Biological and physical processes

All continuing activities, functions, and phenomena associated with organisms and non-living matter.
This category is also used for bioenergetic processes.
Subtopics:
Coastal processes (1555 items)
Fires (20 items)
Geologic processes (850 items)
Ocean processes (403 items)

2374 results listed by similarity [list alphabetically]
AllScenarios_Bin1thru18_SSC: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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AllScenarios_Initial_and_Final_Bed_Elevations: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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CoconutIsland_2023_MBES: High-resolution Geophysical and Imagery Data Collected in May 2023 Near Fort Hase, Marine Corps Base Hawaii

An Ellipsoidally Referenced Survey (ERS) using a Norbit Winghead multibeam echosounder, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Coconut Island, on the island of Oahu, May 7, 2023. This dataset, CoconutIsland_2023_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 0.25 meter (m) bathymetric grid and the dataset CoconutIsland_2023_MBES_Backscatter.zip includes the acoustic backscatter intensity ...

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FtHase_2023_MBES: High-resolution Geophysical and Imagery Data Collected in May 2023 Near Fort Hase, Marine Corps Base Hawaii

An Ellipsoidally Referenced Survey (ERS) using a Norbit Winghead multibeam echosounder, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Fort Hase Marine Corps Base Hawaii (MCBH), on the island of Oahu, May 4-12, 2023. This dataset, FtHase_2023_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid and the dataset FtHase_2023_MBES_Backscatter.zip includes the acoustic backscatter ...

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AllScenarios_Sediment_Fluxes: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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AllScenarios_Spatial_Flow: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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Cape Canaveral tracklines of geophysical data collected in 2016 by Coastal Carolina University

A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data.

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AllScenarios_Spatial_Waves: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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GrandBayModel_InputBathymetry: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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GrandBay_ValidationPeriod_Wave_WaterLevel: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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BocaChica_2022_MBES: High-resolution Geophysical and Imagery Data Collected in November 2022 Offshore of Boca Chica Key, FL

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Boca Chica Key, the Florida Keys, from November 8-13, 2022. This dataset, BocaChica_2022_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid, and the dataset BocaChica_2022_MBES_Backscatter.zip ...

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Tyndall_2022_MBES: High-resolution Geophysical Data Collected in June 2022 Near Tyndall Air Force Base, Panama City, Florida

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Tyndall Air Force Base, Panama City, Florida, from June 20-30, 2022. This dataset, Tyndall_2022_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid, and the dataset Tyndall_2022_MBES_Backscatter.zip ...

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Sediment grain-size distributions from vibracores collected in Searsville Lake, Jasper Ridge Biological Preserve, Stanford, California

This portion of the data release presents sediment grain-size data from vibracores collected from Searsville Lake, Jasper Ridge Biological Preserve, Stanford, California in October 2018 (USGS Field Activity 2018-682-FA). In total, 36 samples were subsampled from two vibracores: JRBP2018-VC01A and JRBP2018-VC01B. The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. The grain-size data are provided in a ...

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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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Sonde data to characterize physical and chemical water column properties of flooded caves (Ox Bel Ha and Cenote Crustacea) within the coastal aquifer of the Yucatan Peninsula, Quintana Roo, from December 2013 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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2005 EAARL Fire Island Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Fire Island USGS ...

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2005 Padre Island USGS EAARL Lidar-derived dune crest, toe and shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Experimental ...

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2006 FEMA Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2006 Federal Emergency ...

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2007 Northeast Barrier Islands USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 Northeast Barrier ...

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2007 South Florida FDEM Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 Florida Division of ...

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2007 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 U.S. Army Corps of ...

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September 2007 Northern Gulf of Mexico USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 Northern Gulf of ...

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National Assessment of Hurricane-Induced Coastal Erosion Hazards: Puerto Rico

This dataset contains information on the probabilities of hurricane-induced erosion (collision, inundation and overwash) for each 100-meter (m) section of the Puerto Rico coast for category 1-5 hurricanes. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the direct landfall of category 1-5 hurricanes. Hurricane-induced water levels, due to both surge and waves, are ...

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2008 USGS Post-Hurricane Ike Texas Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 USGS Post-Hurricane ...

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2008 North Carolina and Virginia NOAA/NGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Atlantic Coast ...

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2008 Assateague Island USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Assateague Island ...

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2009 Cape Canaveral USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Cape Canaveral ...

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2009 North Carolina USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 U.S. Army Corps of ...

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2009 Florida USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Florida U.S. Army ...

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2009 Post-Nor’Ida USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Post-Nor’Ida USGS ...

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2010 Northeast Atlantic USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Northeast Atlantic ...

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2010 Southeast Atlantic USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Southeast Atlantic ...

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2010 Virginia USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Virginia U.S. Army ...

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2010 New York USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 New York U.S. Army ...

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2010 New Jersey USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 New Jersey U.S. ...

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2010 Delaware USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Delaware U.S. Army ...

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2010 Maryland USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Maryland U.S. Army ...

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Wave model grids and bathymetry for the central Beaufort Sea coast, Alaska

The required grid and bathymetry files to run a nested spectral wave model (Simulating Waves WAves Nearshore [SWAN]; Booij and others, 1999) for the central Beaufort Sea coast of Alaska are provided. A three-level SWAN nesting grid with grid resolutions of 5000 meters, 1000 meters, and 200 meters for the overall, intermediate and detail grids, respectively (see included Browse Graphic) has been developed. For this purpose, available local bathymetry (Coastal Frontiers Corporation, 2014; Kasper and others, ...

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Summary statistics for the central Beaufort Sea coast, Alaska

A nested spectral wave model (Simulating Waves WAves Nearshore [SWAN]; Booij and others, 1999) was deployed for the central Beaufort Sea coast of Alaska to simulate waves for the period from 1979 to 2019. Results in the form of spatial summary statistics, describing wave parameters, wind speed and sea-ice area cover for the intermediate grid (see Overview Image on main page of data release), are provided. Further information can be found in Nederhoff and others (2021).

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2010 Assateague Island National Seashore USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Assateague Island ...

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July 2010 Dauphin Island USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Dauphin Island U.S. ...

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2011 USGS New York Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 Atlantic Coast ...

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2011 East Coast New York/New Jersey NOAA/NGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 East Coast New York ...

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2012 Post-Hurricane Sandy Fire Island, New York Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ...

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2012 Post-Hurricane Sandy Northeast Atlantic Coast USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post ...

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2012 Post-Sandy New York and New Jersey USACE NCMP Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Sandy New York ...

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Orthomosaic representing Head of the Meadow Beach, Truro on March 10, 2022

These data map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA, providing updated regional context for the 2019 CoastCam installation. CoastCam CACO-01 are two video cameras aimed at the beach that view the coast shared by beachgoers, shorebirds, seals, and sharks. These data were collected as part of field activity 2022-015-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region. In March 2022, U.S. Geological Survey and Woods ...

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2012 Pre-Hurricane Sandy Fire Island National Seashore, USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ...

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2012 Pre-Sandy New York and New Jersey USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Pre Hurricane Sandy ...

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2012 Post-Hurricane Sandy New Jersey USGS EAARL-B Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ...

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2013-2014 Northeast USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013-2014 Post� ...

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2013 NOAA Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 National Oceanic ...

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2013 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 U.S. Army Corps of ...

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2013 USACE NAE Topobathy Lidar: Maine Point Cloud files with Orthometric Vertical Datum North American Vertical Datum of 1988 (NAVD88) using GEOID12B

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 Gulf Coast USGS ...

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2013 Maine USACE/NAE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 Maine United States ...

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2014 East Coast Rhode Island NOAA/NGS ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Sandy

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 East Coast Rhode ...

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2014 East Coast Maine USACE/NAE ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Sandy

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 East Coast Maine ...

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2015 USACE Florida Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2015 U.S. Army Corps of ...

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2017 USGS Lidar: Chenier Plain, LA Point Cloud files with Orthometric Vertical Datum North American Vertical Datum of 1988 (NAVD88) using GEOID12B

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 Gulf Coast USGS ...

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Orthomosaic representing Marconi Beach, Wellfleet, MA March 11, 2022

The data in this release map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide updated environmental context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2022-014-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-02, which are two video cameras aimed at the ...

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2016 Florida East Coast USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2016 U.S. Army Corps of ...

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2016 USACE Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2016 U.S. Army Corps of ...

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2017 East Coast USACE/FEMA ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Irma

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2017 Atlantic Coast ...

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2018 USGS Florida Panhandle Post-Michael Lidar-derived Dune Crest, Toe, and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2018 United States Army ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2019-08-30 to 2019-09-02, Pre-Hurricane Dorian

Digital elevation models (DEMs) were created from aerial imagery collected between August 30 and September 2, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions prior to Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface before Hurricane Dorian and were created to document inter-annual changes in ...

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RGB-averaged orthoimagery of coastal North Carolina, from 2019-08-30 to 2019-09-02, Pre-Hurricane Dorian

Orthoimages were created from aerial imagery collected between August 30 and September 2, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RBG-averaged orthoimages were created to document ground conditions prior to Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RBG-averaged orthoimages help researchers estimate the land surface before Hurricane Dorian and were created to document ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian

Digital elevation models (DEMs) were created from aerial imagery collected between September 08 and September 13, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions post-Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface after Hurricane Dorian and were created to document inter-annual changes in ...

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RGB-averaged orthoimagery of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian

RGB-averaged ortho products were created from aerial imagery collected between September 8 and 13, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RBG-averaged orthoimages were created to document ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RBG-averaged orthoimages help researchers estimate the land surface after Hurricane Dorian and were created to ...

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1998 East Coast NASA/NOAA/USGS Winter ATM Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Atlantic Coast ...

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1998 Atlantic coast NASA/NOAA/USGS Spring ATM Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Atlantic Coast ...

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RGB-averaged orthoimagery of coastal North Carolina, on 2019-10-11, one-month post-Hurricane Dorian

RGB-averaged orthoimages were created from aerial imagery collected on October 11, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RBG-averaged orthoimages were created to document ground conditions one-month after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RBG-averaged orthoimages help researchers estimate the land surface after Hurricane Dorian and were created to document ...

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Digital elevation models (DEMs) of coastal North Carolina, on 2019-11-26, two-months Post-Hurricane Dorian

Digital elevation models (DEMs) were created from aerial imagery collected November 26, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions two-months after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface one-month post-Hurricane Dorian and were created to document inter-annual changes in ...

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RGB-averaged orthoimagery of coastal North Carolina, on 2019-11-26, two-months Post-Hurricane Dorian

RGB-averaged orthoimages were created from aerial imagery collected on November 26, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RBG-averaged orthoimages were created to document ground conditions two-months after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RBG-averaged orthoimages help researchers estimate the land surface after Hurricane Dorian and were created to document ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2020-02-08 to 2020-02-09

Digital elevation models (DEMs) were created from aerial imagery collected February 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers document inter-annual changes in shoreline position and coastal morphology in response to storm events using ...

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RGB-averaged orthoimagery of coastal North Carolina, from 2020-02-08 to 2020-02-09

RGB-averaged orthoimages were created from aerial imagery collected February 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RGB-averaged orthoimages were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RGB-averaged orthoimages help researchers document inter-annual changes in shoreline position and coastal morphology in ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2020-05-08 to 2020-05-09

Digital elevation models (DEMs) were created from aerial imagery collected May 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers document inter-annual changes in shoreline position and coastal morphology in response to storm events using aerial ...

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1998 Southeast ATM Lidar-derived dune crest, toe and shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Southeast USGS/NASA ...

