine conditions across the reef when grouped by 1 to 2-hour survey period or by season. Sites of cold and warm groundwater discharge along east Hawaii were characterized for comparison. |
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Surface-water temperature, salinity, pH, dissolved oxygen, and turbidity data from nearshore coral reef locations along the west coast of Hawaii Island (2010-2013)
Spatial measurements of water temperature, specific conductance, salinity, pH, dissolved oxygen, and turbidity between 0.25 and 0.50 m water depth were collected every 10-seconds along and across shore at 12 principal study areas along west and east Hawaii Island. Measurements were made between 2010 and 2013 during different seasons and tide states over the course of 1.0 to 2.5 hours to evaluate the spatial and temporal extent of water properties that influence coral reef health and coral reef habitat ... |
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Water level, temperature, and salinity time-series data from nearshore coral reef locations along the west coast of Hawaii Island (2010-2011)
Time-series data of water level, water temperature, and salinity were collected at 10 locations along west Hawaii Island between 2010 and 2011 in nearshore coral reef settings. Conductivity-temperature-depth sensors were attached to fossil limestone, rock, or dead coral within otherwise healthy coral reef settings spanning water depths of 8 to 23 ft. Continuous measurements were made every 10 or 20 minutes. |
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Water temperature time-series data from nearshore coral reef and anchialine pool locations along the west coast of Hawaii Island (2010-2013)
Time-series data of water temperature were collected at 33 locations along the west coast of the Island of Hawaii, including within Kaloko-Honokohau National Historical Park (KAHO), and Puu o Honaunau National Historical Park (PUHO) between 2010 and 2013 in nearshore coral reef and anchialine pool settings. Temperature sensors were attached to fossil limestone, rock or dead coral within otherwise healthy coral reef settings spanning water depths of 0.1 to 8.84 m (0.3 to 29.0 ft). Continuous measurements ... |
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Coral bleaching data by site, West Hawaii, 2010-2011
Observations of bleached coral were documented by scuba divers along pre-determined transects and are presented here in comma-separated format. Included in the table are coral species observed, colony size, size of bleached area on colony, and seawater temperature. |
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Coral disease data by transect, West Hawaii, 2011
Observations of coral disease and health indicators were documented by scuba divers along pre-determined transects and are presented here in comma-separated format. Included in the table are coral species observed, colony size, types and number of indicators observed, and a size range of indicators observed. |
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Coral species and size data by transect, West Hawaii, 2011
Observations of coral species and size were documented by scuba divers along pre-determined transects and are presented here in comma-separated format. |
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Coral Point Count (CPCe) summary data by transect, West Hawaii, 2010-2011
Coral Point Count with Excel extensions (CPCe; Kohler and Gill, 2006) was used to help calculate percent of coral cover or other benthic substrates from a randomly selected subset of seafloor photographs collected on the west Hawaii Island coast. |
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Seafloor photographs and location data, West Hawaii, 2010-2011
Seafloor photographs were collected by SCUBA divers along pre-determined transects using an underwater digital camera following benthic survey protocols developed by the National Park Service (NPS) at Kaloko-Honokohau National Historical Park (Marrack and others, 2014; Weijerman and others, 2014) and modeled after the U.S. Geological Survey (USGS) and NPS coral reef survey protocols (Rogers and others, 2001; Brown and others, 2011). This dataset includes seafloor photographs in jpg format, the locations of ... |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). These four image mosaics have 1.0 meter-per-pixel resolution, and intermittently cover approximately 53 km (33 mi) of shallow, coastal waters along the west, Kona coast, of the island of Hawai'i, including (from north to south) the Kawaihae, Waikoloa, Kukio, and Kailua-Kona areas. ... |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) of the Napili-Honokowai area along the northwest coast of Maui. The area is downloadable as a zip file (napili_honokowai_1m.zip) and includes a high-resolution (1.0 meter per pixel) digital image mosaic, as well as a lower-resolution 'browse' image and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains digital image mosaics along the south coast of Moloka'i. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Pala'au, Umipa'a, Kaunakakai, Kamiloloa, Kawela, Kamalo, and Kalaeloa, were generated from 1:10K aerial photography, and are presented in one zip file (molokai_1ft.zip) that also contains lower-resolution 'browse' graphics of each image-mosaic area, as well as associated metadata. Digital mosaics at 1-meter resolution, including the ... |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains digital image mosaics along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography and are presented in one zip file (oahu_1ft.zip) that also contains lower-resolution 'browse' graphics of each image mosaic area, as well as associated metadata. All of the digital image areas (from Waikiki to Portlock) were ... |
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Digital image mosaic of the nearshore coastal waters of Diamond Head on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Diamond Head area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Haleolono Point on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Haleolono Point area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of Kailua-Kona on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic with 1.0 meter-per-pixel resolution of the Kailua-Kona area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial ... |
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Digital image mosaics of the nearshore coastal waters of Kalaeloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kalaeloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kamalo on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kamalo on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kamiloloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kamiloloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kaunakakai on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kaunakakai on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of Kawaihae on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic of the Kawaihae area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded ... |
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Digital image mosaic of the nearshore coastal waters of Kawela on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kawela area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kawela on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kawela area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of Kukio on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic of the Kukio area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded ... |
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Digital image mosaic of the nearshore coastal waters of La'au Point on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the La'au Point area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Maunalua Bay on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Maunalua Bay area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of the Napili-Honokowai area on the northwest coast of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic of the Napili-Honokowai area on the northwest coast of Maui. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). The image mosaic has been geometrically corrected using lidar data. Also available is a lower-resolution 'browse' image, and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Pala'au on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Pala'au area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Pala'au on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Pala'au area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Portlock area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Puko'o on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Puko'o area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital shaded-relief image mosaic of the nearshore coastal waters of southcentral Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southcentral Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief ... |
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Digital shaded-relief image mosaic of the nearshore coastal waters southeast Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southeast Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief image. ... |
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Digital shaded-relief image mosaic of the nearshore coastal waters southwest Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southwest Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief image. ... |
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Digital image mosaic of the nearshore coastal waters of Umipa'a on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Umipa'a area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Waiakane on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Waiakane area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Wai'alae on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Wai'alae area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of Waikiki on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Waikiki area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters from Waikiki to Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic from Waikiki to Portlock along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography. These five image mosaics were then combined into one larger mosaic and resampled to 1-meter resolution. |
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Shaded-relief image mosaic of the nearshore coastal waters from Waikiki to Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic from Waikiki to Portlock along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography. These five image mosaics were then combined into one larger mosaic, resampled to 1-meter resolution, and merged with lidar bathymetry data to produce the shaded-relief image. |
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Digital image mosaics of the nearshore coastal waters of Waikoloa on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic of the Waikoloa area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded ... |
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Flooding extent polygons for modelled wave-driven water levels in Florida with and without projected coral reef degradation
This data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). There are 12 associated flood mask shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the degradation scenarios (Mean Elevation and Mean Erosion). |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the State of Florida before and after Hurricanes Irma and Maria due to the storms' damage to the coral reefs
This part of the data release presents projected flooding extent polygon shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). There are eight associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the pre-storm scenario (base) and the post-storm scenarios. |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the Commonwealth of Puerto Rico before and after Hurricanes Irma and Maria due to the storms' damage to the coral reefs
This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for Commonwealth of Puerto Rico. There are eight associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the pre-storm scenario (base) and the post-storm scenarios. |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for American Samoa (the islands of Tutuila, Ofu-Olosega, and Tau)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for American Samoa (the islands of Tutuila, Ofu-Olosega, and Tau). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding depth point data ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the Commonwealth of the Northern Mariana Islands (the islands of Saipan and Tinian)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for Commonwealth of the Northern Mariana Islands (the islands of Saipan and Tinian). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the State Florida (the Florida Peninsula and the Florida Keys)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding depth point data ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the Territory of Guam
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the Territory of Guam. There are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding depth point data are also presented as a comma-separated value (.csv) ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the State of Hawaii (the islands of Hawaii, Kahoolawe, Kauai, Lanai, Maui, Molokai, Niihau, and Oahu)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the State of Hawaii (the islands of Hawaii, Kahoolawe, Kauai, Lanai, Maui, Molokai, Niihau, and Oahu). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the Territory of Puerto Rico (the islands of Culebra, Puerto Rico, and Vieques)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the Territory of Puerto Rico (the islands of Culebra, Puerto Rico, and Vieques). For each island there are 8 associated flood mask and flood depth shapefiles: one for each four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding ... |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the States of Hawaii and Florida, the Territories of Guam, American Samoa, Puerto Rico, and the U.S. Virgin Islands, and the Commonwealth of the Northern Mariana Islands
This data release provides flooding extent polygons (flood masks) and depth values (flood points) based on wave-driven total water levels for 22 locations within the States of Hawaii and Florida, the Territories of Guam, American Samoa, Puerto Rico, and the U.S. Virgin Islands, and the Commonwealth of the Northern Mariana Islands. For each of the 22 locations there are eight associated flood mask polygons and flood depth point files: one for each four nearshore wave energy return periods (rp; 10-, 50-, 100- ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the Territory of the U.S. Virgin Islands (the islands of Saint Croix, Saint John, and Saint Thomas)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the Territory of the U.S. Virgin Islands (the islands of Saint Croix, Saint John, and Saint Thomas). For each island there are 8 associated flood mask and flood depth shapefiles: one for each four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of ... |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the State of Florida for current and potentially restored coral reefs
This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). There are 16 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the restoration scenarios (structural_25, structural_05, and ecological_25). |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the Commonwealth of Puerto Rico for current and potentially restored coral reefs
This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the Commonwealth of Puerto Rico. There are 16 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the restoration scenarios (structural_25, structural_05, and ecological_25). |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the Territory of the U.S. Virgin Islands for current and potentially restored coral reefs
This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the Territory of the U.S. Virgin Islands. There are 16 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the restoration scenarios (structural_25, structural_05, and ecological_25). |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). These four image mosaics have 1.0 meter-per-pixel resolution, and intermittently cover approximately 53 km (33 mi) of shallow, coastal waters along the west, Kona coast, of the island of Hawai'i, including (from north to south) the Kawaihae, Waikoloa, Kukio, and Kailua-Kona areas. ... |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) of the Napili-Honokowai area along the northwest coast of Maui. The area is downloadable as a zip file (napili_honokowai_1m.zip) and includes a high-resolution (1.0 meter per pixel) digital image mosaic, as well as a lower-resolution 'browse' image and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains digital image mosaics along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography and are presented in one zip file (oahu_1ft.zip) that also contains lower-resolution 'browse' graphics of each image mosaic area, as well as associated metadata. All of the digital image areas (from Waikiki to Portlock) were ... |
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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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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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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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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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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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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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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 ... |
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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 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 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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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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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) ... |
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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 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—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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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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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 ... |
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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 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-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) ... |
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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) ... |
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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 ... |