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1999 Atlantic Coast NASA/NOAA/USGS ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Floyd

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1999 Atlantic Coast ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2015 Offshore of Dauphin Island, Alabama

From September 16 through 23, 2015, researchers from the U.S. Geological Survey (USGS) conducted an offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Dauphin Island, Alabama (AL). The Alabama Barrier Island Restoration Feasibility Study project objective includes the investigation of nearshore geologic controls on surface morphology. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation files, geographic ...

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2015-330-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2015-330-FA Offshore of Dauphin Island, Alabama, September 2015

From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a point dataset of field activity number (FAN) 2015-330-FA chirp subbottom profile 1,000-shot-interval locations.

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2015-330-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2015-330-FA Offshore of Dauphin Island, Alabama, September 2015

From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a point dataset of field activity number (FAN) 2015-330-FA chirp subbottom profile start of trackline locations.

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2015-330-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2015-330-FA Offshore of Dauphin Island, Alabama, September 2015

From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a line dataset of field activity number (FAN) 2015-330-FA chirp tracklines.

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2018 South Texas USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline derived from the 2018 United States ...

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2018 Puerto Rico USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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Digital elevation models of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016

This part of the data release presents digital elevation models (DEMs) spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the DEMs were created, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were collected ...

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Orthoimagery of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016

This part of the data release presents orthoimagery spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the orthoimages were created, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were collected with precise ...

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Elevation point clouds of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016

This part of the data release presents georeferenced elevation point clouds spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the point clouds were derived, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were ...

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Tile index for Alaska coastal orthoimagery and elevation data: Icy Cape to Cape Prince of Wales, 2016

This part of the data release presents a shapefile that includes a spatial index of orthoimagery and elevation data describing the Alaskan coastline from Icy Cape to Cape Prince of Wales. The data products referenced in this index include orthoimagery, digital surface models, and elevation point clouds which were generated from aerial imagery using structure-from-motion methods. Fairbanks Fodar, a contracted mapping service, collected the aerial imagery in 2016 and created all of the data products ...

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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 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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Elevation data collected in 2009 on the beach and foreshore in the vicinity of Wainwright, Alaska

Beach and foreshore elevation data were collected in the vicinity of Wainwright, Alaska. The area from the mouth of the Kuk River to about 8 km to the northeast was measured in August 2009. The area from the mouth of the Kuk River to about 5 km to the northeast was measured in October 2009. The elevation data were collected with Real-Time Kinematic (RTK) Global Positioning System (GPS) systems mounted on all-terrain vehicles. The GPS sampling rate was 1 Hz with vehicle speeds maintained at less than 15 km ...

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Vertical land motion rates for the years 2007 to 2020 for the U.S. Atlantic coast

This dataset contains rates of land subsidence and uplift derived from Sentinel-1A/B (2015-2020) and ALOS (2007-2011) synthetic aperture radar (SAR) satellites, at approximately 50-75 m resolution and mm-level precision for the U.S. Atlantic coast except for the states of North and South Carolina. The data consist of vertical land motion (VLM) rates and the 1-sigma error in land motion rates and are available as csv files. Similar vertical land motion rates for North Carolina and South Carolina are ...

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Vertical land motion rates for the years 2007 to 2020 for the North and South Carolina coasts

Rates of land subsidence and uplift for the North and South Carolina coasts are derived from Sentinel-1A/B (2015-2020) and ALOS (2007-2011) synthetic aperture radar (SAR) satellites, at approximately 50-75 m resolution and mm-level precision. The data consist of vertical land motion (VLM) rates and the 1-sigma error in land motion rates and are available as csv files.

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Computed tomography (CT) scans of vibracores collected offshore central California, during field activity 2019-651-FA

This dataset includes computed tomography (CT) scans of sediment cores collected offshore central California in the vicinity of Morro Bay. These data were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Multi-sensor core logger (MSCL) data of vibracores collected offshore central California, during field activity 2019-651-FA

This dataset includes multi-sensor core logger (MSCL) data from sediment cores collected offshore central California in the vicinity of Morro Bay. The sediment cores were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Grain-size data of vibracores collected offshore central California, during field activity 2019-651-FA

This dataset includes grain-size data of sediment cores collected offshore central California in the vicinity of Morro Bay. These data were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Photographs of vibracores collected offshore central California, during field activity 2019-651-FA

This dataset includes photographs of sediment cores collected offshore central California in the vicinity of Morro Bay. These data were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Mineralogical point-count data from vibracores collected offshore central California, during field activity 2019-651-FA

This dataset includes mineralogical point-count data from sediment cores collected offshore central California in the vicinity of Morro Bay. These data were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Hydrodynamic and sediment transport model of the mouth of the Columbia River, Washington and Oregon, 2020-2021

A three-dimensional hydrodynamic and sediment transport model application of the mouth of the Columbia River (MCR) was constructed using the Delft3D4 (D3D) modeling suite (Deltares, 2021) to simulate water levels, flow, waves, and sediment transport for time period of September 22, 2020, to March 10, 2021. The model was used to predict the dispersal of sediment from a submerged, nearshore berm composed of sediment that was dredged from the entrance to the MCR navigation channel and placed on the northern ...

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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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Model parameter input files to compare effects of stream discharge scenarios on sediment deposition and concentrations around coral reefs off west Maui, Hawaii

This dataset consists of physics-based Delft3D model and Delwaq model input files used in modeling sediment deposition and concentrations around the coral reefs of west Maui, Hawaii. The Delft3D models were used to simulate waves and currents under small (SC1) and large (‘SC2’) wave conditions for current stream discharge (‘Alt1’) and stream discharge with watershed restoration (‘Alt3’). Delft3D model results were subsequently used as forcing conditions for Delwaq models to simulate sediment ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Initial_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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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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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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Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2008

Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. To re-establish a population at Assateague Island National Seashore (ASIS), seabeach amaranth cultivars were planted by ASIS natural resources staff for three growing seasons from 1999 to 2001 and have been monitored since 2001. Characteristics of favorable seabeach amaranth locations were assessed by sampling barrier island and habitat characteristics at sites ...

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Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2010

Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. To re-establish a population at Assateague Island National Seashore (ASIS), seabeach amaranth cultivars were planted by ASIS natural resources staff for three growing seasons from 1999 to 2001 and have been monitored since 2001. Characteristics of favorable seabeach amaranth locations were assessed by sampling barrier island and habitat characteristics at sites ...

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Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2014

Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. To re-establish a population at Assateague Island National Seashore (ASIS), seabeach amaranth cultivars were planted by ASIS natural resources staff for three growing seasons from 1999 to 2001 and have been monitored since 2001. Characteristics of favorable seabeach amaranth locations were assessed by sampling barrier island and habitat characteristics at sites ...

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Model parameter input files to compare the influence of coral reef carbonate budgets on alongshore variations in wave-driven total water levels on Buck Island Reef National Monument

A set of physics-based XBeach Non-hydrostatic hydrodynamic model simulations (with input files here included) were used to evaluate how varying carbonate budgets, and thus coral reef accretion and degradation, affect alongshore variations in wave-driven water levels along the adjacent shoreline of Buck Island Reef National Monument (BUIS) for a number of sea-level rise scenarios, specifically during extreme wave conditions when the risk for coastal flooding and the resulting impact to coastal communities is ...

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Attendee Survey Results from the April and May 2020 Gulf Islands National Seashore Workshop

In early 2020, scientists gathered to advance sediment budget modeling efforts by conducting a “Needs Assessment Workshop” for the Gulf Island National Seashore (GINS) to understand the coastal processes affecting island resiliency. The “Gulf Islands Sediment Budget Needs Assessment Workshop” was held, virtually, April 23–24 and May 27–28, 2020. The workshop series was organized by researchers from North Carolina State University in collaboration with National Park Service (NPS) and U.S. ...

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Ground Penetrating Radar and Global Positioning System Data Collected from Fire Island, New York, March-April 2021

Fire Island, New York (NY) is a 50-kilometer (km) long barrier island system fronting the southern coast of Long Island, NY with relatively complex geology. In 2016, the U.S. Geological Survey (USGS) conducted ground penetrating radar (GPR) surveys and sediment sampling at Fire Island to characterize and quantify spatial variability in the subaerial geology (Forde and others, 2018; Buster and others, 2018). These surveys, in combination with historical data, allowed for a preliminary reconstruction of the ...

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Digital elevation models (DEMs) of coastal North Carolina, on 2019-10-11, one month Post-Hurricane Dorian

Digital elevation models (DEMs) were created from aerial imagery collected October 11, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions one-month after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface one-month post-Hurricane Dorian and were created to document inter-annual changes in ...

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Barrier island geomorphology and seabeach amaranth metrics at 50-m alongshore transects, and 5-m cross-shore points for 2008 — Assateague Island, MD and VA.

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for developing approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as piping plover ...

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Nearshore water level, tide, and non-tidal residual future projections (2016-2050) for the U.S. Atlantic coast

A dataset of modeled nearshore water levels (WLs) was developed for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields. Water level outputs were extracted from the global grid at approximately 20 km resolution along the Atlantic coastline. These data were then ...

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Nearshore water level, tide, and non-tidal residual hindcasts (1979-2016) for the U.S. Atlantic coast

A dataset of modeled nearshore water levels (WLs) was developed for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields -. Water level outputs were extracted from the global grid at approximately 20 km resolution along the coastlines. These data were then statistically ...

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Nearshore parametric wave setup future projections (2020-2050) for the U.S. Atlantic coast

This dataset presents alongshore wave setup timeseries for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to ...

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Nearshore parametric wave setup hindcast data (1979-2019) for the U.S. Atlantic coast

This dataset presents alongshore wave setup timeseries for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to ...

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Nearshore water level, tide, and non-tidal residual future projections (2016-2050) for the North and South Carolina coasts

A dataset of modeled nearshore water levels (WLs) was developed for the North and South Carolina coastlines. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields. Water level outputs were extracted from the global grid at approximately 20 km resolution along the southeast Atlantic coastline. These data were then statistically downscaled using a ...

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Nearshore water level, tide, and non-tidal residual hindcasts (1979-2016) for the North and South Carolina coasts

A dataset of modeled nearshore water levels (WLs) was developed for the North and South Carolina coastlines. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields -. Water level outputs were extracted from the global grid at approximately 20 km resolution along the coastlines. These data were then statistically downscaled using a signal-specific ...

Info
Nearshore parametric wave setup future projections (2020-2050) for the North and South Carolina coasts

This dataset presents alongshore wave setup timeseries for the North and South Carolina coastlines. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at ...

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Nearshore parametric wave setup hindcast data (1979-2019) for the North and South Carolina coasts

This dataset presents alongshore wave setup timeseries for the North and South Carolina coastlines. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at ...

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OpenFOAM models of low- and high-relief sites from the coral reef flat off Waiakane, Molokai, Hawaii

OpenFOAM Computational Fluid Dynamics (CFD) models were developed to simulate wave energy dissipation across natural rough reef surfaces on the reef flat off Waiakane, Molokai, Hawaii, to understand this process in the context of reef restoration design. A total of 140 models were developed (70 per low- and 70 per high-bed-relief domains). Models were calibrated and validated with oceanographic datasets collected in 2018. This data release presents the 140 model scenarios that can be readily input into ...

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Baseline for the Virginia coastal region, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Salinity_GBI_frontal_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_GBI_frontal: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_GBI_tropical_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_GBI_tropical: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_all_frontal_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_all_frontal: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_all_tropical_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_all_tropical: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_na_frontal_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_na_frontal: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_na_tropical_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Salinity_na_tropical: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Velocity_GBI_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Velocity_GBI: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Velocity_all_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Velocity_all: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Info
Velocity_na_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Info
Velocity_na: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Water_Level_GBI_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Water_Level_GBI: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Info
Water_Level_all_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Water_Level_all: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Info
Water_Level_na_SLR: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Water_Level_na: Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary: model input and results

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

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Shore Proximal Marsh Sediment Deposition and Ancillary Data From Grand Bay National Estuarine Research Reserve, Mississippi: grain size analysis

To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ...

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RBR sensor pressure and tidal data for two sites in the coastal marsh at Grand Bay National Estuarine Research Reserve, Mississippi, from April 2019 through January 2020

To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ...

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RBR sensor wave data for two sites in the coastal marsh at Grand Bay National Estuarine Research Reserve, Mississippi, from April 2019 through January 2020

To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ...

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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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Time series for the central Beaufort Sea coast, Alaska

Time series output from a spectral wave model (Simulating Waves WAves Nearshore [SWAN]; Booij and others 1999), implemented for the central Beaufort Sea coast of Alaska from 1979 to 2019, are provided. The variables include significant wave heights, mean wave periods, mean wave directions, wave steepness, and orbital velocities. Additionally, water depths, x (east-west) and y (north-south) components of the wind, and sea ice concentrations are provided. Further information can be found in Nederhoff and ...

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Orthomosaic representing Marconi Beach, Wellfleet, MA on March 22, 2023

The data in this release re-map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide updated environmental context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2022-014-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-02, which are two video cameras aimed at the ...

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Orthomosaic representing Head of the Meadow Beach, Truro, MA on March 10, 2023

The data in this release re-map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide updated environmental context for the 2020 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2022-015-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-01, which are two video cameras aimed ...

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Baseline for the South Carolina coastal region, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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SC Bias Feature – Feature class containing South Carolina proxy-datum bias information to be used in the Digital Shoreline Analysis System

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Intersects for the coastal region of South Carolina generated to calculate long-term shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Intersects for coastal region of South Carolina generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long-term shoreline change rate transects for the South Carolina coastal region, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Short-term shoreline change rate transects for the South Carolina coastal region using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2010 lidar-derived mean high water shoreline for the coast of South Carolina

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017-2018 lidar-derived mean high water shoreline for the coast of South Carolina

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Intrinsic and Extrinsic Calibration Data From USGS CoastCam deployed at Madeira Beach, Florida

A digital video camera was installed at Madeira Beach, Florida (FL) and faced west along the beach. Every hour during daylight hours, daily from 2017 to 2022, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological Survey (USGS) research project to study the beach and ...

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Imagery from USGS CoastCam deployed at Madeira Beach, Florida

A digital video camera was installed at Madeira Beach, Florida (FL) and faced west along the beach. Every hour during daylight hours, daily from 2017 to 2022, the camera collected raw video and produced snapshots and time-averaged image products. The images included in this data release were collected from January 21, 2017, to December 31, 2017. The camera is part of a U.S. Geological Survey (USGS) research project to study the beach and nearshore environment. USGS researchers analyzed the imagery collected ...

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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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Radiocarbon age data from vibracores collected offshore central California, during field activity 2019-651-FA (ver 2.0, August 2023)

This dataset includes radiocarbon age data from sediment cores collected offshore central California in the vicinity of Morro Bay. These data were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Coordinates of vibracores collected offshore central California, during field activity 2019-651-FA (ver 2.0, August 2023)

This dataset includes coordinate information for sediment cores collected offshore central California in the vicinity of Morro Bay. These data were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Optically stimulated luminescence (OSL) age data from vibracores collected offshore central California, during field activity 2019-651-FA (ver 2.0, August 2023)

This dataset includes optically stimulated luminescence (OSL) age data from sediment cores collected offshore central California in the vicinity of Morro Bay. These data were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Orthomosaic representing Head of the Meadow Beach, Truro from images collected during field activity 2021-014-FA on February 4, 2021

These data map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA, providing updated regional context for the 2019 CoastCam installation. CoastCam CACO-01 are two video cameras aimed at the beach that view the coast shared by beachgoers, shorebirds, seals, and sharks. These data were collected as part of field activity 2021-014-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region. In February 2021, U.S. Geological Survey and ...

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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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Baseline for the North Carolina coastal region from Cape Hatteras to Cape Lookout (NCcentral)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the central coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long and short-term shoreline intersect points for the central coast of North Carolina (NCcentral), calculated using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long and short-term shoreline change rate transects for the central North Carolina coastal region (NCcentral), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017 lidar-derived mean high water shoreline for the coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Baseline for the North Carolina coastal region from the Virginia border to Cape Hatteras (NCnorth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the northern coast of North Carolina from the Virginia border to Cape Hatteras (NCnorth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long and short-term shoreline intersect points for the northern coast of North Carolina (NCnorth), calculated using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long and short-term shoreline change rate transects for the northern North Carolina coastal region (NCnorth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017 lidar-derived mean high water shoreline for the coast of North Carolina from the Virginia border to Cape Hatteras (NCnorth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Baseline for the North Carolina coastal region from Cape Lookout to Cape Fear (NCsouth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the southern coast of North Carolina from Cape Lookout to Cape Fear (NCsouth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long and short-term shoreline intersect points for the southern coast of North Carolina (NCsouth), calculated using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long and short-term shoreline change rate transects for the southern North Carolina coastal region (NCsouth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017 lidar-derived mean high water shoreline for the southern coast of North Carolina from Cape Lookout to Cape Fear (NCsouth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Baseline for the North Carolina coastal region from Cape Fear to the South Carolina border (NCwest)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the western coast of North Carolina from Cape Fear to the South Carolina border (NCwest)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long and short-term shoreline intersect points for the western coast of North Carolina (NCwest), calculated using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long and short-term shoreline change rate transects for the western North Carolina coastal region (NCwest), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017 lidar-derived mean high water shoreline for the coast of North Carolina from Cape Fear to the South Carolina border (NCwest)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2022 Offshore of Breton Island, Louisiana

On August 5, 2022, researchers from the U.S. Geological Survey (USGS) conducted an offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Breton Island, Louisiana (LA). The Breton Island Post Construction Monitoring project objective includes the investigation of nearshore geologic controls on surface morphology in addition to mapping the seafloor to evaluate coastal change. This publication (Forde and others, 2023) serves as an archive of high-resolution chirp subbottom ...

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2022-328-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-328-FA Offshore of Breton Island, Louisiana, August 2022

On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a point dataset of field activity number (FAN) 2022-328-FA chirp subbottom profile 1,000-shot-interval locations.

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2022-328-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-328-FA Offshore of Breton Island, Louisiana, August 2022

On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a point dataset of field activity number (FAN) 2022-328-FA chirp subbottom profile start of trackline locations.

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2022-328-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-328-FA Offshore of Breton Island, Louisiana, August 2022

On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a line dataset of field activity number (FAN) 2022-328-FA chirp tracklines.

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Orthomosaic representing Marconi Beach, Wellfleet from images acquired during field activity 2021-022-FA on March 17, 2021

The data in this publication map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide regional context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. These data were collected as part of field activity 2021-022-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-02, which are two video cameras aimed at the ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in June 2022 Near Panama City, Florida

As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map back-barrier and lagoonal areas, as well as characterizing stratigraphy near Panama City, Florida (FL) in June 2022. The purpose of this study was to conduct a geologic assessment (including bathymetric mapping) of the environs ...

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2022-312-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-312-FA Near Panama City, Florida, November 2022

From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-312-FA chirp subbottom profile 1,000-shot-interval locations.

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2022-312-FA _sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-312-FA Near Panama City, Florida, June 2022

From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-312-FA chirp subbottom profile start of trackline locations.

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2022-312-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-312-FA Near Panama City, Florida, November 2022

From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2022-312-FA chirp tracklines.

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2022 from Seven Mile Island, New Jersey

From April 29 through May 2, 2022, researchers from the U.S. Geological Survey (USGS) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterizing stratigraphy near Seven Mile Island, New Jersey (NJ). The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. ...

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2022-309-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-309-FA Offshore of Seven Mile Island, New Jersey, April and May 2022

From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a point dataset of field activity number (FAN) 2022-309-FA chirp subbottom profile 1,000-shot-interval locations.

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2022-309-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-309-FA Offshore of Seven Mile Island, New Jersey, April and May 2022

From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a point dataset of field activity number (FAN) 2022-309-FA chirp subbottom profile start of trackline locations.

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2022-309-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-309-FA Offshore of Seven Mile Island, New Jersey, April and May 2022

From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a line dataset of field activity number (FAN) 2022-309-FA chirp tracklines.

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Low-altitude aerial imagery collected from a Helikite at Marconi Beach, Wellfleet, MA on March 22, 2023

The data in this release re-map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide updated environmental context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2022-014-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-02, which are two video cameras aimed at the ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2022 from Boca Chica Key, Florida

As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey at the nearshore ledge offshore of Boca Chica Key, Florida (FL) November 8-13, 2022. The objective of the project was to collect bathymetric maps and conduct a geologic assessment of the nearshore ledge off Boca Chica Key in support ...

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2022-334-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-334-FA Offshore of Boca Chica Key, Florida, November 2022

From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-334-FA chirp subbottom profile 1,000-shot-interval ...

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2022-334-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-334-FA Offshore of Boca Chica Key, Florida, November 2022

From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-334-FA chirp subbottom profile start of trackline ...

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2022-334-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-334-FA Offshore of Boca Chica Key, Florida, November 2022

From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2022-334-FA chirp tracklines.

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RGB-averaged orthoimagery of coastal North Carolina, from 2020-05-08 to 2020-05-09

RGB-averaged orthoimages were created from aerial imagery collected May 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RGB-averaged orthoimages were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RGB-averaged orthoimages help researchers document inter-annual changes in shoreline position and coastal morphology in ...

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Salish Sea water level hindcast simulations: 1985-2015

Simulatations of water levels in the Salish Sea for a continuous hindcast of the period October 1, 1985, to September 30, 2015 were conducted to evaluate the utility and skill of a sea-level anomaly predictor and to develop extreme water level estimates accounting for decadal climate variability. The model accounts for sea level position, tides, remote sea-level anomalies, local winds and storm surge and stream flows as they affect water density. Comparison of modeled and measured water levels showed the ...

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Salish Sea water level simulation projections: 2016-2099

Simulations of the period 2016-2099 were conducted using the Salish Sea hydrodynamic model to evaluate extreme water levels associated with anticipated changes in sea level and climate forcing. The model projections accounting for sea level position, tides, remote sea-level anomalies, local winds and storm surge and stream flows as they affect water density. Dynamically downscaled Weather Research and Forecasting (WRF) CMIP5 GFDL wind and atmospheric pressure fields were prescribed over the model open ...

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Salish Sea water level validation simulations: 2017-2020

Simulations of water levels in the Salish Sea over the period October 1, 2016 to September 30, 2020 were conducted to validate the Salish Sea hydrodynamic model. The model accounts for sea level position, tides, remote sea-level anomalies, local winds and storm surge and stream flows as they affect water density. Comparison of modeled and measured water levels showed the model predicts extreme water levels at NOAA and USGS tide gage stations within 0.15 m. Model inputs and outputs of time-series forcing and ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in May 2023 from Oahu, Hawaii

As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterizing stratigraphy near Oahu, Hawaii (HI) May 7-13, 2023. The purpose of this study was to conduct a geologic assessment (including bathymetric mapping) near Fort Hase Beach, ...