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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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Time-series coral-cover data from Hawaii, Florida, Mo'orea, and the Virgin Islands
Coral reefs around the world have degraded over the last half-century as evidenced by loss of live coral cover. This ubiquitous observation led to the establishment of long-term, ecological monitoring programs in several regions with sizable coral-reef resources. As part of the U.S. Geological Survey (USGS) John Wesley Powell Center for Analysis and Synthesis working group "Local-scale ecosystem resilience amid global-scale ocean change: the coral reef example," scientists gathered resultant data from four ... |
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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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Grain-Size and Data Analysis Results from Sediment Samples Collected at Crocker Reef, Florida, Between 2017 and 2019
Sediment samples were collected from undisturbed sections of the seafloor around Crocker Reef, Florida. Crocker Reef is a barrier reef located in the northern portion of the Florida Reef Tract that has been classified by Kellogg and others (2015) as a senile or dead reef consisting of areas of sand and rubble with only scattered stony coral colonies. Samples were collected from November 2017 to April 2019 to help ground truth coincident instrumentation deployed during the same time interval, which was used ... |
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Descriptive core logs, high-resolution images and derived data for Holocene reef cores collected from 1976 to 2017 along the Florida Keys reef tract
The USGS core archive (Reich and others, 2009; https://olga.er.usgs.gov/coreviewer/) houses an extensive collection of coral-reef cores that USGS researchers have collected from throughout the Florida Keys reef tract (FKRT). USGS scientists have compiled all available data on the 71 core records that recovered Holocene reef framework, including radiometric ages (radiocarbon and U-series), data on reef development (timing of reef initiation and senescence, reef accretion, and reef thickness) and geospatial ... |
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Local radiocarbon reservoir age (Delta-R) variability from the nearshore and open-ocean environments of the Florida Keys reef tract during the Holocene and associated U-series and radiocarbon data (Marine13 Radiocarbon Calibration Curve)
Holocene-aged corals from reef cores collected throughout the Florida Keys reef tract (FKRT) were dated using a combination of U-series and radiocarbon techniques to quantify the millennial-scale variability in the local radiocarbon reservoir age (ΔR) of the shallow water environments of south Florida. ΔR provides a measure of the deviation of local radiocarbon concentrations of marine environments from the global average and can be used as a tracer of oceanic circulation and local hydrology. U.S. ... |
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Local radiocarbon reservoir age (ΔR) variability from the nearshore and open-ocean environments of the Florida Keys reef tract during the Holocene and associated U-series and radiocarbon data (Marine20 Radiocarbon Calibration Curve)
68 Holocene-aged corals from reef cores collected throughout the Florida Keys reef tract (FKRT) were dated using a combination of U-series and radiocarbon techniques to quantify the millennial-scale variability in the local radiocarbon reservoir age (ΔR) of the shallow water environments of south Florida. ΔR provides a measure of the deviation of local radiocarbon concentrations of marine environments from the global average and can be used as a tracer of oceanic circulation and local hydrology. U.S. ... |
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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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The absolute and relative composition of Holocene reef cores collected between 1976 and 2017 from the Florida Keys reef tract
This data release provides a summary of the absolute percent composition of all recovered material and relative percent composition of coral taxa in the Holocene-aged intervals of 61 coral-reef cores collected throughout the Florida Keys reef tract (FKRT) housed in the USGS Core Archive in St. Petersburg, FL (Estimated ages for distinct depths within each core are also provided; those ages were either measured by radiometric dating of coral samples at those depths or estimated by linear interpolation ... |
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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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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 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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Microbial and environmental dataset from Crocker Reef, Florida Keys, 2014-2015
Crocker Reef was the site of an integrated reefscape characterization effort focused on calcification and related biogeochemical processes as part of the USGS Coral Reef Ecosystem Study (CREST) project. This effort included two intensive seasonal sampling trips to capture summer (July 8 to 17, 2014) and winter (January 29 to February 5, 2015) conditions. This data release represents water column microbial and environmental data collected for use as metadata in future publications examining reef metabolic ... |
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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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Radiometric ages and descriptive data for Holocene corals from southeast Florida
This data release compiles descriptive information (location, water depth, etc.) and radiometric ages from corals collected through the Southeast Florida Continental Reef Tract (SFCRT; Figure 1). The database includes data from studies published between 1977 and 2015 as well as previously unpublished data. The samples were originally collected using coral-reef coring or other geologic sampling methods. Many of the samples are presently stored in the U.S. Geological Survey (USGS) Core Archive at the St. ... |
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South Florida Holocene coral sea-level database for samples collected from 1977 to 2017
Holocene-aged coral samples from the south Florida region were extensively characterized to create a new database of verified sea-level data. The samples were originally collected using coral-reef coring or other geologic sampling methods and were obtained by various researchers from published studies spanning the interval of 1977 to 2017. Many of these samples are presently stored in the U.S. Geological Survey (USGS) Core Archive at the St. Petersburg Coastal and Marine Science Center in St. Petersburg, ... |
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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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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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Continuous Water Level, Salinity, and Temperature Data from Creeks and Monitoring Wells in Natural and Restored Wetlands on Cape Cod, Massachusetts, 2019
Environmental parameters affecting plant productivity and microbial respiration, such as water level, salinity, and groundwater temperature included in these datasets, are key components of wetland carbon cycling, carbon storage, and capacity to maintain elevation. Data were collected to (1) provide background data to evaluate potential differences in water level and carbon flux between wetland sites with differing elevation and tidal inundation and (2) facilitate applications of Blue Carbon projects in ... |
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Exposure potential of marsh units to environmental health stressors 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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Location and radiochemical data from sediment cores collected on Deer Island, Mississippi
In December 2021, four sediment push cores (core names appended with 'M' for marsh push core) and peat augers (core names appended with 'R' for Russian peat auger) were collected from the marshes of Deer Island, Mississippi during U.S. Geological Survey (USGS) field activity number (FAN) 2021-351-FA. Select intervals from the manual push cores were analyzed for determination of lead-210 activities via alpha spectroscopy for development of accumulation rates using standard model methods. Twenty percent of ... |
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Static chamber gas fluxes and carbon and nitrogen isotope content of age-dated sediment cores from a Phragmites wetland in Sage Lot Pond, Massachusetts, 2013-2015
Coastal wetlands are major global carbon sinks; however, quantification of carbon flux can be difficult in these heterogeneous and dynamic ecosystems. To characterize spatial and temporal variability in a New England salt marsh, static chamber measurements of greenhouse gas (GHG) fluxes were compared among major plant-defined zones (high marsh dominated by Distichlis spicata and a zone of invasive Phragmites australis) during 2013 and 2014 growing seasons. Two sediment cores were collected in 2015 from the ... |
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Conceptual marsh units of salt marshes on the Eastern Shore of Virginia
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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Mean tidal range 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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Unvegetated to vegetated ratio 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 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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Vegetation survey in a coastal marsh at the Grand Bay National Estuarine Research Reserve, Mississippi
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, Mississippi (GNDNERR). 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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Inventory of Managed Coastal Wetlands in Delaware Bay and Delaware's Inland Bays
This data release contains areas within Delaware Bay and Delaware Inland Bays that are within tidal elevations, as determined by the Highest Astronomical Tide (HAT), but that are classified as non-tidal or managed wetlands by the National Wetlands Inventory (NWI) or as non-estuarine by the 2016 Coastal Change Analysis Program (C-CAP) land cover dataset. These areas have been assigned the classification codes of NWI, where available, and C-CAP. These data are based on a 5m resolution elevation raster from ... |
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Time-series of biogeochemical and flow data from a tidal salt-marsh creek, Sage Lot Pond, Waquoit Bay, Massachusetts, 2012-2016 (ver. 2.0, July 2023)
Extended time-series sensor data were collected between 2012 and 2016 in surface water of a tidal salt-marsh creek on Cape Cod, Massachusetts. The objective of this field study was to measure water chemical characteristics and flows, as part of a study to quantify lateral fluxes of dissolved carbon species between the salt marsh and estuary. Data consist of in-situ measurements including salinity, temperature, pH, dissolved oxygen, redox potential, fluorescent dissolved organic matter, turbidity, ... |
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Sedimentologic Data from Point aux Chenes Marsh and Estuary, Mississippi (18CCT09)
Sediment samples, including marsh and estuarine surface samples and marsh push and peat-auger cores, were collected from Point aux Chenes, Mississippi from October 23-26, 2018, and August 4, 2021. Marsh surface samples (top 1 centimeter (cm) of sediment; sample names appended with S), marsh push cores (core names appended with M) and peat-auger cores (core names appended with R) were collected along 50-meter (m), shore perpendicular, transects identified as sites 5, 6, 7, and 9. All samples in the dataset ... |
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Sedimentologic Data from Point aux Chenes Marsh and Estuary, Mississippi (21CCT02)
Sediment samples, including marsh and estuarine surface samples and marsh push and peat-auger cores, were collected from Point aux Chenes, Mississippi from October 23-26, 2018, and August 4, 2021. Marsh surface samples (top 1 centimeter (cm) of sediment; sample names appended with S), marsh push cores (core names appended with M) and peat-auger cores (core names appended with R) were collected along 50-meter (m), shore perpendicular, transects identified as sites 5, 6, 7, and 9. All samples in the dataset ... |
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Slope Values Across Marsh-Forest Boundary in Chesapeake Bay Region, USA
The marsh-forest boundary in the Chesapeake Bay was determined by geoprocessing high-resolution (1 square meter) land use and land cover data sets. Perpendicular transects were cast at standard intervals (30 meters) along the boundary within a GIS by repurposing the Digital Shoreline Analysis System (DSAS) Version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. Average and maximum slope values were assigned to each transect from surface elevation data. The same values were also provided as ... |
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Conceptual marsh units of 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 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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Mean tidal range 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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Unvegetated to vegetated ratio 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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Wave power on 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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Conceptual marsh units of 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 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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Mean tidal range 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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Unvegetated to vegetated ratio 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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Unvegetated to vegetated ratio at Thompsons Beach and Stone Harbor, New Jersey from 2014 to 2018
In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science ... |
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Conceptual marsh units of 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 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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Mean tidal range 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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Exposure potential of marsh units to environmental health stressors 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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Rate of shoreline change 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, mean tidal range, and shoreline change rate are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific ... |
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Unvegetated to vegetated ratio 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 marsh units in Cape Cod National Seashore salt marsh complex, Massachusetts
Elevation distribution in the Cape Cod National Seashore (CACO) salt marsh complex and approximal wetlands is given in terms of mean elevation of conceptual marsh units defined by Defne and Ganju (2019). The elevation data is based on the 1-meter resolution Coastal National Elevation Database (CoNED), where data gaps exist. 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 ... |
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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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Conceptual marsh units for Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia
The salt marsh complex of Assateague Island National Seashore (ASIS) and Chincoteague Bay was delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location is used to determine the ridge lines that separate each marsh unit while the surface slope is used to automatically assign each unit a drainage point, where water is expected to drain through. Through scientific efforts initiated with the Hurricane Sandy ... |
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Collection, Analysis, and Age-Dating of Sediment Cores from Salt Marshes, Rhode Island, 2016
The accretion history of fringing salt marshes in Narragansett Bay, Rhode Island, was reconstructed from sediment cores. Age models, based on excess lead-210 and cesium-137 radionuclide analysis, were constructed to evaluate how vertical accretion and carbon burial rates have changed during the past century. The Constant Rate of Supply (CRS) age model was used to date six cores collected from three salt marshes. Both vertical accretion rates and carbon burial increased from 1900 to 2016, the year the data ... |
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Mean tidal range in marsh units of Plum Island Estuary and Parker River salt marsh complex, Massachusetts
Biomass production is positively correlated with mean tidal range in salt marshes along the Atlantic coast of the United States of America. Recent studies support the idea that enhanced stability of the marshes can be attributed to increased vegetative growth due to increased tidal range. This dataset displays the spatial variation of mean tidal range (i.e. Mean Range of Tides, MN) in the Plum Island Estuary and Parker River (PIEPR) salt marsh complex based on conceptual marsh units defined by Defne and ... |
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Conceptual marsh units for Cape Cod National Seashore salt marsh complex, Massachusetts
The salt marsh complex of Cape Cod National Seashore (CACO), Massachusetts, USA and approximal wetlands were delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location is used to determine the ridge lines that separate each marsh unit while the surface slope is used to automatically assign each unit a drainage point, where water is expected to drain through. Through scientific efforts initiated with the ... |
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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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Conceptual marsh units for Fire Island National Seashore and central Great South Bay salt marsh complex, New York
The salt marsh complex of Fire Island National Seashore (FIIS) and central Great South Bay was delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location is used to determine the ridge lines that separate each marsh unit while the surface slope is used to automatically assign each unit a drainage point, where water is expected to drain through. Through scientific efforts initiated with the Hurricane Sandy ... |
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Collection, analysis, and age-dating of sediment cores from mangrove wetlands in San Juan Bay Estuary, Puerto Rico, 2016