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2023-310-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2023-310-FA Offshore of Kailua, Hawaii, May 2023

From May 7-13, 2023, the U.S. Geological Survey (USGS) conducted a geologic assessment, including bathymetric mapping, near Kailua, Hawaii in support of efforts to construct an artificial coral reef offshore of Marine Corps Base Hawaii (MCBH). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2023-310-FA chirp subbottom ...

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2023-310-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2023-310-FA Offshore of Kailua, Hawaii, May 2023

From May 7-13, 2022, the U.S. Geological Survey (USGS) conducted a geologic assessment, including bathymetric mapping, near Kailua, Hawaii in support of efforts to construct an artificial coral reef offshore of Marine Corps Base Hawaii (MCBH). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced ...

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2023-310-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2023-310-FA Offshore of Kailua, Hawaii, May 2023

From May 7-13, 2022, the U.S. Geological Survey (USGS) conducted a geologic assessment, including bathymetric mapping, near Kailua, Hawaii in support of efforts to construct an artificial coral reef offshore of Marine Corps Base Hawaii (MCBH). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2023-310-FA chirp tracklines.

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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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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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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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USGS CoastCam at Tres Palmas, Rincón, Puerto Rico: Timestack Imagery and Coordinate Data

A digital video camera was installed at Tres Palmas, Rincón, Puerto Rico (PR) and faced west along the beach. Every hour during daylight hours, daily from August 27, 2019, to March 10, 2020, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the red, green, ...

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USGS CoastCam at Isla Verde, Puerto Rico: 2018-2019 Timestack Imagery and Coordinate Data

A digital video camera was installed at Isla Verde Beach in San Juan, Puerto Rico (PR) and faced northeast along the beach. Every hour during daylight hours, daily from February 1, 2019, to July 15, 2019, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the ...

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USGS CoastCam at Waiakāne, Moloka'i, Hawai'i: 2018 Timestack Imagery and Coordinate Data

A digital video camera was installed at Waiakāne, Moloka'i, Hawai'i (HI) and faced west along the beach. Every hour during daylight hours, daily from June 26, 2018, to September 20, 2018, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the red, green, and ...

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USGS CoastCam at Isla Verde, Puerto Rico: 2018-2019 Intrinsic and Extrinsic Calibration Data

A digital video camera was installed at Isla Verde, Puerto Rico (PR) and faced northeast along the beach. Every hour during daylight hours, daily from February 1, 2019, to July 15, 2019, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological Survey (USGS) research ...

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2001 Gulf Coast USGS/NASA ATM Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2005 East Coast (DE, MD, NJ, NY, NC, and VA) USACE NCMP Topobathy Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2012 Post-Hurricane Sandy Long Island, New York USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2016 USACE Post-Hurricane Matthew Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2016 Massachusetts NOAA Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2017 Georgia through New York USACE NCMP Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ...

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2017 Florida West Coast NOAA Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches.Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 Alabama and Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 East Coast (VA, NC, SC) USACE NCMP Post-Florence Topobathy Lidar-Derived Dune Crest, Toe, and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 East Coast (NC) USACE NCMP Topobathy Lidar Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 Mississippi and Alabama USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2019 North Carolina and Virginia USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (L=lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2019 North Carolina and Virginia Post-Dorian USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2020 New Jersey and New York USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2021 New York State Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ...

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2022 New Jersey and New York USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ...

Info
2020 New Jersey USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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1998 MA, NY, MD, and VA USGS/NASA ATM2 Lidar-derived dune crest, toe and shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

Info
USGS CoastCam at Tres Palmas, Rincón, Puerto Rico: Intrinsic and Extrinsic Calibration Data

A digital video camera was installed at Tres Palmas, Rincón, Puerto Rico (PR) and faced west to view the beach and water offshore. Every hour during daylight hours, daily from August 27, 2019 to March 10, 2020, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological ...

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Ground Penetrating Radar and Global Positioning System Data Collected from Central Florida Gulf Coast Barrier Islands, Florida, February-March 2021

A morphologically diverse and dynamic group of barrier islands along the Central Florida (FL) Gulf Coast (CFGC) form a 75-kilometer-long chain stretching from Anclote Key in the north to Egmont Key in the south. In 2021, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted ground penetrating radar (GPR) surveys on barrier islands located along the CFGC, in Pinellas County, FL. This study investigated the past evolution of the CFGC from field ...

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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 ...

Info
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 ...

Info
USGS CoastCam at Waiakāne, Moloka'i, Hawai'i: 2018 Intrinsic and Extrinsic Calibration Data

A digital video camera was installed at Waiakāne, Moloka'i, Hawai'i (HI) and faced west along the beach. Every hour during daylight hours, daily from June 26, 2018, to September 20, 2018, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological Survey (USGS) research ...

Info
2014 Post-Hurricane Sandy SC to NY NOAA NGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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Wave model input files

Provided here are the required input files to run a standalone wave model (Simulating Waves WAves Nearshore [SWAN]; Booij and others, 1999) on eleven model domains from the Canada-U.S. border to Norton Sound, Alaska to create a downscaled wave database (DWDB). The DWDB, in turn, can be used to reconstruct hindcast (1979-2019) and projected (2020-2050) time series at each point in the model domains see Engelstad and others, 2023 for further information on reconstruction of time-series. The model forcing ...

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Wave time-series: ERA5 hindcast period 1979-2019 - U.S. Canada border to Bering Strait

Modeled wave time series data are presented for the hindcast period of 1979 to 2019 from the U.S. Canada border to the Bering Strait close to the 5 and 10 m isobaths. Outputs include three-hourly nearshore significant wave heights (Hs), mean wave periods (Tm) and mean wave directions (Dm) for 6424 locations. Data are available as netCDF files and are packaged for the Beaufort Sea region from the U.S. Canada border to Nuvuk (Point Barrow), and for the Chukchi Sea region from Nuvuk to Kotzebue Sound and from ...

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USGS CoastCam at Sand Key, Florida: Intrinsic and Extrinsic Calibration Data (Camera 1)

Two digital video cameras were installed at Sand Key, Florida (FL), facing south (camera 1) and north (camera 2) along the beach. Every hour during daylight hours, the cameras collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements.. The cameras are part of a U.S. Geological Survey (USGS) research project to study the ...

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ATLANTIC - Coastal Vulnerability to Sea-Level Rise: A Preliminary Database for the U.S. Atlantic Coast

The goal of this project is to provide a preliminary overview, at a National scale, the relative susceptibility of the Nation's coast to sea-level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of ...

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GULF - Coastal Vulnerability to Sea-Level Rise: U.S. Gulf Coast

The goal of this project is to quantify, at the National scale, the relative susceptibility of the Nation's coast to sea-level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of regions where ...

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PACIFIC - Coastal Vulnerability to Sea-Level Rise: U.S. Pacific Coast

The goal of this project is to quantify, at the National scale, the relative susceptibility of the Nation's coast to sea-level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of regions where ...

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Point shapefile of probability of shoreline change along the U.S. Atlantic Coast (ProbSLC_AtlanticData.shp)

During the 21st century, sea-level rise will have a wide range of effects on coastal environments, human development and infrastructure in coastal areas. Consequently there is a need to develop modeling or other analytical approaches that can be used to evaluate potential impacts to inform coastal management. This shapefile provides the data that were used to develop and evaluate the performance of a Bayesian network (BN) that was developed to predict long-term shoreline change associated with sea-level ...

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Offshore baseline for Cape Cod coastal region generated to calculate shoreline change rates from Provincetown to the southern end of Monomoy Island, Massachusetts (CapeCod_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Cape Cod region from Provincetown to the southern end of Monomoy Island, Massachusetts (CapeCod_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Shorelines of the Cape Cod coastal region from Provincetown to the southern end of Monomoy Island, Massachusetts, used in shoreline change analysis (CapeCod_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Cape Cod region from Provincetown to the southern end of Monomoy Island, Massachusetts (CapeCod_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Offshore baseline for Delmarva North coastal region generated to calculate shoreline change rates from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia (DelmarvaN_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Delmarva North region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia (DelmarvaN_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Shorelines of the Delmarva North coastal region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia, used in shoreline change analysis (DelmarvaN_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Delmarva North region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia (DelmarvaN_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Offshore baseline for the Delmarva South/Southern Virginia region generated to calculate shoreline change rates from Wallops Island, Virginia to the Virginia/North Carolina border (DelmarvaS_SVA_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Delmarva South/Southern Virginia region from Wallops Island, Virginia to the Virginia/North Carolina border (DelmarvaS_SVA_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Delmarva South and Southern Virginia coastal region from Wallops Island, Virginia to the Virginia/North Carolina border, used in shoreline change analysis (DelmarvaS_SVA_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Delmarva South/Southern Virginia region from Wallops Island, Virginia to the Virginia/North Carolina border (DelmarvaS_SVA_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for Greater Boston coastal region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts, generated to calculate shoreline change rates (GreaterBoston_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Greater Boston region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts (GreaterBoston_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Greater Boston coastal region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts, used in shoreline change analysis (GreaterBoston_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Greater Boston region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts (GreaterBoston_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for Long Island coastal region generated to calculate shoreline change rates for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Long Island coastal region used in shoreline change analysis for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Rate Calculations for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for Massachusetts Islands coastal region generated to calculate shoreline change rates for Martha's Vineyard and Nantucket (MA_Islands_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Massachusetts Islands Region including Martha's Vineyard and Nantucket (MA_Islands_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Massachusetts Islands coastal region including Martha's Vineyard and Nantucket, used in shoreline change analysis (MA_Islands_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Massachusetts Islands Region including Martha's Vineyard and Nantucket (MA_Islands_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for New England North coastal region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts, generated to calculate shoreline change rates (NE_North_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New England North region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts (NewEnglandN_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the New England North coastal region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts, used in shoreline change analysis (NewEnglandN_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New England North region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts (NewEnglandN_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for New England South coastal region from Dartmouth, Massachusetts to Napatree Point, Rhode Island, generated to calculate shoreline change rates (NE_South_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New England South region from Dartmouth, Massachusetts to Napatree Point, Rhode Island (NewEnglandS_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the New England South coastal region used in shoreline change analysis from Dartmouth, Massachusetts to Napatree Point, Rhode Island (NewEnglandS_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New England South region from Dartmouth, Massachusetts to Napatree Point, Rhode Island (NewEnglandS_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for New Jersey North coastal region generated to calculate shoreline change rates from Sandy Hook to Little Egg Inlet, New Jersey (NJN_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New Jersey North region from Sandy Hook to Little Egg Inlet, New Jersey (NewJerseyN_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the New Jersey North coastal region used in shoreline change analysis from Sandy Hook to Little Egg Inlet, New Jersey (NewJerseyN_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New Jersey North region from Sandy Hook to Little Egg Inlet, New Jersey (NewJerseyN_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for New Jersey South coastal region generated to calculate shoreline change rates from Little Egg Inlet to Cape May, New Jersey (NJS_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New Jersey South region from Little Egg Inlet to Cape, May, New Jersey (NewJerseyS_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the New Jersey South coastal region used in shoreline change analysis from Little Egg Inlet to Cape May, New Jersey (NewJerseyS_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New Jersey South region from Little Egg Inlet to Cape, May, New Jersey (NewJerseyS_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiE_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along East Kauai, Hawaii (Papaa to Nawiliwili)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiE_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Kauai east region from Papaa to Nawiliwili, Hawaii

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiE_shorelines - Shorelines of the eastern coastal region of Kauai, Hawaii, from Papaa to Nawiliwili, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiE_ST- Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Kauai east region from Papaa to Nawiliwili, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiN_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along North Kauai, Hawaii (Haena to Moloaa)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiN_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Kauai north region from Haena to Moloaa, Hawaii

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiN_shorelines - Shorelines of the northern coastal region of Kauai, Hawaii, from Haena to Moloaa, used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiN_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with weighted linear regression short-term rate calculations for the Kauai north region from Haena to Moloaa, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiS_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along South Kauai, Hawaii (Waimea to Kipu Kai)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiS_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Kauai south region from Waimea to Kipu Kai, Hawaii

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiS_shorelines - Shorelines of the southern coastal region of Kauai, Hawaii, from Waimea to Kipu Kai, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiS_ST- Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Kauai south region from Waimea to Kipu Kai, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiW_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along West Kauai, Hawaii (Oomano to Polihale)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiW_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Kauai west region from Oomano to Polihale, Hawaii

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiW_shorelines - Shorelines of the western coastal region of Kauai, Hawaii, from Oomano to Polihale, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
KauaiW_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Kauai west region from Oomano to Polihale, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiK_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along the Kihei Coast of Maui, Hawaii (Maalaea to Makena)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiK_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Maui Kihei region from Maalaea to Makena, Hawaii

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiK_shorelines - Shorelines of the Kihei coastal region of Maui, Hawaii, from Maalaea to Makena, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiK_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Maui Kihei region from Maalaea to Makena, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiN_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along the North Coast of Maui, Hawaii (Waihee to Kuau)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiN_LT- Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Maui North region from Waihee to Kuau, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiN_shorelines - Shorelines of the northern coastal region of Maui, Hawaii, from Waihee to Kuau, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiN_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Maui North region from Waihee to Kuau, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiW_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along the West Coast of Maui, Hawaii (Ukumehame to Honolua)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiW_LT- Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Maui West region from Ukumehame to Honolua, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiW_shorelines - Shorelines of the western coastal region of Maui, Hawaii, from Ukumehame to Honolua, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
MauiW_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Maui West region from Ukumehame to Honolua, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuE_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along East Oahu, Hawaii (Kahuku to Makapuu)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuE_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Oahu East region from Kahuku to Makapuu, Hawaii

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuE_shorelines - Shorelines of the eastern coastal region of Oahu, Hawaii, from Kahuku to Makapuu, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuE_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Oahu East region from Kahuku to Makapuu, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuN_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along North Oahu, Hawaii (Camp Erdman to Kahuku)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuN_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Oahu north region from Camp Erdman to Kahuku, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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OahuN_shorelines - Shorelines of the northern coastal region of Oahu, Hawaii, from Camp Erdman to Kahuku, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuN_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Oahu North region from Camp Erdman to Kahuku, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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OahuS_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along South Oahu, Hawaii (Barbers Point to Sandy Beach)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuS_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Oahu south region from Barbers Point to Sandy Beach, Hawaii

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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OahuS_shorelines - Shorelines of the southern coastal region of Oahu, Hawaii, from Barbers Point to Sandy Beach, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuS_ST- Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Oahu south region from Barbers Point to Sandy Beach, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuW_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along West Oahu, Hawaii (Yokohama to Tracks Beach)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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OahuW_LT- Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Oahu west region from Yokohama to Tracks Beach, Hawaii

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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OahuW_shorelines - Shorelines of the western coastal region of Oahu, Hawaii, from Yokohama to Tracks Beach, used in shoreline change analysis.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
OahuW_ST- Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Oahu west region from Yokohama to Tracks Beach, Hawaii.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Location and depth data for piston and gravity cores collected in September 2019 offshore of south-central California (USGS FAN 2019-642-FA)

This dataset includes the location and depth information for 39 piston and gravity cores that were collected as part of a groundtruthing survey in September 2019 aboard the R/V Bold Horizon. This dataset is one of several collected as part of the Bureau of Ocean Energy Management (BOEM)-funded California Deepwater Investigations and Groundtruthing (Cal DIG I) project. The purpose of the study is to assess shallow geohazards, benthic habitats, and thereby the potential for alternative energy infrastructure ...

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High-resolution shoreline change measurements (1997-2005) from Corolla to Cape Hatteras, NC (swash_shorelines.shp, geographic, WGS 84)

The northeastern North Carolina coastal system, from False Cape, Virginia, to Cape Lookout, North Carolina, has been studied by a cooperative research program that mapped the Quaternary geologic framework of the estuaries, barrier islands, and inner continental shelf. This information provides a basis to understand the linkage between geologic framework, physical processes, and coastal evolution at time scales from storm events to millennia. The study area attracts significant tourism to its parks and ...

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Offshore baseline for the Oregon coastal region generated to calculate shoreline change rates (OR_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Oregon (OR_shorelines_uncertainty.dbf)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Oregon coastal region used in shoreline change analysis (OR_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.2 Transects with Long-Term Linear Regression Rate Calculations for Oregon (OR_transects_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.2 Transects with Short-Term End Point Rate Calculations for Oregon (OR_transects_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the Washington coastal region generated to calculate shoreline change rates (WA_baseline.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Washington (WA_shorelines_uncertainty.dbf)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Washington coastal region used in shoreline change analysis (WA_shorelines.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.2 Transects with Long-Term Linear Regression Rate Calculations for Washington (WA_transects_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.2 Transects with Short-Term End Point Rate Calculations for Washington (WA_transects_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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USGS CoastCam at Sand Key, Florida: Intrinsic and Extrinsic Calibration Data (Camera 2)

Two digital video cameras were installed at Sand Key, Florida (FL), facing south (camera 1) and north (camera 2) along the beach. Every hour during daylight hours, the cameras collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The images included in this data release were collected by camera 2 (c2) from May 29, ...

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USGS CoastCam at Madeira Beach, Florida: Timestack Imagery and Coordinate Data

A digital video camera was installed at Madeira Beach, Florida (FL) and faced west along the beach. Every hour during daylight hours, daily from 2017 to 2022, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the red, green, and blue or monochrome pixel ...

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USGS CoastCam at Sand Key, Florida: Timestack Imagery and Coordinate Data (Camera 2)

Two digital video cameras were installed at Sand Key, Florida (FL), facing south (camera 1) and north (camera 2) along the beach. Every hour during daylight hours, daily from 2018 to 2022, the cameras collected raw video and produced snapshots and time-averaged image products. For camera 2, one such product that is created is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup ...

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Baseline for the coast of Puerto Rico's main island generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 (ver. 2.0, March 2023)

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States' coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling ...

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Shoreline intersects for the coast of Puerto Rico's main island generated by the Digital Shoreline Analysis System version 5.1 (ver. 2.0, March 2023)

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling ...

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Shorelines for Vieques, Culebra, and the main island of Puerto Rico from the 1900s to 2018 (ver. 2.0, March 2023)

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling ...

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Shoreline change rates for the coast of Puerto Rico's main island calculated using the Digital Shoreline Analysis System version 5.1 (ver. 2.0, March 2023)

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling ...

Info
Baseline for the islands of Vieques and Culebra, Puerto Rico, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling ...

Info
Shoreline intersects for the islands of Vieques and Culebra, Puerto Rico, calculated using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling ...

Info
Shoreline change rates for the islands of Vieques and Culebra, Puerto Rico, calculated using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling ...

Info
Geospatial Navigational Data Associated with Chirp Sub-Bottom Profiles Collected During USGS Field Activity Number 2023-325-FA in June and August 2023 from the Chandeleur Islands, Louisiana

As part of the 2022 Disaster Supplemental project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterize stratigraphy near the Chandeleur Islands, Louisiana (LA) in June and August 2023. The purpose of this study was to conduct a morphologic and geologic assessment of the impacts of the 2020 and 2021 hurricane seasons within part of the Breton National ...

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Archive of Chirp Sub-Bottom Profile, Imagery, and Navigational Data Collected in June and August 2023 from the Chandeleur Islands, Louisiana

As part of the 2022 Disaster Supplemental project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterize stratigraphy near the Chandeleur Islands, Louisiana (LA) in June and August 2023. The purpose of this study was to conduct a morphologic and geologic assessment of the impacts of the 2020 and 2021 hurricane seasons within part of the Breton National ...

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2005 USGS Post-Hurricane Rita Texas and Louisiana Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 USGS Post-Hurricane ...

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Hurricane Florence Overwash Extents

The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the southeast coast of the United States from North Carolina to Virginia and attributed to coastal processes during [Atlantic Basin] Hurricane Florence, which made landfall in the U.S. on September 14, 2018.

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Hurricane Isaias Overwash Extents

The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the coast of the Carolinas and attributed to coastal processes during [Atlantic Basin] Hurricane Isaias, which made landfall in the U.S. on August 4, 2020.

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Hurricane Matthew Overwash Extents (version 2.0, 20210916)

The National Assessment of Coastal Change Hazards project exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Florida, Georgia, North Carolina,and South Carolina coasts and attributed to coastal processes during [Atlantic Basin] Hurricane Matthew, which made landfall in the U.S. on October 8, 2018.

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Hurricane Sally Overwash Extents

The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Florida and Alabama coast and attributed to coastal processes during [Atlantic Basin] Hurricane Sally, which made landfall in the U.S. on September 16, 2020.

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Grainsize data from vibracores collected in Ozette Lake, Washington, in 2019

Grainsize data were collected from select sediment cores from Ozette Lake, Washington, in 2019. These data were used to investigate submarine landslide deposits triggered by large Cascadia Subduction Zone earthquakes.

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Multi-sensor core logger (MSCL) data of vibracores and bob-cores collected in Lake Ozette, from 2019 to 2021

This dataset includes multi-sensor core logger (MSCL) data from sediment cores collected in Lake Ozette, Washington. The sediment cores were collected during USGS field activities 2019-622-FA and 2021-641-FA for investigating submarine landslide deposits triggered by large Cascadia Subduction Zone earthquakes.

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Marsh Shorelines of the Massachusetts Coast from 2013-14 Topographic Lidar Data

The Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the Massachusetts coast. Seventy-six maps were produced in 1997 depicting a statistical analysis of shoreline change on ocean-facing shorelines from the mid-1800s to 1978 using multiple data sources. In 2001, a 1994 shoreline was added. More recently, in cooperation with CZM, the U.S. Geological Survey (USGS) delineated a new shoreline for Massachusetts using color ...