The San Juan Bay Estuary, Puerto Rico, contains mangrove forests that store significant amounts of organic carbon in soils and biomass. There is a strong urbanization gradient across the estuary, from the highly urbanized and clogged Caño Martin Peña in the western part of the estuary, a series of lagoons in the center of the estuary, and a tropical forest reserve (Piñones) in the easternmost part with limited urbanization. We collected sediment cores to determine carbon burial rates and vertical ... |
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Conceptual marsh units of 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 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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Mean tidal range 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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Unvegetated to vegetated ratio 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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Conceptual marsh units of 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 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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Mean tidal range 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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Unvegetated to vegetated ratio 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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Unvegetated to vegetated marsh ratio in Cape Cod National Seashore salt marsh complex, Massachusetts
Unvegetated to vegetated marsh ratio (UVVR) in the Cape Cod National Seashore (CACO) salt marsh complex and approximal wetlands is computed based on conceptual marsh units defined by Defne and Ganju (2019). UVVR was calculated based on U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) 1-meter resolution imagery. 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 ... |
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Unvegetated to vegetated marsh ratio in Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia
Unvegetated to vegetated marsh ratio (UVVR) in the Assateague Island National Seashore and Chincoteague Bay is computed based on conceptual marsh units defined by Defne and Ganju (2018). UVVR was calculated based on U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) 1-meter resolution imagery. 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 ... |
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Continuous Monitoring Data From Great Barnstable Marsh on Cape Cod, Massachusetts, 2017-19
Salt marshes are environmental ecosystems that contribute to coastal landscape resiliency to storms and rising sea level. Ninety percent of mid-Atlantic and New England salt marshes have been impacted by parallel grid ditching that began in the 1920s–40s to control mosquito populations and to provide employment opportunities during the Great Depression (James-Pirri and others, 2009; Kennish, 2001). Continued alteration of salt marsh hydrology has had unintended consequences for salt marsh sustainability ... |
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Conceptual marsh units for 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 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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Mean tidal range in marsh units of 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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Unvegetated to vegetated marsh ratio 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 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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Collection, analysis, and age-dating of sediment cores from a salt marsh platform and ponds, Rowley, Massachusetts, 2014-15
Sediment cores were collected from three sites within the Plum Island Ecosystems Long-Term Ecological Research (PIE-LTER) domain in Massachusetts to obtain estimates of long-term marsh decomposition and evaluate shifts in the composition and reactivity of sediment organic carbon in disturbed marsh environments. Paired sediment cores were collected from three sites on the marsh platform and from three ponds; these cores were about 100 and 50 centimeters in length, respectively. The marsh sites had similar ... |
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Wave thrust values at point locations along the shorelines of Massachusetts and Rhode Island
This product provides spatial variations in wave thrust along shorelines in Massachusetts and Rhode Island. Natural features of relevance along the State coast are salt marshes. In recent times, marshes have been eroding primarily through lateral erosion. Wave thrust represents a metric of wave attack acting on marsh edges. The wave thrust is calculated as the vertical integral of the dynamic pressure of waves. This product uses a consistent methodology with sufficient spatial resolution to include 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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Unvegetated to vegetated ratio 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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Unvegetated to vegetated marsh ratio in Plum Island Estuary and Parker River salt marsh complex, Massachusetts
Unvegetated to vegetated marsh ratio (UVVR) in the Plum Island Estuary and Parker River (PIEPR) salt marsh complex was computed based on conceptual marsh units defined by Defne and Ganju (2018). UVVR was calculated based on U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) 1-meter resolution imagery. 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 ... |
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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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Mean tidal range in marsh units of Fire Island National Seashore and central Great South Bay salt marsh complex, New York
Biomass production is positively correlated with mean tidal range in salt marshes along the Atlantic coast of the United States of America. Recent studies support the idea that enhanced stability of the marshes can be attributed to increased vegetative growth due to increased tidal range. This dataset displays the spatial variation of mean tidal range (i.e. Mean Range of Tides, MN) in the Fire Island National Seashore and central Great South Bay salt marsh complex, based on conceptual marsh units defined ... |
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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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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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Continuous Monitoring Data From Herring River Wetlands, Cape Cod, Massachusetts, 2015 to January 2020
The Herring River estuary (Wellfleet, Cape Cod, Massachusetts) has been tidally restricted for over a century by a dike constructed near the mouth of the river. Behind 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 wetlands dominated by Phragmites australis. This estuary is now managed by the National Park Service, which has plans to replace the dike and ... |
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Mean tidal range in marsh units of Cape Cod National Seashore salt marsh complex, Massachusetts
Biomass production is positively correlated with mean tidal range in salt marshes along the Atlantic coast of the United States of America. Recent studies support the idea that enhanced stability of the marshes can be attributed to increased vegetative growth due to increased tidal range. This dataset displays the spatial variation of mean tidal range (i.e. Mean Range of Tides, MN) in the Cape Cod National Seashore (CACO) salt marsh complex and approximal wetlands based on conceptual marsh units defined by ... |
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Unvegetated to vegetated marsh ratio in Fire Island National Seashore and central Great South Bay salt marsh complex, New York
Unvegetated to vegetated marsh ratio (UVVR) in the Fire Island National Seashore and central Great South Bay salt marsh complex, is computed based on conceptual marsh units defined by Defne and Ganju (2018). UVVR was calculated based on U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) 1-meter resolution imagery. 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 ... |
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Wave thrust values at point locations along the shorelines of Chesapeake Bay, Maryland and Virginia
This product provides spatial variations in wave thrust along shorelines in the Chesapeake Bay. Natural features of relevance along the Bay coast are salt marshes. In recent times, marshes have been eroding primarily through lateral erosion. Wave thrust represents a metric of wave attack acting on marsh edges. The wave thrust is calculated as the vertical integral of the dynamic pressure of waves. This product uses a consistent methodology with sufficient spatial resolution to include the distinct features ... |
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Conceptual marsh units of 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 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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Mean tidal range 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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Exposure potential of marsh units to environmental health stressors 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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Rate of shoreline change 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, mean tidal range, and shoreline change rate 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. ... |
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Unvegetated to vegetated ratio 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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Conceptual marsh units for Plum Island Estuary and Parker River salt marsh complex, Massachusetts
The salt marsh complex of Plum Island Estuary and Parker River (PIEPR) was delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location was used to determine the ridge lines that separate each marsh unit while the surface slope was used to automatically assign each unit a drainage point, where water is expected to drain through. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. ... |
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Conceptual marsh units of 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 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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Mean tidal range 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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Exposure potential of marsh units to environmental health stressors 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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Rate of shoreline change 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, mean tidal range, and shoreline change rate 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 ... |
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Unvegetated to vegetated ratio 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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Continuous Monitoring Data From Natural and Restored Salt Marshes on Cape Cod, Massachusetts, 2016-17
Continuous monitoring data reported are a portion of data from a larger study investigating changes in soil properties, carbon accumulation, and greenhouse gas fluxes in four recently restored salt marsh sites and nearby natural salt marshes. For several decades, local towns, conservation groups, and government organizations have worked to identify, replace, repair, and enlarge culverts to restore tidal flow upstream from historical tidal restrictions in an effort to restore salt marsh ecosystems on Cape ... |
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Mean tidal range in marsh units of Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia
Biomass production is positively correlated with mean tidal range in salt marshes along the Atlantic coast of the United States of America. Recent studies support the idea that enhanced stability of the marshes can be attributed to increased vegetative growth due to increased tidal range. This dataset displays the spatial variation of mean tidal range (i.e. Mean Range of Tides, MN) in the Assateague Island National Seashore and Chincoteague Bay based on conceptual marsh units defined by Defne and Ganju ... |
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Conceptual marsh units of Blackwater salt marsh complex, Chesapeake Bay, Maryland
This data release contains coastal wetland synthesis products for the geographic region of Blackwater, 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 forecast products to ... |
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Riparian vegetation abundance (percent cover) in the Elwha River estuary, Washington, in 2007 and 2014
This portion of the data release presents riparian plant species abundance (percent cover) data from plots sampled in the Elwha River estuary, Washington, in 2007 and 2014. In August 2007, we established 21 vegetation plots within the study area in a stratified random fashion, with three to five plots in five of the vegetation cover types denoted in the habitat classification maps: mixed riparian forest, willow-alder forest, riparian shrub, emergent marsh/marsh-shrub transition, and dunegrass. Each plot was ... |
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Riparian vegetation species richness in the Elwha River estuary, Washington, in 2007 and 2014
This portion of the data release presents riparian plant species richness (number of unique taxa) data from plots sampled in the Elwha River estuary, Washington, in 2007 and 2014. In August 2007, we established 21 vegetation plots within the study area in a stratified random fashion, with three to five plots in five of the vegetation cover types denoted in the habitat classification maps: mixed riparian forest, willow-alder forest, riparian shrub, emergent marsh/marsh-shrub transition, and dunegrass. Each ... |
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Seasonal vegetation characteristics in a Spartina foliosa- and Salicornia pacifica-dominated salt marsh at China Camp State Park
As part of the San Francisco Bay Marsh Sediment Experiments and hydrodynamic investigations in San Pablo Bay and China Camp Marsh, California, vegetation sampling measurements were taken over several periods at numerous locations. This portion of the data release presents physical characteristics and percent cover data from vegetation plots sampled in China Camp State Park salt marsh (northern San Francisco Bay) in 2015, 2016, and 2017. One-meter quadrats (1m x 1m) were analyzed for percent cover of each ... |
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Wetland Paleoecological Study of Coastal Louisiana: Sediment Cores and Diatom Samples Dataset
Wetland sediment data was collected from coastal Louisiana as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits for tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh to brackish marsh throughout the southwest Louisiana Chenier Plain and are located coincident with Coastwide Reference Monitoring System (CRMS). Sediment ... |
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Wetland Paleoecological Study of Coastal Louisiana: X-radiographs
Wetland sediment data was collected from coastal Louisiana as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits for tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh to brackish marsh throughout the southwest Louisiana Chenier plain and are located coincident with Coastwide Reference Monitoring System (CRMS). Sediment ... |
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Wetland Paleoecological Study of Coastal Louisiana: Surface Sediment and Diatom Calibration Dataset
Wetland sediment data was collected from coastal Louisiana as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits for tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh to brackish marsh throughout the southwest Louisiana Chenier plain and are located coincident with Coastwide Reference Monitoring System (CRMS). Sediment ... |
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Sediment Core Microfossil Data Collected from the Coastal Marsh of Grand Bay National Estuarine Research Reserve, Mississippi, USA
To aid in geologic studies of sediment transport and environmental change in coastal marsh, 1-centimeter (cm) foraminiferal subsamples were taken from seven sediment push cores collected in the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi, in October 2016. The push cores were collected along two, shore-perpendicular transects at 5, 15, 25, and 50 meters (m) from the shoreline, on opposite sides of Middle Bay during U.S. Geological Survey (USGS) Field Activities Number (FAN) 2016-358 ... |
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Wetland-Change Data Derived from Landsat Imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1984 to 2015: Land-cover Change Analysis
This U.S. Geological Survey (USGS) data release includes geospatial datasets that were created for the analysis of Virginia and Maryland Atlantic coastal wetland changes over time. Wetland change was determined by assessing two metrics: wetland persistence and land-cover switching. Because seasonal water levels, beach width, and vegetation differences can affect change analyses, only images acquired during the spring (March, April, and May) were included in the wetland-change metrics (N=10). Land-cover ... |
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Land-Cover Data Derived from Landsat Satellite Imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1985 and 2015
This U.S. Geological Survey (USGS) data release includes geospatial datasets that were created to analyze wetland changes along the Virginia and Maryland Atlantic coasts between 1984 and 2015. Wetland change was determined by assessing two metrics: wetland persistence and land-cover switching. Because seasonal water levels, beach width, and vegetation differences can affect change analyses, only images acquired during the spring (March, April, and May) were included in the wetland-change metrics (N=10). ... |
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Wetland-Change Data Derived from Landsat Imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1984 to 2015: Wetland Persistence Analysis
This U.S. Geological Survey (USGS) data release includes geospatial datasets that were created for the analysis of Virginia and Maryland Atlantic coastal wetland changes over time. Wetland change was determined by assessing two metrics: wetland persistence and land-cover switching. Because seasonal water levels, beach width, and vegetation differences can affect change analyses, only images acquired during the spring (March, April, and May) were included in the wetland-change metrics (N=10). To assess ... |
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Static chamber fluxes of carbon dioxide and methane from coastal wetlands on Upper Cape Cod, Massachusetts and supporting environmental data, 2021
Saline tidal wetlands are important sites of carbon sequestration and produce negligible methane (CH4) emissions due to regular inundation with sulfate-rich seawater. Yet, widespread management of coastal hydrology has restricted vast areas of coastal wetlands to tidal exchange. These ecosystems often undergo impoundment and freshening, which in turn cause vegetation shifts like invasion by Phragmites, that affect ecosystem carbon balance. Understanding controls of carbon exchange in these understudied ... |
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Static chamber fluxes of carbon dioxide and methane from Phragmites wetlands and supporting data collected across a salinity gradient on Cape Cod, Massachusetts
Saline tidal wetlands are important sites of carbon sequestration and produce negligible methane (CH4) emissions due to regular inundation with sulfate-rich seawater. Yet, widespread management of coastal hydrology has restricted vast areas of coastal wetlands to tidal exchange. These ecosystems often undergo impoundment and freshening, which in turn cause vegetation shifts like invasion by Phragmites, that affect ecosystem carbon balance. Understanding controls of carbon exchange in these understudied ... |
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Eddy covariance fluxes of carbon dioxide and methane from the Herring River in Wellfleet, MA (ver 2.0, June 2022)
Saline tidal wetlands are important sites of carbon sequestration and produce negligible methane (CH4) emissions due to regular inundation with sulfate-rich seawater. Yet, widespread management of coastal hydrology has restricted vast areas of coastal wetlands to tidal exchange. These ecosystems often undergo impoundment and freshening, which in turn cause vegetation shifts like invasion by Phragmites, that affect ecosystem carbon balance. Understanding controls of carbon exchange in these understudied ... |
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Continuous Water Level, Salinity, and Temperature Data from Monitoring Wells in Herring River Wetlands, Cape Cod, Massachusetts, 2020-2021
Environmental parameters affecting plant productivity and microbial respiration, such as water level, salinity, and groundwater temperature included in these datasets, are key components of wetland carbon cycling, carbon storage, and capacity to maintain elevation. Data were collected to (1) provide background data to evaluate potential differences in water level and carbon flux between wetland sites with differing elevation and tidal inundation and (2) facilitate applications of Blue Carbon projects in ... |
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Continuous Water Level, Salinity, and Temperature Data from Monitoring Wells in Wetlands on the South Shore of Cape Cod, Massachusetts, 2020
Environmental parameters affecting plant productivity and microbial respiration, such as water level, salinity, and groundwater temperature included in these datasets, are key components of wetland carbon cycling, carbon storage, and capacity to maintain elevation. Data were collected to (1) provide background data to evaluate potential differences in water level and carbon flux between wetland sites with differing elevation and tidal inundation and (2) facilitate applications of Blue Carbon projects in ... |
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Seafloor character from air-photo data-Santa Barbara Channel
Seafloor character was derived from interpretations of aerial photograph-derived kelp-distribution data available for Santa Cruz Island in the Santa Barbara Channel, California (Kushner and others 2013). The number of substrate classes was reduced because rugosity could not be derived for all areas. |
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Seafloor character from lidar data-Santa Barbara Channel
Seafloor character was derived from interpretations of lidar data available for the mainland coast within the study area from the California State Waters Mapping Program (Johnson and others, 2012; Johnson and others, 2013a; Johnson and others, 2013b; Johnson and others, 2013c). The number of substrate classes was reduced because rugosity could not be derived for all areas. References Cited: Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L ... |
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Seafloor character from multibeam echo sounder data-Santa Barbara Channel
Substrate was classified using the method of (Cochrane 2008) for this study multibeam sonar. Sea floor character derived from multibeam sonar data is available for the mainland coast within the study area from the California State Waters Mapping Program (Johnson and others, 2012; Johnson and others, 2013a; Johnson and others, 2013b; Johnson and others, 2013c). The number of substrate classes was reduced because rugosity could not be derived for all areas due to the lack of bathymetry data for other data ... |
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Seafloor character from sidescan sonar data-Santa Barbara Channel
Substrate was classified using the method of (Cochrane and Lafferty, 2002) for this study. Sea floor character derived from towed sidescan sonar data is available for the mainland coast within the study area from USGS online publications (Cochrane and others, 2003; Cochrane and others, 2005). The number of substrate classes was reduced because rugosity could not be derived for all areas due to the lack of bathymetry data for other data sets used in the study. References Cited: Cochrane, G.R., Nasby, N.M., ... |
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Benthic communities in the New London sidescan mosaic study area
This data layer depicts benthic communities found in the New London sidescan sonar mosaic study area. |
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Habitat--Offshore of Point Conception Map Area, California
This part of DS 781 presents data for the habitat map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Habitat_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point ... |
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Habitat--Offshore of Gaviota Map Area, California
This part of DS 781 presents data for the habitat map of the Offshore of Gaviota Map Area, California. The vector data file is included in "Habitat_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. ... |
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Habitat--Monterey Canyon and Vicinity, California
This part of DS 781 presents data for the habitat map of the seafloor of the Monterey Canyon and Vicinity map area, California. The vector data file is included in "Habitat_MontereyCanyon.zip," which is accessible from https://doi.org/10.5066/F7XD0ZQ4. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., ... |
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Benthic habitats of the coral reef ecosystem on the south shore of Moloka'i
A benthic habitat polygon coverage has been created of the coral reef ecosystem on the south shore of Moloka'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major Biological Cover, Percent of Major Biological Cover, Reef Zone ... |
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Benthic habitat map of the U.S. Coral Reef Task Force Watershed Partnership Initiative Kaanapali priority study area and the State of Hawaii Kahekili Herbivore Fisheries Management Area, west-central Maui, Hawaii
A benthic habitat polygon coverage has been created of the coral reef ecosystem within the U.S. Coral Reef Task Force Watershed Partnership Initiative Kaanapali priority study area and the State of Hawaii Kahekili Herbivore Fisheries Management Area, West-Central Maui, Hawaii. Polygons were hand-digitized from visual interpretation of QuickBird-2 satellite imagery (2005), and SHOALS bathymetry data. We also utilized in situ knowledge from underwater photography and videography (2002-2011), side-scan sonar ... |
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Benthic habitats of the coral reef ecosystem off the coast of Pu'ukohola Heiau (PUHE) National Historic Site
A benthic habitat polygon coverage has been created of the coral reef ecosystem off the coast of Pu'ukohola Heiau (PUHE) National Historic Site on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major ... |
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Benthic habitats of the coral reef ecosystem off the coast of Kaloko-Honokohau (KAHO) National Historical Park
A benthic habitat polygon coverage has been created of the coral reef ecosystem within and adjacent to Kaloko-Honokohau (KAHO) National Historical Park on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate ... |
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Benthic habitats of the coral reef ecosystem off the coast of Pu'uhonua O Honaunau (PUHO) National Historical Park
A benthic habitat polygon coverage has been created of the coral reef ecosystem off the coast of Pu'uhonua O Honaunau (PUHO) National Historical Park on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, ... |
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Geologic Observations-Oregon OCS Floating Wind Farm Site
This part of the Oregon Outer Continental Shelf (OCS) Floating Windfarm Suite Data Release presents geological observations from video collected on U.S. Geological Survey (USGS) field activity 2014-607-FA in the Floating Wind Farm survey area. The survey was conducted using 12 hour day operations out of Charleston Harbor near Coos Bay, Oregon. The cruise plan consisted of 23 days on site split between sonar mapping and video ground truth surveying. Activities parsed out to nine days of sonar mapping, three ... |
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Mammal Observations-Oregon OCS Floating Wind Farm Site
This part of the Oregon OCS Data Release presents marine mammal observations from U.S. Geological Survey (USGS) field activity 2014-607-FA in the Oregon Outer continental Shelf (OCS)Floating Wind Farm survey area. The survey was conducted using 12 hour day operations out of Charleston Harbor near Coos Bay, Oregon. The cruise plan consisted of 23 days on site split between sonar mapping and video ground truth surveying. Activities parsed out to nine days of sonar mapping, three days of video surveying, eight ... |
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Habitat--Offshore of Bodega Head, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Bodega Head map area, California. The vector data file is included in "Habitat_OffshoreBodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E. ... |
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Remote Sensing Coastal Change Simple Data Distribution Service
The Remote Sensing Coastal Change Simple Data Service provides timely and long-term access to emergency, provisional, and approved photogrammetric imagery, derivatives, and ancillary data through a web service via HyperText Transfer Protocol to a folder/file structure organized by data collection platform and survey (collection effort) with metadata sufficient to facilitate both human and machine access. Data are acquired, processed, and published using standardized workflows. Each data type added to the ... |
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Habitat--Offshore of Pacifica, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Pacifica map area, California. The vector data file is included in "Habitat_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross ... |
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Habitat--Offshore of Bolinas, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Bolinas map area, California. The vector data file is included in "Habitat_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., ... |
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Habitat--Offshore of Half Moon Bay, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Half Moon Bay map area, California. The polygon shapefile is included in "Habitat_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J ... |
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Habitat--Offshore of Salt Point, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Salt Point map area, California. The vector data file is included in "Habitat_OffshoreSaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ... |
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Habitat--Offshore of San Francisco, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of San Francisco map area, California. The vector data file is included in "Habitat_SanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G. ... |
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Habitat--Offshore of San Gregorio, California
This part of SIM 3306 presents data for the habitat map of the Offshore of San Gregorio map area, California. The vector data file is included in "Habitat_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey, M.D., Bretz, C ... |
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Habitat--Offshore of Aptos, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Aptos map area, California. The vector data file is included in "Habitat_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., ... |
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Habitat--Offshore Santa Cruz, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Santa Cruz map area, California. The vector data file is included in "Habitat_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier ... |
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Habitat--Offshore of Point Reyes Map Map Area, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Point Reyes map area, California. The vector data file is included in "Habitat_PointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, ... |
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Habitat--Offshore of Tomales Point, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Tomales Point map area, California. The polygon shapefile is included in "Habitat_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., ... |
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Habitat--Offshore of Carpinteria, California
This part of DS 781 presents habitat data in the Offshore of Carpinteria map area, California. The vector data file is included in "Habitat_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L ... |
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Habitat--Offshore of Coal Oil Point, California
This part of DS 781 presents the habitat map of the Offshore of Coal Oil Point map area, California. The vector data file is included in "Habitat_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, ... |
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Habitat--Offshore of Fort Ross, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Fort Ross map area, California. The polygon shapefile is included in "Habitat_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, ... |
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Habitat--Offshore of Refugio Beach, California
This part of DS 781 presents the habitat map of the Offshore of Refugio Beach map area, California. The vector data file is included in "Habitat_RefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., Seitz, G.G., Endris, C.A., Sliter ... |
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Habitat--Offshore of Santa Barbara, California
This part of DS 781 presents data for the habitat map of the Offshore of Santa Barbara map area, California. The vector data file is included in "Habitat_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., ... |
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Habitat--Offshore of Ventura, California
This part of DS 781 presents habitat data in the Offshore of Ventura map area, California. The vector data file is included in "Habitat_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey ... |
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Geomorphic habitat units derived from 2009 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 11 September 2009 1 meter resolution NAIP aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (17 September 2009) for areas < MHHW and aerial lidar surveys (4-6 April 2009) for elevations > MHHW. |
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Geomorphic habitat units derived from 2011 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 03 September 2011* 0.3 meter resolution Microsoft/Digital Globe aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (25 August 2011) for areas < MHHW and aerial lidar surveys (13-15 April 2012) for elevations > MHHW. *Image date of 3-Sep-11 corrected in metadata. During product generation the imagery date was believed to be 8-25-2011, as reported by ... |
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Geomorphic habitat units derived from 2012 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 30 August 2012 0.15 meter resolution NPS Elwha PlaneCam aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (28 August 2012) for areas < MHHW and aerial lidar surveys (17 October 2012) for elevations > MHHW. |
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Geomorphic habitat units derived from 2013 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 26 August 2013 0.15 meter resolution NPS Elwha PlaneCam aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (16 September 2013) for areas < MHHW and aerial lidar surveys (17 October 2012) supplemented with NPS Elwha PlaneCam SfM photogrammetry data (19 September 2013) for elevations > MHHW. |
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Geomorphic habitat units derived from 2014 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 28 August 2014 0.15 meter resolution NPS Elwha PlaneCam aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (5-8 September 2014) for areas < MHHW and aerial lidar surveys (7 November 2014) supplemented with NPS Elwha PlaneCam SfM photogrammetry data (30 September 2014) for elevations > MHHW. |
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Vegetation habitat units derived from 2009 aerial imagery and field data for the Elwha River estuary, Washington
Estuary vegetation cover delineated from 11 September 2009 1-meter-resolution NAIP aerial imagery at a scale of 1:1500. |
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Vegetation habitat units derived from 2011 aerial imagery and field data for the Elwha River estuary, Washington
Estuary vegetation cover delineated from 3 September 2011* 0.3-meter-resolution aerial imagery (Microsoft/Digital Globe) at a scale of 1:1500. *Image date of 3-Sep corrected in metadata. During product generation the imagery date was believed to be 8-25-2011, as reported by DigitalGlobe reseller. |
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Vegetation habitat units derived from 2012 aerial imagery and field data for the Elwha River estuary, Washington
Estuary vegetation cover delineated from 30 August 2012 0.15-meter-resolution NPS Elwha PlaneCam aerial imagery at a scale of 1:1500. |
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Vegetation habitat units derived from 2013 aerial imagery and field data for the Elwha River estuary, Washington
Estuary vegetation cover delineated from 26 August 2013 0.15-meter-resolution NPS Elwha PlaneCam aerial imagery at a scale of 1:1500. |
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Vegetation habitat units derived from 2014 aerial imagery and field data for the Elwha River estuary, Washington
Estuary vegetation cover delineated from 28 August 2014 0.15-meter-resolution NPS Elwha PlaneCam aerial imagery at a scale of 1:1500. |
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Habitat--Drakes Bay and Vicinity, California