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Offshore baseline for the northeastern Florida (FLne) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Shorelines of the northeastern Florida (FLne) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for northeastern Florida (FLne)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for northeastern Florida (FLne)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for northeastern Florida (FLne)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for northeastern Florida (FLne)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the southeastern Florida (FLse) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the southeastern Florida (FLse) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for southeastern Florida (FLse)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for southeastern Florida (FLse)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for southeastern Florida (FLse)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for southeastern Florida (FLse)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the Georgia (GA) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Shorelines of the Georgia (GA) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Georgia (GA)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Georgia (GA)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Georgia (GA)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Georgia (GA)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the central North Carolina (NCcentral) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Shorelines of the central North Carolina (NCcentral) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for central North Carolina (NCcentral)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for central North Carolina (NCcentral)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for central North Carolina (NCcentral)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for central North Carolina (NCcentral)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Offshore baseline for the northern North Carolina (NCnorth) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the northern North Carolina (NCnorth) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for northern North Carolina (NCnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for northern North Carolina (NCnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for northern North Carolina (NCnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for northern North Carolina (NCnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the southern North Carolina (NCsouth) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the southern North Carolina (NCsouth) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for southern North Carolina (NCsouth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for southern North Carolina (NCsouth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for southern North Carolina (NCsouth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for southern North Carolina (NCsouth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the western North Carolina (NCwest) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the western North Carolina (NCwest) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for western North Carolina (NCwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for western North Carolina (NCwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for western North Carolina (NCwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the South Carolina (SC) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the South Carolina (SC) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for South Carolina (SC)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for South Carolina (SC)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for South Carolina (SC)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for South Carolina (SC)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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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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Offshore baseline for the Alabama coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Alabama

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Alabama coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Alabama

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Alabama

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Alabama

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the Florida north (FLnorth) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Florida north (FLnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Florida north (FLnorth) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Florida north (FLnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Florida north (FLnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Florida north (FLnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the Florida west (FLwest) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Florida west (FLwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Florida west (FLwest) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Florida west (FLwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Florida west (FLwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Florida west (FLwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the Louisiana coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Louisiana

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Louisiana coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Louisiana

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Louisiana

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Louisiana

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the Mississippi coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Mississippi

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Mississippi coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Mississippi

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Mississippi

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Mississippi

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the Texas east (TXeast) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Texas east (TXeast)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Shorelines of the Texas east (TXeast) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Texas east (TXeast)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Texas east (TXeast)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Offshore baseline for the Texas west (TXwest) coastal region generated to calculate shoreline change rates

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Texas west (TXwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Shorelines of the Texas west (TXwest) coastal region used in shoreline change analysis

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Texas west (TXwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Texas west (TXwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
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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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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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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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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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2010–2011

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2013–2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2010

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2012

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2013–2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2010–2011

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2012

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2014–2015

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2010–2011

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2012

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2013–2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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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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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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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Event Hazards

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Fabric Dataset

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Hazard Impact Type

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Maximum Change Likelihood

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Perpetual Hazards

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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2013-14 Massachusetts Lidar-Derived Dune Crest Point Data

This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ...

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2013-14 Massachusetts Lidar-Derived Dune Toe Point Data

This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ...

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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 ...

Info
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 ...

Info
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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2015 Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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2016 NOAA Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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2016 USACE Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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2018 Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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Town Neck Beach, Massachusetts, 10 cm 2016-2017 Digital Elevation Models

Low-altitude (80-100 meters above ground level) Unmanned Aircraft Systems (UAS) imagery of Town Neck Beach in Sandwich, Massachusetts, were used in a structure-from-motion (SfM) photogrammetry workflow to create high-resolution topographic datasets. Imagery was collected at close to low tide on twelve days to observe changes in beach and dune morphology. Ground control points (GCPs), which are temporary targets on the ground located by using a real-time kinematic global navigation satellite system (RTK-GNSS ...

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Town Neck Beach, Massachusetts, 5 cm 2016-2017 Orthomosaics

Low-altitude (80-100 meters above ground level) Unmanned Aircraft Systems (UAS) imagery of Town Neck Beach in Sandwich, Massachusetts, were used in a structure-from-motion (SfM) photogrammetry workflow to create high-resolution topographic datasets. Imagery was collected at close to low tide on twelve days to observe changes in beach and dune morphology. Ground control points (GCPs), which are temporary targets on the ground located by using a real-time kinematic global navigation satellite system (RTK-GNSS ...

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Historical Shorelines for Puerto Rico from 1901 to 1987

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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VA Bias_Feature – Feature class containing Virginia proxy-datum bias information to be used in the Digital Shoreline Analysis System.

Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release ...

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Intersects for coastal region of Virginia generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Long-term shoreline change rates for the Virginia coastal region, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Short-term shoreline change rates for the Virginia coastal region using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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A GIS compilation of vector shorelines for the Virginia coastal region from the 1840s to 2010s

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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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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Mean High Water Shorelines for the Outer Cape of Massachusetts from Nauset Inlet to Race Point (1998-2005)

This data release contains mean high water (MHW) shorelines for the Outer Cape of Cape Cod, Massachusetts, from Nauset Inlet to Race Point. From 1998-2005, the U.S. Geological Survey surveyed 45 kilometers of coastline 111 times using a ground-based system called Surveying Wide-Area Shorelines (SWASH). The SWASH system used a six-wheeled amphibious all-terrain vehicle as a platform for an array of Global Positioning System sensors. High-accuracy measurements of horizontal position, vertical position, and ...

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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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Baseline for the Florida east coast (FLec) coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Bias Feature for the Florida east coast (FLec) coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Intersects for the Florida east coast (FLec) coastal region generated to calculate long-term shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Intersects for the Florida east coast (FLec) coastal region generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Shorelines of the Florida east coast (FLec) coastal region used in shoreline change analysis

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The U.S. Geological Survey (USGS) Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane ...

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Long-term shoreline change rates for the Florida east coast (FLec) coastal region using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Short-term shoreline change rates for the Florida east coast (FLec) coastal region using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Baseline for the Florida panhandle (FLph) coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Bias Feature for the Florida panhandle (FLph) coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Intersects for the Florida panhandle (FLph) coastal region generated to calculate long-term shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Intersects for the Florida panhandle (FLph) coastal region generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Shorelines of the Florida panhandle (FLph) coastal region used in shoreline change analysis

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The U.S. Geological Survey (USGS) Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane ...

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Long-term shoreline change rates for the Florida panhandle (FLph) coastal region using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Short-term shoreline change rates for the Florida panhandle (FLph) coastal region using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Baseline for the Florida west coast (FLwc) coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Bias Feature for the Florida west coast (FLwc) coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Intersects for the Florida west coast (FLwc) coastal region generated to calculate long-term shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Intersects for the Florida west coast (FLwc) coastal region generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Shorelines of the Florida west coast (FLwc) coastal region used in shoreline change analysis

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The U.S. Geological Survey (USGS) Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane ...

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Long-term shoreline change rates for the Florida west coast (FLwc) coastal region using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Short-term shoreline change rates for the Florida west coast (FLwc) coastal region using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Baseline for the Georgia coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Bias Feature for the Georgia coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Intersects for the Georgia coastal region generated to calculate long-term shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Intersects for the Georgia coastal region generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Shorelines of the Georgia coastal region used in shoreline change analysis

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The U.S. Geological Survey (USGS) Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane ...

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Long-term shoreline change rates for the Georgia coastal region using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Short-term shoreline change rates for the Georgia coastal region using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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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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2014 profile-derived mean high water shorelines of Cape Cod Bay, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Cape Cod Bay, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2012-2014 contour-derived mean high water shorelines of the Massachusetts coast used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2012 profile-derived mean high water shorelines of Martha's Vineyard, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 profile-derived mean high water shorelines of Martha's Vineyard, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 profile-derived mean high water shorelines of the north shore of Martha's Vineyard, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the north shore of Martha's Vineyard, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the south shore of Martha's Vineyard, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2012 profile-derived mean high water shorelines of Nantucket, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 profile-derived mean high water shorelines of Nantucket, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 profile-derived mean high water shorelines of the north shore of Nantucket, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the north shore of Nantucket, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the south shore of Nantucket, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2010 profile-derived mean high water shorelines of the North Shore of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2014 profile-derived mean high water shorelines of the North Shore of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the North Shore of MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2011 profile-derived mean high water shorelines of the Outer Cape of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2014 profile-derived mean high water shorelines of the Outer Cape of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the Outer Cape of MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2014 profile-derived mean high water shorelines of the south shore of Cape Cod, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the southern shoreline of Cape Cod, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2010 profile-derived mean high water shorelines of the South Coast of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 profile-derived mean high water shorelines of the South Coast of MA used in shoreline change analysis.

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the South Coast of MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2011 profile-derived mean high water shorelines of the South Shore of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013-2014 profile-derived mean high water shorelines of the South Shore of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the South Shore of MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2018 mean high water shoreline of the coast of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Historical shoreline positions for the coast of MA, from 1844 - 2014.

The Massachusetts Office of Coastal Zone Management (MA CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (1800's-1989) shoreline positions and shoreline change maps. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- ...

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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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Preliminary estimates of forecasted shoreline positions for Florida and Georgia

During Hurricane Irma, Florida and Georgia experienced substantial impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses from hurricanes result in increased vulnerability of coastal regions, including densely populated areas. Erosion may put critical infrastructure at risk of future flooding and may cause economic loss. The U.S. Geological Survey (USGS) Coastal and Marine Hazards Resources Program is working to assess shoreline erosion along the southeast U.S. ...

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Uncertainty of forecasted shoreline positions for Florida and Georgia

During Hurricane Irma, Florida and Georgia experienced substantial impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses from hurricanes result in increased vulnerability of coastal regions, including densely populated areas. Erosion may put critical infrastructure at risk of future flooding and may cause economic loss. The U.S. Geological Survey (USGS) Coastal and Marine Hazards Resources Program is working to assess shoreline erosion along the southeast U.S. ...

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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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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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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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Baseline for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Intersects for coastal region around Boston, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Long-term and short-term shoreline change rates for coastal region around Boston, Massachusetts calculated without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the Buzzards Bay coastal region in Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Intersects for the Buzzards Bay coastal region in Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Long-term and short-term shoreline change rates for the Buzzards Bay coastal region in Massachusetts calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Intersects for the Cape Cod Bay coastal region in Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the Cape Cod Bay coastal region in Massachusetts, generated to calculate shoreline change rates (without the proxy-datum bias) using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the Cape Cod Bay coastal region in Massachusetts, generated to calculate shoreline change rates (with the proxy-datum bias) using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Long-term and short-term shoreline change rates for the Cape Cod Bay coastal region in Massachusetts calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the northern coast of Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the southern coast Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Intersects for Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Long-term and short-term shoreline change rates for Martha's Vineyard, Massachusetts calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the northern coast of Nantucket, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the southern coast of Nantucket, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Intersects for Nantucket, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Long-term and short-term shoreline change rates for Nantucket, Massachusetts calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Intersects for the coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Long-term and short-term shoreline change rates for the coastal region north of Boston, Massachusetts calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the backshore of Outer Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the east facing coast of Cape Cod, Massachusetts, from Monomoy to Provincetown, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Intersects for Outer Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Long-term and short-term shoreline change rates for Outer Cape Cod, Massachusetts calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the southern coast of Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Intersects for the southern coastal region of Cape Cod Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Long-term and short-term shoreline change rates for the southern coastal region of Cape Cod, Massachusetts calculated without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the coast south of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Intersects for the coast south of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Long-term and short-term shoreline change rates for the coast south of Boston, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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1970s Shorelines for the Main Island of Puerto Rico

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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2010 Shorelines for Vieques, Culebra, and the Main Island of Puerto Rico

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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1970s Shorelines for Vieques and Culebra, Puerto Rico

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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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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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Assateague Island, MD & VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD & VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Assateague Island, MD & VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Assawoman Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assawoman Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Assawoman Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cape Hatteras, NC, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Hatteras, NC, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cape Hatteras, NC, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cape Lookout, NC, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Lookout, NC, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cape Lookout, NC, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Coast Guard Beach, MA, 2013-2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Coast Guard Beach, MA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Coast Guard Beach, MA, 2013-2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cobb Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cobb Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cobb Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fisherman Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fisherman Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Fisherman Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Metompkin Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Metompkin Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Metompkin Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Monomoy Island, MA, 2013-2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Monomoy Island, MA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Monomoy Island, MA, 2013-2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Myrtle Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Myrtle Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Myrtle Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parramore Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Parramore Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parramore Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parker River, MA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Parker River, MA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parker River, MA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rhode Island National Wildlife Refuge, RI, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rhode Island National Wildlife Refuge, RI, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Rhode Island National Wildlife Refuge, RI, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Ship Shoal Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Ship Shoal Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Ship Shoal Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Smith Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Smith Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Smith Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Wreck Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Wreck Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Wreck Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

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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 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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Baseline for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Long-term and short-term shoreline change rates for the coastal region around Boston, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Baseline for the coastal region of Buzzards Bay, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for coastal region of Buzzards Bay, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Long-term and short-term shoreline change rates for the region of Buzzards Bay, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Baseline for the region of Cape Cod Bay, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for coastal region of Cape Cod Bay, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Long-term and short-term shoreline change rates for the region of Cape Cod Bay, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Baseline for the Elizabeth Islands, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for the region of the Elizabeth Islands, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

Info
Long-term and short-term shoreline change rates for the region of the Elizabeth Islands, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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MA Bias_Feature – Feature class containing Massachusetts proxy-datum bias information to be used in the Digital Shoreline Analysis System.