This part of DS 781 presents data for the habitat map of the seafloor of the Drakes Bay and Vicinity map area, California. The vector data file is included in "Habitat_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., ... |
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Habitat--Hueneme Canyon and Vicinity, California
This part of DS 781 presents data for the habitat map of the seafloor of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Habitat_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter ... |
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Habitat--Offshore of Monterey, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Monterey map area, California. The vector data file is included in "Habitat_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds. ... |
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Habitat--Offshore Pigeon Point, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Pigeon Point map area, California. The vector data file is included in "Habitat_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., ... |
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Habitat--Offshore Scott Creek, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Scott Creek map area, California. The vector data file is included in "Habitat_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., ... |
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BSYCHAB -- Habitat polygons for the Big Sycamore reserve area
Benthic habitat polygon coverages have been created for marine reserve locations surrounding the Santa Barbara Basin. Diver, ROV and submersible video transects, bathymetry data, sedimentary samples, and sonar mapping, have been integrated to describe the geological, biological, and oceanographic aspects of habitat. Big Sycamore reserve, is part of the Marine Ecological Reserves Research Program (MERRP). The U.S. Geological Survey (USGS), in a cooperative project with Sea Grant-MERRP and investigators at ... |
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NANAHAB -- Habitat polygons for the nearshore North Anacapa Island, Channel Islands NMS
Benthic habitat polygon coverages have been created for marine reserve locations surrounding the Santa Barbara Basin. Diver, ROV and submersible video transects, bathymetry data, sedimentary samples, and sonar mapping, have been integrated to describe the geological, biological, and oceanographic aspects of habitat. Anacapa Reserve, is part of the Marine Ecological Reserves Research Program (MERRP). The U.S. Geological Survey (USGS), in a cooperative project with Sea Grant-MERRP and investigators at ... |
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SMIGHAB -- Habitat polygons for the nearshore San Miguel Island, Channel Islands NMS
Benthic habitat polygon coverages have been created for marine reserve locations surrounding the Santa Barbara Basin. Diver, ROV and submersible video transects, bathymetry data, sedimentary samples, and sonar mapping, have been integrated to describe the geological, biological, and oceanographic aspects of habitat. The U.S. Geological Survey (USGS), in a cooperative project with Sea Grant-MERRP and investigators at National Marine Fisheries Service (NMFS), the Channel Islands National Marine Sanctuary ... |
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SVANHAB -- Habitat polygons for the nearshore Point Arguello study area, South Vandenberg Reserve
Benthic habitat polygon coverages have been created for marine reserve locations surrounding the Santa Barbara Basin. Diver, ROV and submersible video transects, bathymetry data, sedimentary samples, and sonar mapping, have been integrated to describe the geological, biological, and oceanographic aspects of habitat. The U.S. Geological Survey (USGS), in a cooperative project with Sea Grant-MERRP and investigators at National Marine Fisheries Service (NMFS), the Channel Islands National Marine Sanctuary ... |
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NANPHAB -- Benthic Habitat polygons for North Anacapa Passage (UTM 10N, NAD83)
Benthic habitat polygon coverages have been created for marine reserve locations surrounding the Santa Barbara Basin. Diver, ROV and submersible video transects, bathymetry data, sedimentary samples, and sonar mapping, have been integrated to describe the geological, biological, and oceanographic aspects of habitat. Anacapa Reserve, is part of the Marine Ecological Reserves Research Program (MERRP). The U.S. Geological Survey (USGS), in a cooperative project with Sea Grant-MERRP and investigators at ... |
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SANAHAB -- Benthic Habitat polygons for South Anacapa Island (UTM 10N, NAD83)
Benthic habitat polygon coverages have been created for marine reserve locations surrounding the Santa Barbara Basin. Diver, ROV and submersible video transects, bathymetry data, sedimentary samples, and sonar mapping, have been integrated to describe the geological, biological, and oceanographic aspects of habitat. Anacapa Reserve, is part of the Marine Ecological Reserves Research Program (MERRP). The U.S. Geological Survey (USGS), in a cooperative project with Sea Grant-MERRP and investigators at ... |
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SANPHAB -- Habitat polygons for South Anacapa Passage (UTM 10N, NAD83)
Benthic habitat polygon coverages have been created for marine reserve locations surrounding the Santa Barbara Basin. Diver, ROV and submersible video transects, bathymetry data, sedimentary samples, and sonar mapping, have been integrated to describe the geological, biological, and oceanographic aspects of habitat. Anacapa Reserve, is part of the Marine Ecological Reserves Research Program (MERRP). The U.S. Geological Survey (USGS), in a cooperative project with Sea Grant-MERRP and investigators at ... |
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SCAV2OBS -- Assorted visual observations of benthic habitat from ROV and SCUBA dives in the Channel Islands National Marine Sanctuary. (UTM 10N, NAD83)
Point based visual observations of benthic habitat from a variety of SCUBA and ROV dives. Unknown postitional accuracy. Some video data maintained by Russ Vetter, National Marine Fisheries Service, Southwest Fisheries Science Center. |
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SECRUHAB -- Habitat polygons for Southeast Santa Cruz Island (UTM 10N, NAD83)
Benthic habitat polygon coverages have been created for marine reserve locations surrounding the Santa Barbara Basin. Diver, ROV and submersible video transects, bathymetry data, sedimentary samples, and sonar mapping, have been integrated to describe the geological, biological, and oceanographic aspects of habitat. Anacapa Reserve, is part of the Marine Ecological Reserves Research Program (MERRP). The U.S. Geological Survey (USGS), in a cooperative project with Sea Grant-MERRP and investigators at ... |
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USGS Collection of Sea Bottom Photographs from the Stellwagen Bank National Marine Sanctuary Region (JPEG images)
The U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration's (NOAA) National Marine Sanctuary Program, conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary region from 1994 to 2004. The mapped area is approximately 3,700 square km (1,100 square nm) in size and was subdivided into 18 quadrangles. Several series of sea floor maps of the region based on multibeam sonar surveys have been published. In addition, 2,628 seabed ... |
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Table and accompanying photographs for biogeomorphic classification of shorebird nesting sites on the U.S. Atlantic coast from May to August, 2014
Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and use along their Atlantic Coast breeding range. A smartphone application called iPlover was developed to collect standardized ... |
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Table and accompanying photographs for biogeomorphic classification of shorebird nesting sites on the U.S. Atlantic coast from April to August, 2015
Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and use along their Atlantic Coast breeding range. A smartphone application called iPlover was developed to collect standardized ... |
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Table and accompanying photographs for biogeomorphic classification of shorebird nesting sites on the U.S. Atlantic coast from March to September, 2016
Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and use along their Atlantic Coast breeding range. A smartphone application called iPlover was developed to collect standardized ... |
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Seafloor character--Offshore of Bodega Head, California
This part of DS 781 presents the seafloor-character map Offshore of Bodega Head, California (raster data file is included in "SeafloorCharacter_BodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., ... |
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Underwater video observations offshore of Seattle, Washington
This part of USGS Data Series 935 (Cochrane, 2014) presents observations from underwater video collected in the Offshore of Seattle, California, map area, a part of the Southern Salish Sea Habitat Map Series. To validate the interpretations of multibeam sonar data and turn it into geologically and biologically useful information, the U.S. Geological Survey (USGS) towed a camera sled over specific locations throughout the Seattle map area to collect video and photographic data that would “ground truth” ... |
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Seafloor character--Offshore of Pacifica, California
This part of DS 781 presents the seafloor-character map Offshore of Pacifica, California. The raster data file is included in "SFC_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross, S.L., Golden, N.E., Watt, J.T., ... |
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Seafloor character--Offshore of Bolinas, California
This part of DS 781 presents the seafloor-character map Offshore of Bolinas, California (raster data file is included in "SeafloorCharacter_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html). These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, ... |
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Seafloor character--Offshore of Half Moon Bay, California
This part of DS 781 presents the seafloor-character map of the Offshore of Half Moon Bay map area, California. The raster data file is included in "SeafloorCharacter_OffshoreHalfMoonBay.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. This raster-format seafloor-character map shows four substrate classes of Offshore of Half Moon Bay, California. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G. ... |
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Seafloor character--Offshore of Salt Point, California
This part of DS 781 presents the seafloor-character map Offshore of Salt Point, California (raster data file is included in "SeafloorCharacter_SaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html). These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., ... |
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Seafloor character--Offshore of San Francisco, California
This part of DS 781 presents the seafloor-character map (see sheet 5) Offshore of San Francisco, California (raster data file is included in "SFC_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html). These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., ... |
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Seafloor character--Offshore of San Gregorio, California
This part of SIM 3306 presents data for the seafloor-character map of the Offshore of San Gregorio map area, California. The raster data file is included in "SeafloorCharacter_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., ... |
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Seafloor character--Offshore of Fort Ross, California
This part of DS 781 presents the seafloor-character map Offshore of Fort Ross, California (raster data file is included in "SeafloorCharacter_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html). These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., ... |
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Seafloor character--Offshore of Point Reyes Map Area, California
This part of DS 781 presents the seafloor-character map Offshore of Point Reyes, California (raster data file is included in "SFC_PointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html). These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N ... |
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Seafloor character--Offshore of Tomales Point, California
This part of DS 781 presents the seafloor-character map of the Offshore of Tomales Point map area, California. The raster data file is included in "SeafloorCharacter_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html). These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris, C ... |
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Seafloor character--Offshore of Carpinteria, California
This part of DS 781 presents data for the seafloor-character map of the Offshore of Carpinteria map area, California. The raster data file is included in "SeafloorCharacter_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., ... |
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Seafloor character, 2-m grid--Offshore of Coal Oil Point, California
This part of DS 781 presents 2-m resolution data for the seafloor-character map of the Offshore of Coal Oil Point map area, California. The raster data file is included in "SeafloorCharacter_OffshoreCoalOilPoint_2m.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad ... |
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Seafloor character, 5-m grid--Offshore of Coal Oil Point, California
This part of DS 781 presents 5-m resolution data for the seafloor-character map of the Offshore of Coal Oil Point map area, California. The raster data file is included in "SeafloorCharacter_OffshoreCoalOilPoint_5m.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad ... |
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Seafloor character--Drakes Bay and Vicinity, California
This part of DS 781 presents the seafloor-character map of the Drakes Bay and Vicinity map area, California (raster data file is included in "SeafloorCharacter_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html). These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., ... |
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Seafloor character--Offshore of Refugio Beach, California
This part of DS 781 presents the seafloor-character map of the Offshore of Refugio Beach map area, California. The raster data file is included in "SeafloorCharacter_OffshoreRefugioBeach.zip," which is accessible from https ://pubs.usgs.ov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html). These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., ... |
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Seafloor character--Offshore of Santa Barbara, California
This part of DS 781 presents data for the seafloor-character map of the Offshore of Santa Barbara map area, California. The raster data file is included in "SeafloorCharacter_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B ... |
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Seafloor character--Offshore of Ventura, California
This part of DS 781 presents data for the seafloor-character map of the Offshore of Ventura map area, California. The raster data file is included in "SeafloorCharacter_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., ... |
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C0111SC_video_observations
This part of DS 781 presents video observations from cruise C0111SC in southern California. The vector data file is included in "c0111sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 1999 and 2009, the seafloor in southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric ... |
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C0212SC_video_observations
This part of DS 781 presents video observations from cruise C0212SC in southern California. The vector data file is included in "c0212sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 2006 and 2009, the seafloor in central California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric ... |
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C210NC_video_observations
This part of DS 781 presents video observations from cruise C210NC in northern California. The vector data file is included in "c201nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 2010, the seafloor in northern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) using both multibeam echosounders and bathymetric sidescan sonar units. This mapping mission collected ... |
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F208NC_video_observations
This part of DS 781 presents video observations from cruise F208NC in northern California. The vector data file is included in "f208nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in central California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric ... |
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F307NC_video_observations
This part of DS 781 presents video observations from cruise F307NC in northern California The vector data file is included in "f307nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in northern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric ... |
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L908NC_video_observations
This part of DS 781 presents video observations from cruise L908NC for northern California. The vector data file is included in "l908nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in central California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric ... |
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s1c08sc_video_observations
This part of DS 781 presents video observations from cruise S1C08SC for the Santa Barbara Channel region and beyond in southern California. The vector data file is included in "s1c08sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using ... |
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S2210MB_video_observations
This part of DS 781 presents video observations from cruise S2210MB in northern California. The vector data file is included in "s2210mb_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 2006 and 2009, the seafloor in central California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric ... |
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sw109sc_video_observations
This part of DS 781 presents video observations from cruise SW109SC for the Santa Barbara Channel region and beyond in southern California. The vector data file is included in "sw109sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), ... |
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z107sc_video_observations
This part of DS 781 presents video observations from cruise Z107SC in southern California. The vector data file is included in "z107sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric ... |
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z206sc_video_observations
This part of DS 781 presents video observations from cruise Z206SC in southern California. The vector data file is included in "z206sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric ... |
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Benthic Biological Interpretation for California Seafloor Mapping Project
This part of DS 781 presents benthic biological observations of the California coast in support of the California Seafloor Mapping Project. A shapefile and corresponding comma-delimited text file are included in "Benthic_Biological_Interpretation.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. |
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C109NC_video_observations
This part of DS 781 presents video observations from cruise C109NC in northern California. The vector data file is included in "c109nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 2006 and 2007, the seafloor in northern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), using both multibeam echosounders and bathymetric sidescan sonar units. This mapping mission ... |
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Underwater video observations offshore of Burien, Washington
This part of USGS Data Series 935 (Cochrane, 2014) presents observations from underwater video collected in the Offshore of Burien, California, map area, a part of the Southern Salish Sea Habitat Map Series. To validate the interpretations of multibeam sonar data and turn it into geologically and biologically useful information, the U.S. Geological Survey (USGS) towed a camera sled over specific locations throughout the Seattle map area to collect video and photographic data that would ground truth the ... |
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Underwater video observations offshore of Tacoma, Washington
This part of USGS Data Series 935 (Cochrane, 2014) presents observations from underwater video collected in the Offshore of Tacoma, Washington, map area, a part of the Southern Salish Sea Map Series. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the U.S. Geological Survey (USGS) towed a camera sled over specific locations throughout the Tacoma map area to collect video and photographic data that would “ground truth” the seafloor. ... |
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Digital seafloor character data of the Gulf of Alaska from historical National Ocean Service (NOS) smooth sheets
This data release provides seafloor-characteristics point data across the Gulf of Alaska, as digitized directly from National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) smooth sheets published from 1892 to 2001, and archived at the National Geophysics Data Center (NGDC). Geo-rectification and digitization methods were adapted from Zimmermann and Benson (2013). Each location includes information for the smooth sheet number (H#####), a unique site number location, latitude, ... |
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List of NOS smooth sheets used in USGS Gulf of Alaska Digitization Project
This table lists the NOS smooth sheets included in the associated shapefile (GulfofAlaskaDigitizationProject_NOSSeafloorCharacter.zip; N = 329, plus insets), the number of samples for each smooth sheet, the year of collection (1892 to 2001), and the smooth sheet scale (from 1:2,000 to 1:600,000). Smooth sheets are available through the National Geophysics Data Center’s online data portal (NDGC, http://www.ngdc.noaa.gov). |
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Seafloor character--Hueneme Canyon and Vicinity, California
This part of DS 781 presents data for the seafloor-character map of the Hueneme Canyon and Vicinity map area, California. The raster data file is included in "SeafloorCharacter_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., ... |
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BackscatterA [8101]--Offshore Pigeon Point, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. This metadata file refers to the data included in "BackscatterA_8101_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, ... |
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BackscatterB [7125]--Offshore Pigeon Point, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. This metadata file refers to the data included in "BackscatterB_7125_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, ... |
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BackscatterC [SWATH]--Offshore Pigeon Point, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. This metadata file refers to the data included in "BackscatterC_SWATH_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson ... |
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Bathymetry Hillshade--Offshore Pigeon Point, California
This part of DS 781 presents data for the shaded-relief bathymetry map of Offshore Pigeon Point, California. The raster data file is included in "BathymetryHS_OffshorePigeonPoint.zip", which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W ... |
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Bathymetry--Offshore Pigeon Point, California
This part of DS 781 presents data for the bathymetry map of Offshore Pigeon Point, California. The raster data file is included in "Bathymetry_OffshorePigeonPoint.zip", which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P ... |
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Seafloor character--Offshore Pigeon Point, California
This part of DS 781 presents the seafloor-character map Offshore of Pigeon Point, California. The raster data file is included in "SeafloorCharacter_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., ... |
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BackscatterA [8101]--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterA_8101_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., ... |
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BackscatterB [7125]--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterB_7125_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., ... |
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BackscatterC [SWATH]--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterC_SWATH_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., ... |
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Bathymetry Hillshade--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the shaded-relief bathymetry map of Offshore Scott Creek, California. The raster data file is included in "BathymetryHS_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., ... |
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Bathymetry--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the bathymetry map of Offshore Scott Creek, California. The raster data file is included in "Bathymetry_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., ... |
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Contours--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore Scott Creek map area, California. The vector data file is included in "Contours_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., ... |
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Geology and geomorphology--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Scott Creek map area, California. The vector data file is included in "Geology_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., ... |
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Seafloor character--Offshore Scott Creek, California
This part of DS 781 presents the seafloor-character map of the Offshore of Scott Creek map area, California. The raster data file is included in "SeafloorCharacter_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, ... |
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BackscatterA [SWATH]--Offshore Aptos, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Aptos map area, California. Backscatter data are provided as two separate grids depending on mapping system and processing method. This metadata file refers to the data included in "BackscatterA_SWATH_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., ... |
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BackscatterB [EM300]--Offshore Aptos, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Aptos map area, California. Backscatter data are provided as two separate grids depending on mapping system and processing method. This metadata file refers to the data included in "BackscatterB_EM300_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., ... |
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Seafloor character, 2 m resolution--Offshore of Aptos, California
This part of DS 781 presents data for the seafloor-character map Offshore of Aptos, California. Seafloor-character data are provided as two separate grids depending on resolution of the mapping system and processing method. This metadata file refers to the data included in "SeafloorCharacter_2m_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., ... |
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Seafloor character, 5 m resolution--Offshore of Aptos, California
This part of DS 781 presents data for the seafloor-character map Offshore of Aptos, California. Seafloor-character data are provided as two separate grids depending on resolution of the mapping system and processing method. This metadata file refers to the data included in "SeafloorCharacter_5m_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., ... |
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Backscatter [SWATH]--Offshore Santa Cruz, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Santa Cruz map area, California. Backscatter data are provided as a raster file included in "Backscatter_Swath_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, ... |
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Seafloor character--Offshore Santa Cruz, California
This part of DS 781 presents the seafloor-character map Offshore of Santa Cruz, California. The raster data file is included in "SeafloorCharacter_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman ... |
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Landscape and vegetation photos and ground truthing data collected on North Core Banks, NC in October 2022
These data map in high detail surficial cross-sections of North Core Banks, a barrier island in Cape Lookout National Seashore, NC, in October 2022. U.S. Geological Survey field efforts are part of an interagency agreement with the National Park Service to monitor the recovery of the island from Hurricanes Florence (2018) and Dorian (2019). Three sites of outwash, overwash, and pond formation were targeted for extensive vegetation ground-truthing, sediment samples, bathymetric mapping with a remote ... |
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Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation
Coast Train is a library of images of coastal environments, annotations, and corresponding thematic label masks (or ‘label images’) collated for the purposes of training and evaluating machine learning (ML), deep learning, and other models for image segmentation. It includes image sets from both geospatial satellite, aerial, and UAV imagery and orthomosaics, as well as non-geospatial oblique and nadir imagery. Images include a diverse range of coastal environments from the U.S. Pacific, Gulf of Mexico, ... |
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Coastal Features Extracted from Landsat Satellite Imagery, Delaware Bay, New Jersey to Shinnecock Bay, New York, 2008-2022
This data release serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery from Delaware Bay, New Jersey (NJ) to Shinnecock Bay, New York (NY). A total of 119 images acquired between 2008 and 2022 were analyzed to produce 143 thematic land-cover raster datasets. Water, bare earth (sand), and vegetated land-cover classes were mapped using successive thresholding and masking of the modified normalized difference water index (mNDWI), the normalized difference bare ... |
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Coastal Land-Cover Data Derived from Landsat Satellite Imagery, Delaware Bay, New Jersey to Shinnecock Bay, New York, 2008-2022
This data release serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery from Delaware Bay, New Jersey (NJ) to Shinnecock Bay, New York (NY). A total of 119 images acquired between 2008 and 2022 were analyzed to produce 143 thematic land-cover raster datasets. Water, bare earth (sand), and vegetated land-cover classes were mapped using successive thresholding and masking of the modified normalized difference water index (mNDWI), the normalized difference bare ... |
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Unprocessed aerial imagery from 9 December 2015 coastal survey of Central California.
This is a set of 1132 oblique aerial photogrammetric images and their derivatives, collected from Capitola to Pajaro Dunes with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 January 2016 coastal survey of Central California.
This is a set of 1836 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 February 2016 coastal survey of Central California.
This is a set of 3494 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 2 March 2016 coastal survey of Central California.
This is a set of 1309 oblique aerial photogrammetric images and their derivatives, collected from Santa Cruz to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 March 2016 coastal survey of Central California.
This is a set of 2753 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 15 September 2016 coastal survey of Central California.
This is a set of 1600 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 September 2016 coastal survey of Central California.
This is a set of 1569 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ano Nuevo with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 December 2016 coastal survey of Central California.
This is a set of 3234 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 20 December 2016 coastal survey of Central California.
This is a set of 3036 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 25 January 2017 coastal survey of Central California.
This is a set of 4521 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 22 February 2017 coastal survey of Central California.
This is a set of 4808 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Lucia with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 March 2017 coastal survey of Central California.
This is a set of 5642 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 April 2017 coastal survey of Central California.
This is a set of 5044 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 8 May 2017 coastal survey of Central California.
This is a set of 1975 oblique aerial photogrammetric images and their derivatives, collected from Pedro Point to Sunset Beach with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 May 2017 coastal survey of Central California.
This is a set of 628 oblique aerial photogrammetric images and their derivatives, collected from SeaCliff Beach to Fort Ord with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 17 May 2017 coastal survey of Central California.
This is a set of 3045 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 19 May 2017 coastal survey of Central California.
This is a set of 3164 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 27 May 2017 coastal survey of Central California.
This is a set of 642 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 31 May 2017 coastal survey of Central California.
This is a set of 410 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 13 June 2017 coastal survey of Central California.
This is a set of 757 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 26 June 2017 coastal survey of Central California.
This is a set of 5069 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 December 2017 coastal survey of Central California.
This is a set of 2948 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 21 December 2017 coastal survey of Central California.
This is a set of 2072 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 29 January 2018 coastal survey of Central California.
This is a set of 5365 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 7 March 2018 coastal survey of Central California.
This is a set of 5355 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 28 May 2018 coastal survey of Central California.
This is a set of 3550 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 June 2018 coastal survey of Central California.
This is a set of 1533 oblique aerial photogrammetric images and their derivatives, collected from Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 10 September 2018 coastal survey of Central California.
This is a set of 5846 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 February 2019 coastal survey of Central California.
This is a set of 4734 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 4 March 2019 coastal survey of Central California.
This is a set of 2541 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 11 March 2019 coastal survey of Central California.
This is a set of 1967 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 10 June 2019 coastal survey of Central California.
This is a set of 5042 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 15 October 2019 coastal survey of Central California.
This is a set of 3777 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 31 October 2019 coastal survey of Central California.
This is a set of 1911 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 29 November 2019 coastal survey of Central California.
This is a set of 1782 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Davenport with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 30 November 2019 coastal survey of Central California.
This is a set of 1444 oblique aerial photogrammetric images and their derivatives, collected from Davenport to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 20 January 2020 coastal survey of Central California.
This is a set of 3072 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 25 January 2020 coastal survey of Central California.
This is a set of 1880 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 9 March 2020 coastal survey of Central California.
This is a set of 1979 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 19 March 2020 coastal survey of Central California.
This is a set of 4835 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 19 April 2020 coastal survey of Central California.
This is a set of 2889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 July 2020 coastal survey of Central California.
This is a set of 1890 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 30 September 2020 coastal survey of Central California.
This is a set of 3862 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 15 October 2020 coastal survey of Central California.
This is a set of 1982 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 10 January 2021 coastal survey of Central California.
This is a set of 1896 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 11 January 2021 coastal survey of Central California.
This is a set of 3796 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 29 January 2021 coastal survey of Central California.
This is a set of 4919 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 3 March 2021 coastal survey of Central California.