The Digital Shoreline Analysis System (DSAS) is a freely available software application that works within the Environmental Systems Research Institute (ESRI) Geographic Information System (ArcGIS) software. DSAS computes rate-of-change statistics for a time series of shoreline vector data. Additionally, the DSAS application is useful for computing rates of change for any boundary-change problem that incorporates a clearly-identified feature position at discrete times, such as glacier limits, river banks, or ...

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Baselines for the coast of Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for coastal region of Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Long-term and short-term shoreline change rates for the region of Martha's Vineyard, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Baselines for the coast of Nantucket, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for coastal region of Nantucket, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Long-term and short-term shoreline change rates for the region of Nantucket, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Baseline for the coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Long-term and short-term shoreline change rates for the region north of Boston, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Baselines for the Outer Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for the Outer Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Long-term and short-term shoreline change rates for the Outer Cape Cod, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Baseline for the southern coast of Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for the southern coast of Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Long-term and short-term shoreline change rates for the southern coast of Cape Cod, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Baseline for the coastal region south of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Intersects for coastal region south of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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Long-term and short-term shoreline change rates for the coastal region south of Boston, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of ...

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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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Geospatial Navigational Data Associated with Chirp Sub-Bottom Profiles Collected During USGS Field Activity Number 2014-303-FA in June and July 2014 from Fire Island, New York

During June 15-23 and July 10-12, 2014, the U.S. Geological Survey (USGS) conducted a nearshore geologic assessment, including bathymetric mapping, along Fire Island, New York (NY). This work was conducted in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near Fire Island, NY to assess the impacts of Hurricane Sandy to the area in October 2012. Geophysical data were collected as part of the Hurricane Sandy Supplemental Project (GS2-2B). The ...

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Archive of Chirp Sub-Bottom Profile, Imagery, and Navigational Data Collected in June and July 2014 from Fire Island, New York

During June 15-23 and July 10-12, 2014, the U.S. Geological Survey (USGS) conducted a nearshore geologic assessment, including bathymetric mapping, along Fire Island, New York (NY). This work was conducted in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near Fire Island, NY to assess the impacts of Hurricane Sandy to the area in October 2012. Geophysical data were collected as part of the Hurricane Sandy Supplemental Project (GS2-2B). The ...

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Geospatial Navigational Data Associated with Chirp Sub-Bottom Profiles Collected During USGS Field Activity Numbers 2021-326-FA and 2022-326-FA in 2021 and 2022 from Duck, North Carolina

In June/December 2021 and July 2022, the U.S. Geological Survey (USGS) and U.S. Army Corps of Engineers, Engineer Research and Development Center (USACE-ERDC) conducted repeat, nearshore geologic assessments, including bathymetric mapping, near Duck, North Carolina (NC). This work was performed in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near the USACE Field Research Facility and to measure the co-evolution of the morphology and ...

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Archive of Chirp Sub-Bottom Profile, Imagery, and Navigational Data Collected During USGS Field Activity Numbers 2021-326-FA and 2022-326-FA in 2021 and 2022 from Duck, North Carolina

In June/December 2021 and July 2022, the U.S. Geological Survey (USGS) and U.S. Army Corps of Engineers, Engineer Research and Development Center (USACE-ERDC) conducted repeat, nearshore geologic assessments, including bathymetric mapping, near Duck, North Carolina (NC). This work was performed in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near the USACE Field Research Facility and to measure the co-evolution of the morphology and ...

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Core descriptions and sedimentologic data from vibracores collected in 2021 from Central Florida Gulf Coast Barrier Islands

In 2021, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) conducted ground penetrating radar (GPR) and sediment sampling surveys on barrier islands located along the central Florida Gulf Coast (CFGC), Pinellas County, Florida (FL). This study investigated the past evolution of the CFGC from field sites at Anclote Keys, Caladesi and Honeymoon Islands, and Fort DeSoto to quantify changes that occurred along these barrier systems prior to the 20th ...

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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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Intersects for the coastal region of Virginia generated to calculate long-term shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Climatological wave height, wave period and wave power along coastal areas of the East Coast of the United States and Gulf of Mexico

This U.S. Geological Survey data release provides data on spatial variations in climatological wave parameters (significant wave height, peak wave period, and wave power) for coastal areas along the United States East Coast and Gulf of Mexico. Significant wave height is the average wave height, from crest to trough, of the highest one-third of the waves in a specific time period. Peak wave period is the wave period associated with the most energetic waves in the wave spectrum in a specific time period. Wave ...

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Bathymetric change of Central San Francisco Bay, California: 1971 to 2020

This 25-m-resolution surface presents bathymetric change of Central San Francisco Bay, California (hereafter referred to as Central Bay). This surface compares a 1-m-resolution digital elevation model (DEM) of the central portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the Central Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 25-m-resolution DEM of Central Bay comprised of historic surveys from ...

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Bathymetric change of San Pablo Bay, California: 1983 to 2015

This 25-m-resolution surface presents bathymetric change of San Pablo Bay, California, from 1983 to 2015. This surface compares a 1-m-resolution digital elevation model (DEM) of the northern portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the San Pablo Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 25-m-resolution bathymetric DEM of San Pablo Bay comprised of historic surveys from 1983 to 1986 ...

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Bathymetric change of South San Francisco Bay, California: 1979 to 2020

This 50-m-resolution surface presents bathymetric change of South San Francisco Bay, California (hereafter referred to as South Bay). This surface compares a 1-m-resolution digital elevation model (DEM) of the southern portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the South Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 50-m-resolution DEM of South Bay comprised of historic surveys from 1979 to ...

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Bathymetric change of Suisun Bay, California: 1988 to 2016

This 25-m-resolution surface presents bathymetric change of Suisun Bay, California, from 1988 to 2016. This surface compares a 1-m-resolution digital elevation model (DEM) of the northern portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the Suisun region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 25-m-resolution bathymetric DEM of Suisun Bay comprised of historic surveys from 1988 to 1990 (referred to as ...

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Beach foreshore slope for the East Coast of the United States

This data release contains foreshore slopes for primarily open-ocean sandy beaches along the East Coast of the United States (Maine through Florida). The slopes were calculated while extracting shoreline position from lidar point cloud data collected between 1997 and 2018. The shoreline positions have been previously published, but the slopes have not. An along-shore reference baseline was defined, and then 20-meter spaced cross-shore beach transects were created perpendicular to the baseline. All data ...

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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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Low-altitude aerial imagery collected from a Helikite at Marconi Beach, Wellfleet, MA on March 22, 2024

The data in this release re-map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide updated environmental context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2024-016-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of two video cameras aimed at the beach (CoastCam CACO-02). In ...

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Lifespan of marsh units in Connecticut salt marshes

The lifespans of salt marshes in Connecticut are calculated based on estimated sediment supply and sea-level rise (SLR) predictions, following the methodology of Ganju and others (2020). The salt marsh delineations are from Ackerman and others (2023). The SLR predictions are local estimates corresponding to increases of 0.3, 0.5 and 1.0 meter in global mean sea level (GMSL) by 2100, as projected by Sweet and others (2022). This work has been a part of the USGS’s effort to expand the national assessment of ...

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USGS CoastCam at DUNEX: Intrinsic and Extrinsic Calibration Data (Camera 1)

Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ...

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USGS CoastCam at DUNEX: Intrinsic and Extrinsic Calibration Data (Camera 2)

Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ...

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Core descriptions and sedimentologic data from vibracores and sand augers collected in 2021 and 2022 from Fire Island, New York

In 2021 and 2022, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and the USGS New York Water Science Center (NYWSC), on behalf of SPCMSC, conducted sediment sampling and ground penetrating radar (GPR) surveys at Point O' Woods and Ho-Hum Beach (NYWSC, 2021) and Watch Hill, Long Cove, and Smith Point (SPCMSC, 2022), Fire Island, New York. These data complement previous SPCMSC GPR and sediment sampling surveys conducted at Fire Island in 2016 ...

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2002 Post-Tropical Storm Fay University of Texas Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2002 University of Texas ...

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2002 NOAA/NASA/USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2002 Post-Hurricane Lili ...

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2003 Pre- and Post-Hurricane Isabel USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2003 Pre- and Post ...

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2004 Post-Hurricane Charley West Florida EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Post-Hurricane ...

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2005 Post-Hurricane Dennis Florida U.S. Army Corps of Engineers Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 USACE Post-Dennis ...

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2005 Post-Hurricane Katrina EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Post-Hurricane ...

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September 2006 Post-Hurricane Wilma Florida U.S. Army Corps of Engineers Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2006 Post-Hurricane ...

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March 2006 Mississippi and Alabama USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2006 USGS Mississippi ...

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September 2006 Mississippi and Alabama USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2006 USGS Mississippi ...

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September 2007 Southwest Florida Division of Emergency Management Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 Southwest Florida ...

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June 2008 Alabama and Florida USGS EAARL Lidar-derived dune crest, toe and shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the June 2008 Louisiana, ...

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2008 Post-Hurricane Gustav Northern Gulf of Mexico USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Post-Hurricane ...

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2008 South Louisiana USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 South Louisiana ...

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2009 Western Gulf of Mexico USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Western Gulf of ...

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2010 Alabama and Florida USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Alabama and Florida ...

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2010 Florida West Coast USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Florida West Coast ...

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2010 Louisiana and Mississippi USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Louisiana and ...

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2011 Northern Gulf Coast USACE Lidar-derived dune crest, toe and shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 Northern Gulf Coast ...

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2012 Post-Hurricane Isaac USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ...

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2013 Dauphin Island USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 Dauphin Island ...

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2014 USGS CMGP Post-Sandy Long Island Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 USGS CMGP Post ...

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2014 Mobile County, Alabama Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 Mobile County, ...

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2015 Mississippi and Alabama USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2015 Mississippi and ...

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1998 Fall Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Fall Gulf Coast ...

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1999 Fall Texas USGS/NASA/NOAA ATM Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1999 Fall Gulf Coast ...

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Hurricane Delta Overwash Extents

The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Louisiana coast and attributed to coastal processes during [Atlantic Basin] Hurricane Delta, which made landfall in the U.S. on October 9, 2020.

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Hurricane Irma Overwash Extents

The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Florida coast and attributed to coastal processes during [Atlantic Basin] Hurricane Irma, which made landfall in the U.S. on September 9, 2017.