This is a set of 2049 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 26 March 2021 coastal survey of Central California.
This is a set of 5626 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 September 2021 coastal survey of Central California.
This is a set of 2678 oblique aerial photogrammetric images and their derivatives, collected from PigeonPt to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 December 2021 coastal survey of Central California.
This is a set of 4722 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 20 January 2022 coastal survey of Central California.
This is a set of 2066 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 4 February 2022 coastal survey of Central California.
This is a set of 2269 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 March 2022 coastal survey of Central California.
This is a set of 2098 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 9 June 2022 coastal survey of Central California.
This is a set of 4595 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12-13 September 2022 coastal survey of Central California.
This is a set of 3661 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 1 January 2023 coastal survey of Central California.
This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 January 2023 coastal survey of Central California.
This is a set of 2105 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 16 January 2023 coastal survey of Central California.
This is a set of 2763 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 January 2023 coastal survey of Central California.
This is a set of 5039 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 February 2023 coastal survey of Central California.
This is a set of 2943 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 February 2023 coastal survey of Central California.
This is a set of 1939 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 2 March 2023 coastal survey of Central California.
This is a set of 1839 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 3 March 2023 coastal survey of Central California.
This is a set of 2758 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 13 March 2023 coastal survey of Central California.
This is a set of 2195 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 16 March 2023 coastal survey of Central California.
This is a set of 2915 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 17 March 2023 coastal survey of Central California.
This is a set of 2077 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 April 2023 coastal survey of Central California.
This is a set of 2374 vertical aerial photogrammetric images and their derivatives, collected from Half Moon Bay to Santa Cruz with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 June 2023 coastal survey of Central California.
This is a set of 2123 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 10 October 2023 coastal survey of Central California.
This is a set of 3929 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 11 October 2023 coastal survey of Central California.
This is a set of 4930 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 October 2023 coastal survey of Central California.
This is a set of 2869 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 December 2023 coastal survey of Central California.
This is a set of 4772 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 29 December 2023 coastal survey of Central California.
This is a set of 1821 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 January 2024 coastal survey of Central California.
This is a set of 2876 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 January 2024 coastal survey of Central California.
This is a set of 1965 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 9 February 2024 coastal survey of Central California.
This is a set of 4787 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 February 2024 coastal survey of Central California.
This is a set of 2323 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 24 February 2024 coastal survey of Central California.
This is a set of 3059 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 7 March 2024 coastal survey of Central California.
This is a set of 2161 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 April 2024 coastal survey of Central California.
This is a set of 2286 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 17 June 2024 coastal survey of Central California.
This is a set of 5140 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 August 2024 coastal survey of Central California.
This is a set of 2003 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 January 2023 coastal-landslides survey of Central California.
This is a set of 8762 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 January 2023 coastal-landslides survey of Central California.
This is a set of 11207 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 4-5 November 2020 CZU-fire survey of Central California.
This is a set of 11776 near-nadir aerial photogrammetric images and their derivatives, collected from CZU fire with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 26 January 2017 landslides survey of Central California.
This is a set of 4889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 February 2017 landslides survey of Central California.
This is a set of 5954 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 29 March 2018 coastal survey of Central and southern California.
This is a set of 1160 oblique aerial photogrammetric images and their derivatives, collected from Mud Creek Slide to Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera ... |
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Unprocessed aerial imagery from 13 October 2018 coastal survey of Northern California to Washington.
This is a set of 11805 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Mussel Rock CA with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 19 April 2024 coastal survey of Northern California to Washington.
This is a set of 14032 oblique aerial photogrammetric images and their derivatives, collected from Hoh Head to Cape Mendocino with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 25 September 2016 coastal survey of Oregon and Washington.
This is a set of 1712 oblique aerial photogrammetric images and their derivatives, collected from Cape Falcon to Cascade Head with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 28 September 2017 coastal survey of Oregon and Washington.
This is a set of 2060 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Nestucca River OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 3 August 2020 coastal survey of Oregon and Washington.
This is a set of 2324 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 3 September 2020 coastal survey of Oregon and Washington.
This is a set of 2158 oblique aerial photogrammetric images and their derivatives, collected from NW WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 29 August 2022 coastal survey of Oregon and Washington.
This is a set of 2413 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 June 2023 coastal survey of Oregon and Washington.
This is a set of 10139 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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PCMSC PlaneCam – Field data from periodic and event-response surveys of the U.S. West Coast.
This is an ongoing collection of aerial oblique and near-nadir images, ancillary data, and derivatives, from aerial surveys of coastal and near-coastal environments with a crewed light aircraft using the "PCMSC PlaneCam," a mounted fixed-lens DSLR camera with an attached consumer-grade GPS for time-keeping and approximate position, and a Global Navigation Satellite System (GNSS) for precise positioning. Data are collected and produced primarily for coastal monitoring using structure-from-motion ... |
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Unprocessed aerial imagery from 28 September 2016 coastal survey of Southern California.
This is a set of 2671 oblique aerial photogrammetric images and their derivatives, collected from ptConception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 March 2017 coastal survey of Southern California.
This is a set of 2979 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 27 December 2017 coastal survey of Southern California.
This is a set of 2392 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Santa Barbara with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 13 September 2018 coastal survey of Southern California.
This is a set of 2062 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 May 2020 coastal survey of Southern California.
This is a set of 2167 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 September 2020 coastal survey of Southern California.
This is a set of 1968 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 2 March 2022 coastal survey of Southern California.
This is a set of 2212 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 28 September 2022 coastal survey of Southern California.
This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 2 October 2022 coastal survey of Southern California.
This is a set of 1108 oblique aerial photogrammetric images and their derivatives, collected from Santa Rosa Island with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by ... |
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Unprocessed aerial imagery from 8 March 2023 coastal survey of Southern California.
This is a set of 2006 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 12 October 2023 coastal survey of Southern California.
This is a set of 2013 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Port Hueneme with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 5 January 2024 coastal survey of Southern California.
This is a set of 2061 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 12 February 2024 coastal survey of Southern California.
This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 23 February 2024 coastal survey of Southern California.
This is a set of 2371 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 18 March 2024 coastal survey of Southern California.
This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 23 January 2018 Thomas-fire survey of Southern California.
This is a set of 4838 oblique aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 19 April 2023 thomas-fire survey of Southern California.
This is a set of 3086 vertical aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 4 August 2020 coastal survey of Washington.
This is a set of 645 oblique aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 28 August 2022 coastal survey of Washington.
This is a set of 4116 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 29 August 2022 coastal survey of Washington.
This is a set of 4281 oblique and near nadir aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the ... |
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Unprocessed aerial imagery from 6 July 2024 coastal survey of Washington.
This is a set of 7809 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 31 August 2024 coastal survey of Washington.
This is a set of 6976 oblique aerial photogrammetric images and their derivatives, collected from Juan de Fuca Strait to Grays Harbor with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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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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Coastal Marine Geology Program Video and Photograph Portal
Access to the U.S. Geological Survey (USGS) Coastal and Marine Geology Program’s (CMGP) vast collection of unique and valuable seafloor and coastal imagery is made available in the CMGP Video and Photograph Portal. The portal provides a single location for data discovery and viewing. The CMGP and our research partners invest immense resources collecting, processing, and archiving seafloor and oblique coastal video and photographs. Until the publication of the CMGP Video and Photograph Portal in 2015, only ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - 2005/06/19 through 2005/11/20 Deterministic Scenario
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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - 2015/08/27 through 2015/08/29 Deterministic Scenario
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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - 2015/12/09 through 2015/12/11 Deterministic Scenario
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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 10-Year 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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 10-Year Simulation Without 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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing 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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 2010 Simulation Without 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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Initial Existing Conditions Grid
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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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios 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) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Intermediate-Low Sea Level Rise (SLR) Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios 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) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Low Sea Level Rise (SLR) Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios 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) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Present-Day Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios 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) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Static Intermediate-Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios 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) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Static Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios 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) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Intermediate-Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios 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) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios 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) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Present-Day Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios 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) ... |
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Coastal Features Extracted from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana, 1984-2019
The data release (Bernier, 2021) associated with this metadata record serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery at the northern Chandeleur Islands, Louisiana. To minimize the effects of tidal water-level variations, 75 cloud-free, low-water images acquired between 1984 and 2019 were analyzed. Water, bare earth (sand), vegetated, and intertidal land-cover classes were mapped from Hewes Point to Palos Island using successive thresholding and masking ... |
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Coastal Land-Cover Data Derived from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana, 1984-2019
The data release (Bernier, 2021) associated with this metadata record serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery at the northern Chandeleur Islands, Louisiana. To minimize the effects of tidal water-level variations, 75 cloud-free, low-water images acquired between 1984 and 2019 were analyzed. Water, bare earth (sand), vegetated, and intertidal land-cover classes were mapped from Hewes Point to Palos Island using successive thresholding and masking ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 10-Year 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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 10-Year Simulation Without 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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 2010 Simulation Without 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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Initial Project Conditions Grid
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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Vertical chemical profiles collected across haloclines in the water column of the Ox Bel Ha cave network within the coastal aquifer of the Yucatan Peninsula in January 2015 and January 2016
Natural cave passages penetrating a coastal aquifer in the Yucatan Peninsula (Mexico) were accessed to test the hypothesis that chemoclines associated with salinity gradients (haloclines) within the flooded cave networks of the karst subterranean estuary are sites of methane oxidation. Two field trips were carried out to the fully-submerged cave system located 6.6 km inland from the coastline in January 2015 and January 2016. Vertical chemical profiles across the water column haloclines were obtained using ... |
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Temporal hydrologic and chemical records from the Ox Bel Ha cave network within the coastal aquifer of the Yucatan Peninsula, from January 2015 to January 2016
Natural cave passages penetrating a coastal aquifer in the Yucatan Peninsula (Mexico) were accessed to investigate how regional meteorology and hydrology control methane dynamics in karst subterranean estuaries. Three field trips were carried out in January 2015, June 2015, and January 2016 to obtain year-long high-resolution temporal records of water chemistry and environmental parameters below and above the surface at a site (Cenote Bang) within the Ox Bel Ha cave network. These efforts resulted in ... |
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Geochemical data to characterize physical and chemical properties of the Cenote Bang, a component of the Ox Bel Ha cave network within the subterranean estuary coastal aquifer of the Yucatan Peninsula, from December 2013 to January 2016
Subterranean estuaries extend inland into density-stratified coastal carbonate aquifers that contain a surprising diversity of endemic animals (mostly crustaceans) within a highly oligotrophic environment. How complex ecosystems thrive in this globally-distributed, cryptic habitat (termed anchialine) is poorly understood. The northeastern margin of the Yucatan Peninsula contains over 250 km of mapped, diver-accessible caves passages where previous studies have suggested chemoautotrophic processes are the ... |
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Sonde data to characterize physical and chemical properties of the Cenote Bang, a component of the Ox Bel Ha cave network within the subterranean estuary coastal aquifer of the Yucatan Peninsula, from December 2013 to January 2016
Subterranean estuaries extend inland into density-stratified coastal carbonate aquifers that contain a surprising diversity of endemic animals (mostly crustaceans) within a highly oligotrophic environment. How complex ecosystems thrive in this globally-distributed, cryptic habitat (termed anchialine) is poorly understood. The northeastern margin of the Yucatan Peninsula contains over 250 km of mapped, diver-accessible caves passages where previous studies have suggested chemoautotrophic processes are the ... |
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Hydrological and chemical records from the flooded Ox Bel Ha cave system in the Yucatan Peninsula, Quintana Roo, from August 2014 to January 2015
Natural cave passages penetrating coastal aquifers in the Yucatan Peninsula (Quintana Roo, Mexico) were accessed to investigate how regional meteorology and hydrology control dissolved organic carbon and methane dynamics in karst subterranean estuaries, the region of aquifers where fresh and saline waters mix. Three field trips were carried out in December 2013, August 2014, and January 2015 to obtain 1) physicochemical and 2) geochemical data from the water column and 3) temporal records of water chemistry ... |
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Vegetation biomass and density from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018
Vegetation type and density data were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, and Middle River and the Mokelumne River in March 2018. Vegetation samples were collected by divers, and used to determine dry biomass density. These data were collected as part of a cooperative project, with the USGS California Water Science Center and the California ... |
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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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Subbottom and Sidescan Sonar Data Acquired in 2015 From Grand Bay, Mississippi and Alabama
From May 28 to June 3, 2015, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic evolution and estuarine sediment thickness in Grand Bay, Alabama and Mississippi. Specific objectives were to document the age and accumulation patterns of estuarine sediment to advance our understanding of sediment exchange with the adjacent marsh and sources of sediment to the coastal ocean. This investigation is part of the USGS Sea-level and Storm Impacts on Estuarine Environments ... |
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Radon-222 and Water Column Data Related to Submarine Groundwater Discharge Along the Western Margin of Indian River Lagoon, Florida—September 2016 to July 2017 (ver. 2.0, March 2018)
Indian River Lagoon (IRL) is one of the most biologically diverse estuarine systems in the continental United States, stretching 200 kilometers (km) along the Atlantic coast of central Florida. The width of the lagoon varies between 0.5-9.0 km and is characterized by shallow, brackish waters with significant human development along both shores. Scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center, working in collaboration with the St. Johns River Water ... |
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Radon-222 Time-Series Data Related to Submarine Groundwater Discharge Along the Western Margin of Indian River Lagoon, Florida
Indian River Lagoon (IRL) is one of the most biologically diverse estuarine systems in the continental United States, stretching 200 kilometers (km) along the Atlantic coast of central Florida. The width of the lagoon varies between 0.5–9.0 km and is characterized by shallow, brackish waters with significant human development along both shores. Scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center, working in collaboration with the St. Johns River Water ... |
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Aquatic invertebrate abundance in the Elwha River estuary, Washington, in 2007 and 2013
This portion of the data release presents aquatic invertebrate abundance data from samples collected in the Elwha River estuary, Washington, in 2007 and 2013 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). Replicate benthic samples were collected at 18 locations throughout the estuary complex using a petite Ponar grab sampler (appx. 2400 mL sample) and sorted through a 500-micron sieve. Samples were fixed in 10 percent ... |
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Fish abundance in the Elwha River estuary, Washington, from 2006 to 2014
This portion of the data release presents fish abundance data from samples collected in the Elwha River estuary, Washington, in 2006, 2007, 2013, and 2014 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). We used the Puget Sound beach seining protocol (Simenstad and others, 1991) to sample fish populations in the Elwha River estuary complex. The beach seine was 38 m long x 2 m deep, with a 2 m x 2 m bag in the center of ... |
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Diet of Chinook and coho salmon in the Elwha River estuary, Washington, before and during dam removal
This portion of the data release presents fish diet data from Chinook and coho salmon collected in the Elwha River estuary, Washington, in 2006, 2007, 2013, and 2014 (there are no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). Fish were collected using a beach seine at six locations throughout the estuary. Fish were transferred to buckets containing aerated ambient water and kept cool until handling. We anesthetized fish ... |
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Terrestrial invertebrate abundance in the Elwha River estuary, Washington, in 2007 and 2013.
This portion of the data release presents terrestrial invertebrate abundance data from samples collected in emergent and shrub vegetation along the edge of the Elwha River estuary, Washington, in 2007 and 2013 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). We deployed terrestrial insect fallout traps at ten locations in the east estuary, five replicates each in shrub and emergent (littoral) vegetation habitats. Clear, ... |
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Acidification and Increasing CO2 Flux Associated with Five, Springs Coast, Florida Springs (1991-2014)
Scientists from the South West Florida Management District (SWFWMD) acquired and analyzed over 20 years of seasonally-sampled hydrochemical data from five first-order-magnitude (springs that discharge 2.83 m3 s-1 or more) coastal springs located in west-central Florida. These data were subsequently obtained by the U.S. Geological Survey (USGS) for further analyses and interpretation. The spring study sites (Chassahowitzka, Homosassa, Kings Bay, Rainbow, and Weeki Wachee), which are fed by the Floridan ... |
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Digital Polymerase Chain Reaction (dPCR) Data from the Sediment-Bound Contaminant Resiliency and Response Strategy Pilot Study, Northeastern United States, 2015
Due to the recognized proliferation and spread of antibiotic resistance genes by anthropogenic use of antibiotics for human, agriculture and aquaculture purposes, antibiotic resistance genes have been defined as an emerging contaminant (Laxminarayan and others, 2013; Rodriguez-Rojas and others, 2013; Niu and others, 2016). The presence and spread of these genes in non-clinical and non-agricultural environments has created the need for background investigations to enhance our understanding of the magnitude ... |
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Southeast Florida and Florida Keys Antibiotic Resistance Study
The prevalence of antibiotic resistance genes in microbial communities from sewage wastewater streams and from offshore marine sediments in the vicinity of sewage wastewater outfalls in Southeast Florida was investigated from June 2018 to March 2019. Sediment and wastewater samples were analyzed for 15 different antibiotic resistant gene targets via polymerase chain reaction (PCR) presence/absence assays in Southeast Florida coral reef environments. Data collected from five sites (Broward North Wastewater ... |
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Presence/absence Quantitative Polymerase Chain Reaction (qPCR) Data from the Sediment-Bound Contaminant Resiliency and Response Strategy Pilot Study, Northeastern United States, 2015
Due to the recognized proliferation and spread of antibiotic resistance genes by anthropogenic use of antibiotics for human, agriculture and aquaculture purposes, antibiotic resistance genes have been defined as an emerging contaminant (Laxminarayan and others, 2013; Rodriguez-Rojas and others, 2013; Niu and others, 2016). The presence and spread of these genes in non-clinical and non-agricultural environments has created the need for background investigations to enhance our understanding of the magnitude ... |
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DNA microsatellite markers for Mustard Hill Coral (Porites astreoides) from the Florida Keys Reef Tract
This data set includes: (1) allele sizes of 11 previously published microsatellites (Kenkel and others, 2013; Shearer and Coffroth, 2004) for 39 individuals of mustard hill coral, Porites astreoides (mustard hill coralP. astreoides) collected in the Spring of 2017 from four locations in the Florida Keys Reef Tract (FKRT): Fowey Rocks, Crocker Reef, Sombrero Reef and Pulaski Shoal and (2) the deoxyribonucleic acid (DNA) concentration of the extracted DNA prior to polymerase chain reaction (PCR) reactions for ... |
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Cold-water coral microbiomes (Acanthogorgia spp. Desmophyllum dianthus, and Lophelia pertusa) from the Gulf of Mexico and Atlantic Ocean off the southeast coast of the United States: raw sequencing data
The files provided in this U.S. Geological Survey (USGS) data release (Kellogg and Voelschow, 2021) are the raw DNA sequence files referenced in the associated journal article (Kellogg and Pratte, 2021) entitled, “Unexpected diversity of Endozoicomonas in deep-sea corals.”. This dataset, PRJNA699458_16S-V3V4_raw_data_1.zip, represents the 16S rRNA gene amplicon surveys of 28 samples of deep-sea corals, including Acanthogorgia aspera (n=5), Acanthogorgia spissa (n=4), Desmophyllum dianthus (n=7), and ... |
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Testing Treatments Against Parasitic Scuticociliate (Philaster apodigitiformis) that Causes Mass Mortality Among Sea Urchins (Diadema antillarum) - Results
The information contained in this data release are the results observed and collected during an experiment that tested the efficacy of nine compounds (2’4’ dihydroxychalcone, bithionol sulfoxide, carnidazole, furaltadone, plumbagin, oxyclozanide, quinacrine, tomatine, and toltrazuril), previously found to be effective against the parasitic ciliate family Philasteridae (Iglesias and others, 2002; Sueiro and others, 2022). One commercially available product (Kordon Ich Attack) was also tested, however was ... |
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Orthoimagery of Eastern Dry Rocks coral reef, Florida, 2021
A seabed orthoimage was developed 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. The orthoimage covers a rectangular area of seafloor approximately 800x160 meters (0.12 square kilometers) in size, and it was created using image-mosaicking methods and saved as a tiled, 5-mm resolution raster. |
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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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GNSS locations of seabed images collected at Eastern Dry Rocks coral reef, Florida, 2021
This text file (SQUID5_EDR_2021_Image_Locations.txt) provides the GNSS antenna location for underwater images collected at Eastern Dry Rocks coral reef, near Key West, Florida, in May 2021, using the SQUID5 Structure-from-Motion (SfM) system, a towed-surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey. The GNSS antenna location for the time of each image capture is presented with greater precision than is stored in the individual image's EXIF header due to ... |
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Point cloud data of Eastern Dry Rocks coral reef, Florida, 2021
A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Eastern Dry Rocks coral reef near Key West, Florida, in May 2021 using the SQUID-5 camera system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, RGB colors, Metashape-computed confidence values, and a two-class classification ('unclassified' and 'low noise') derived from the confidence values. LAS (and its compressed form, LAZ) is an open format ... |
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Overlapping seabed images collected at Eastern Dry Rocks coral reef, Florida, 2021
Underwater images totaling 138,733 in number were collected at Eastern Dry Rocks coral reef, near Key West, Florida, in May 2021, using the SQUID5 Structure-from-Motion (SfM) system, a towed-surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey. The images are organized in zipped files grouped by survey line. The SQUID-5 records images as TIFF (.tif) format to maintain the highest resolution and bit depth. Each image includes EXIF metadata, containing GNSS ... |
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Reef-census data from Buck Island Reef
In July of 2016, Florida Institute of Technology researchers, in collaboration with the U.S. Geological Survey (USGS), conducted reef-census surveys at 54 sites around Buck Island Reef National Monument, St. Croix, U.S. Virgin Islands. The sites are divided across two reef sectors (North and South) and three reef habitats (fore reef, reef crest, and back reef). The surveys provided data on the percent coverage of corals and other benthic taxa, and abundance of bioeroding parrotfishes and urchins. |
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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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GNSS locations of seabed images collected at Looe Key, Florida, 2021
The text file "SQUID5_LKR_2021_Image_Locations.txt" provides the GNSS antenna location for underwater images collected at Looe Key, Florida, in July 2021, using the SQUID5 Structure-from-Motion (SfM) system, a towed-surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey. The GNSS antenna location for the time of each image capture is presented with greater precision than is stored in the individual image EXIF headers due to decimal place limitations of the EXIF ... |
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Orthoimagery of Looe Key, Florida, 2021
A seabed orthoimage was developed 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. The orthoimage covers a rectangular area of seafloor approximately 720x100 meters (0.072 square kilometers) in size. It was created using image-mosaicking methods and saved as a tiled GeoTIFF raster at 5-millimeter resolution. |
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Point cloud data of Looe Key, Florida, 2021
A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Looe Key, 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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Overlapping seabed images collected at Looe Key, Florida, 2021
A total of 94,567 underwater images were collected at Looe Key, Florida, in July 2021, using the SQUID5 Structure-from-Motion (SfM) system, a towed-surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey. The images are organized in zipped files grouped by survey line. The SQUID-5 records images in the Tagged Image File Format format to maintain the highest resolution and bit depth. Each image includes Exchangeable Image File (EXIF) metadata, containing Global ... |
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Underwater temperature on off-shore coral reefs of the Florida Keys, U.S.A. (Version 8)
The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ... |
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Cold-water coral microbiomes (Anthothela spp.) from Baltimore and Norfolk Canyons: raw and processed data
The files included in this data release are the raw and processed deoxyribonucleic acid (DNA) sequence files referenced in the journal article by Lawler and others (2016) entitled “Coral-Associated Bacterial Diversity is Conserved Across Two Deep-Sea Anthothela Species”. They represent a 16S rRNA gene amplicon survey of cold-water corals (Anthothela spp.) microbiomes completed using Roche 454 pyrosequencing with titanium reagents. The samples used in this study were collected from cold-water corals ... |
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Uranium-Thorium Ages for Late Holocene Corals from the Southeast Florida Nearshore Ridge Complex
This data release (Modys and others, 2023a) compiles Uranium-Thorium (U-Th) dating data for late Holocene coral samples collected from the Nearshore Ridge Complex (NRC) off Pompano Beach, Southeast Florida (SEFL). The samples were collected under Scientific Activity Licenses (SAL) from the Florida Fish and Wildlife Conservation Commission (SAL-18-1659A-SRP) and with permission from Broward County Environmental Protection and Growth Management. |
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2022-334-FA_BocaChica_Polecam_Imagery: High-resolution Geophysical and Imagery Data Collected in November 2022 Offshore of Boca Chica Key, FL
Underwater images totaling 23,948 in number were collected offshore of Boca Chica Key, the Florida Keys , during November 2022, using the Polecam system developed by the U.S. Geological Survey (USGS). The Polecam system is a single downward-looking underwater Teledyne FLIR camera with a Computar V1228-MPY lens and with a rigidly-attached Global Navigation Satellite System (GNSS) antenna mounted directly above the camera's central axis. The pole camera was attached to the gunwale of the USGS research vessel ... |
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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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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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