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Hurricane Laura Overwash Extents

The National Assessment of Coastal Change Hazards project project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Louisiana coast and attributed to coastal processes during [Atlantic Basin] Hurricane Laura, which made landfall in the U.S. on August 27, 2020.

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Hurricane Michael Overwash Extents

The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the Florida coast and attributed to coastal processes during [Atlantic Basin] Hurricane Michael, which made landfall in the U.S. on October 10, 2018.

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Hurricane Zeta Overwash Extents

The National Assessment of Coastal Change Hazards project exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Louisiana coast and attributed to coastal processes during [Atlantic Basin] Hurricane Zeta, which made landfall in the U.S. on October 28, 2020.

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2004 Post-Hurricane Ivan Northern Gulf of Mexico EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 USGS Post-Ivan ...

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Orthomosaics representing Nauset Light Beach, Eastham, MA on September 14 and 20, 2023, pre and post Hurricane Lee

The data in this release map Marconi Beach, Head of the Meadow Beach, and Nauset Light Beach, in Cape Cod National Seashore (CACO), Massachusetts, before and after Hurricane Lee in September 2023. U.S Geological Survey personnel conducted field surveys to collect topographic data using global navigation satellite systems (GNSS) at all three beaches. In addition, at Nauset Light Beach, an uncrewed aerial system (UAS) was used to collect images with a Ricoh GRII camera for use in structure from motion ...

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USGS CoastCam at DUNEX: Timestack Imagery and Coordinate Data (Camera 1)

Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ...

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USGS CoastCam at DUNEX: Timestack Imagery and Coordinate Data (Camera 2)

Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ...

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SWASH Model Water Level Time Series at Wrightsville Beach, NC, USA for ILM site

This data release contains model output of water level elevations resulting from deterministic simulations at Wrightsville Beach, North Carolina (NC), USA. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Birchler and others (2024).

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SWASH Model Water Level Time Series at Wrightsville Beach, NC, USA for MHX site

This data release contains model output of water level elevations resulting from deterministic simulations at Wrightsville Beach, North Carolina (NC), USA. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Birchler and others (2024).

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SWASH Model Water Level Time Series at Wrightsville Beach, NC, USA for PIER site

This data release contains model output of water level elevations resulting from deterministic simulations at Wrightsville Beach, North Carolina (NC), USA. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Birchler and others (2024).

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Midshore baseline for the exposed central Beaufort Sea coast of Alaska (Hulahula River to the Colville River) generated to calculate shoreline change rates

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed, open-ocean coast of Alaska between the Hulahula River and the Colville River for the time period 1947 to 2017. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

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Digital Shoreline Analysis System (DSAS) version 5.1 transects with long-term linear regression rate calculations for the exposed central Beaufort Sea coast of Alaska from the Hulahula River to the Colville River

This dataset consists of long-term (70 years) shoreline change rates for the exposed, open-ocean coast of Alaska from the Hulahula River to the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2017. A reference baseline was ...

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Digital Shoreline Analysis System (DSAS) version 5.1 transects with short-term linear regression rate calculations for the exposed central Beaufort Sea coast of Alaska from the Hulahula River to the Colville River

This dataset consists of short-term (less than 39 years) shoreline change rates for the exposed, open-ocean coast of Alaska from the Hulahula River to the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2017. A reference ...

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Midshore baseline for the sheltered central Beaufort Sea coast of Alaska (Hulahula River to the Colville River) generated to calculate shoreline change rates

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the mainland coast of Alaska sheltered by barrier islands from the Hulahula River and the Colville River for the time period 1947 to 2017. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

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Digital Shoreline Analysis System (DSAS) version 5.1 transects with long-term linear regression rate calculations for the sheltered central Beaufort Sea coast of Alaska from the Hulahula River to the Colville River

This dataset consists of long-term (70 years) shoreline change rates for the mainland coast of Alaska sheltered by barrier islands from the Hulahula River to the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2017. A ...

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Digital Shoreline Analysis System (DSAS) version 5.1 transects with short-term linear regression rate calculations for the sheltered central Beaufort Sea coast of Alaska from the Hulahula River to the Colville River

This dataset consists of short-term (less than 39 years) shoreline change rates for the mainland coast of Alaska sheltered by barrier islands from the Hulahula River to the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and ...

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Shorelines from 1947 to 2017 for the central Beaufort Sea coast of Alaska (Hulahula River to the Colville River) used in shoreline change analysis

This dataset includes historical shoreline positions that span 70 years, from 1947 to 2017, for the north coast of Alaska between the Hulahula River and the Colville River. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), Conoco-Philips (CP), British Petroleum Alaska (BPXA), and NOAA), satellite imagery (U.S. Fish and ...

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Midshore baseline for the exposed eastern Beaufort Sea coast of Alaska (U.S. Canadian Border to the Hulahula River) generated to calculate shoreline change rates

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed, open-ocean coast of Alaska between the U.S. Canadian Border to the Hulahula River for the time period 1947 to 2017. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

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Digital Shoreline Analysis System (DSAS) version 5.1 transects with long-term linear regression rate calculations for the exposed eastern Beaufort Sea coast of Alaska from the U.S. Canadian Border to the Hulahula River

This dataset consists of long-term (70 years) shoreline change rates for the exposed, open-ocean coast of Alaska from the U.S. Canadian Border to the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2017. A reference ...

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Digital Shoreline Analysis System (DSAS) version 5.1 transects with short-term linear regression rate calculations for the exposed eastern Beaufort Sea coast of Alaska from the U.S. Canadian Border to the Hulahula River

This dataset consists of short-term (less than 39 years) shoreline change rates for the exposed, open-ocean coast of Alaska from the U.S. Canadian Border to the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1978 and 2017. A ...

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Midshore baseline for the sheltered eastern Beaufort Sea coast of Alaska (U.S. Canadian Border to the Hulahula River) generated to calculate shoreline change rates

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the mainland coast of Alaska sheltered by barrier islands from the U.S. Canadian Border to the Hulahula River for the time period 1947 to 2017. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

Info
Digital Shoreline Analysis System (DSAS) version 5.1 transects with long-term linear regression rate calculations for the sheltered eastern Beaufort Sea coast of Alaska from the U.S. Canadian Border to the Hulahula River

This dataset consists of long-term (70 years) shoreline change rates for the mainland coast of Alaska sheltered by barrier islands from the U.S. Canadian Border to the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2017. A ...

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Digital Shoreline Analysis System (DSAS) version 5.1 transects with short-term linear regression rate calculations for the sheltered eastern Beaufort Sea coast of Alaska from the U.S. Canadian Border to the Hulahula River

This dataset consists of short-term (less than 39 years) shoreline change rates for the mainland coast of Alaska sheltered by barrier islands from the U.S. Canadian Border to the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1978 ...

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Shorelines from 1947 to 2017 for the eastern Beaufort Sea coast of Alaska (U.S. Canadian Border to the Hulahula River) used in shoreline change analysis

This dataset includes historical shoreline positions that span 70 years, from 1947 to 2017, for the north coast of Alaska between the U.S. Canadian Border to the Hulahula River. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), Conoco-Philips (CP), British Petroleum Alaska (BPXA), and NOAA), satellite imagery (U.S. Fish and ...

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Projected coastal flooding depths for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flood depth GeoTIFFs based on sea-level rise and wave-driven total water levels for the coast of the American Samoa’s most populated islands of Tutuila, Ofu-Olosega, and Tau. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated American Samoan Islands due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to ...

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Projected coastal flooding depths for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Mariana Islands

This data release provides flood depth GeoTIFFs based on sea-level rise and wave-driven total water levels for the coast of the most populated Mariana Islands of Guam and Saipan. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Mariana Islands due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 ...

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Projected coastal flooding depths for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian Islands (ver. 1.1, September 2024)

This data release provides flood depth GeoTIFFs based on sea-level rise and wave-driven total water levels for the coast of the most populated Hawaiian Islands of Oahu, Molokai, Kauai, Maui, and Big Island. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Hawaiian Islands due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves ...

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Projected coastal flooding extents for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flooding extent polygons based on sea-level rise and wave-driven total water levels for the coast of American Samoa's most populated islands of Tutuila, Ofu-Olosega, and Tau. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 resolution ...

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Projected coastal flooding extents for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Mariana Islands

This data release provides flooding extent polygons based on sea-level rise and wave-driven total water levels for the coast of the most populated Mariana Islands of Guam and Saipan. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 resolution along these islands' ...

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Projected coastal flooding extents for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian Islands

This data release provides flooding extent polygons based on sea-level rise and wave-driven total water levels for the coast of the most populated Hawaiian Islands of Oahu, Molokai, Kauai, Maui, and Big Island. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 ...

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Projected coastal flooding inundation depths for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flood depth GeoTIFFs based on sea-level rise (SLR) for the coast of the most populated American Samoa s most populated islands of Tutuila, Ofu-Olosega, and Ta'u. Digital elevation models were used to extract SLR flooded areas at 10-m2 resolution along the coastlines for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR scenarios.

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Projected coastal flooding inundation depths for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Mariana Islands

This data release provides flood depth GeoTIFFs based on sea-level rise for the coast of the most populated Mariana Islands of Guam and Saipan. Digital elevation models were used to extract sea-level rise flooded areas at 10-m2 resolution along the coastlines for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios.

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Projected coastal flooding inundation depths for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian Islands

This data release provides flood depth GeoTIFFs based on potential future sea-level rise (SLR)for the coast of the most populated Hawaiian Islands of O'ahu, Moloka'i, Kaua'i, Maui, and Big Island. Digital elevation models were used to extract SLR flooded areas at 10-m2 resolution along the coastlines for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR scenarios.

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Projected sea-level rise flooding inundation extents for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flooding extent polygons based on sea-level rise (SLR) water levels for the coast of American Samoa's most populated islands of Tutuila, Ofu-Olosega, and Ta'u. Digital elevation models were used to predict SLR flooding extents for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR scenarios.

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Projected sea-level rise flooding inundation extents for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter in the Mariana Islands

This data release provides flooding extent polygons based on potential future sea-level rise (SLR) rise water levels for the coast of the most populated Mariana Islands of Guam and Saipan. Digital elevation models were used to predict SLR flooding extents for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR rise scenarios.

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Projected sea-level rise flooding inundation extents for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian Islands

This data release provides flooding extent polygons based on potential future sea-level rise (SLR) water levels for the coast of the most populated Hawaiian Islands of O'ahu, Moloka'i, Kaua'i, Maui, and Big Island. Digital elevation models were used to extract SLR flooded areas along the coastlines at 10-m2 resolution and converted to polygon shapefiles of the extents for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR scenarios.

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Reference baselines used to extract shorelines for the West Coast of the United States (ver. 1.1, September 2024)

This data release contains reference baselines for primarily open-ocean sandy beaches along the west coast of the United States (California, Oregon and Washington). The slopes were calculated while extracting shoreline position from lidar point cloud data collected between 2002 and 2011. The shoreline positions have been previously published, but the slopes have not. A reference baseline was defined and then evenly-spaced cross-shore beach transects were created. Then all data points within 1 meter of each ...

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Beach foreshore slope for the West Coast of the United States (ver. 1.1, September 2024)

This data release contains foreshore slopes for primarily open-ocean sandy beaches along the west coast of the United States (California, Oregon and Washington). The slopes were calculated while extracting shoreline position from lidar point cloud data collected between 2002 and 2011. The shoreline positions have been previously published, but the slopes have not. A reference baseline was defined and then evenly-spaced cross-shore beach transects were created. Then all data points within 1 meter of each ...

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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, ...