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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 along the southeast US coastline and implications for vulnerability to future storms. Shoreline positions were compiled prior to and following Hurricane Irma along the sandy shorelines of the Gulf of Mexico and Atlantic...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Atlantic Coast, Baseline, CMGP, Coastal and Marine Geology Program, DSAS, All tags...
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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 most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change. This data release and other associated products represent an expansion...
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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 most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change. This data release and other associated products represent an expansion...
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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 the magnitude of the threat posed by sea-level rise, and the urgency to better understand it, there is an increasing need to forecast sea-level rise effects on barrier islands. To address this problem, scientists in the U.S. Geological Survey (USGS) Coastal and Marine Geology program are developing Bayesian networks as a tool to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as the piping plover (Charadrius melodus)...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Assateague Island, Assateague Island, Assateague Island National Seashore, Assateague Island National Seashore, Atlantic Ocean, All tags...
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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 the magnitude of the threat posed by sea-level rise, and the urgency to better understand it, there is an increasing need to forecast sea-level rise effects on barrier islands. To address this problem, scientists in the U.S. Geological Survey (USGS) Coastal and Marine Geology program are developing Bayesian networks as a tool to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as the piping plover (Charadrius melodus)...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Assateague Island, Assateague Island, Assateague Island National Seashore, Assateague Island National Seashore, Atlantic Ocean, All tags...
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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 data release includes two new mean high water (MHW) shorelines extracted from lidar data collected in 2010 and 2017-2018. Previously published historical shorelines for South Carolina (Kratzmann and others, 2017)...
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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 transect were associated with each transect. Next, it was determined which points were one the foreshore, and then a linear regression was fit through the foreshore points. Beach slope was defined as the slope of...
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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. A reference baseline was defined, and then 20-meter equally-spaced cross-shore beach transects were created perependicular to the baseline. All data points within 1-meter (along-shore) of each transect were associated with that transect. For each transect, the points on the foreshore were identified, and a linear regression was fit through the foreshore points. Beach...
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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 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 federal, state, and local managers with...
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In September 2018, the U.S. Geological Survey, in collaboration with the U.S. Army Corps of Engineers, conducted high-resolution geophysical mapping and sediment sampling to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands,” were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present. Mapping was focused offshore of the town of Gay on the Keweenaw Peninsula of Michigan, where ongoing erosion and re-deposition of the stamp sands has buried miles of native, white-sand beaches. Stamp sands are also encroaching onto Buffalo Reef, a large...
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In summer 2018, the U.S. Geological Survey partnered with the U.S Department of Energy and the Bureau of Ocean Energy Management to conduct the Mid-Atlantic Resources Imaging Experiment (MATRIX) as part of the U.S. Geological Survey Gas Hydrates Project. The field program objectives were to acquire high-resolution 2-dimensional multichannel seismic-reflection and split-beam echosounder data along the U.S Atlantic margin between North Carolina and New Jersey to determine the distribution of methane gas hydrates in below-sea floor sediments and investigate potential connections between gas hydrate dynamics and sea floor methane seepage. MATRIX field work was carried out between August 8 and August 28, 2018 on the...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Atlantic Ocean, BOEM, Bureau of Ocean Energy Management, CMHRP, Cape Hatteras, All tags...
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In summer 2018, the U.S. Geological Survey partnered with the U.S Department of Energy and the Bureau of Ocean Energy Management to conduct the Mid-Atlantic Resources Imaging Experiment (MATRIX) as part of the U.S. Geological Survey Gas Hydrates Project. The field program objectives were to acquire high-resolution 2-dimensional multichannel seismic-reflection and split-beam echosounder data along the U.S Atlantic margin between North Carolina and New Jersey to determine the distribution of methane gas hydrates in below-sea floor sediments and investigate potential connections between gas hydrate dynamics and sea floor methane seepage. MATRIX field work was carried out between August 8 and August 28, 2018 on the...
Categories: Data, Data Release - In Progress; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Atlantic Ocean, BOEM, Bureau of Ocean Energy Management, CMHRP, Cape Hatteras, All tags...
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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 available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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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 available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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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 available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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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 available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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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 available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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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 available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMGP, Coastal Erosion, All tags...
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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 available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Assawoman Island, Assawoman Island, Atlantic Ocean, Barrier Island, Bayesian Network, All tags...
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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 available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...


map background search result map search result map Development: Development delineation: Edwin B. Forsythe NWR, NJ, 2012 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2013–2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2010 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2012 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2012 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rockaway Peninsula, NY, 2010 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 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Myrtle Island, VA, 2014 Seismic Reflection, EdgeTech SB-424 Chirp tracklines collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS field activity 2018-043-FA, (Esri polyline shapefile, GCS WGS 84) Multichannel Seismic-Reflection and Navigation Data Collected Using Sercel GI Guns and Geometrics GeoEel Digital Streamers During the Mid-Atlantic Resource Imaging Experiment (MATRIX), USGS Field Activity 2018-002-FA Split-beam Echo Sounder and Navigation Data Collected Using a Simrad EK80 Wide Band Tranceiver and ES38-10 Transducer During the Mid-Atlantic Resource Imaging Experiment (MATRIX), USGS Field Activity 2018-002-FA. 2010 Shorelines for Vieques, Culebra, and Main Island of Puerto Rico 1970s Shorelines for Vieques and Culebra, Puerto Rico Shorelines of the Florida panhandle (FLph) coastal region used in shoreline change analysis Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2008 Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2014 Mean tidal range of marsh units in Eastern Shore of Virginia salt marshes 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 Beach foreshore slope for the West Coast of the United States Beach foreshore slope for the East Coast of the United States shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Myrtle Island, VA, 2014 Seismic Reflection, EdgeTech SB-424 Chirp tracklines collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS field activity 2018-043-FA, (Esri polyline shapefile, GCS WGS 84) 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 Development: Development delineation: Edwin B. Forsythe NWR, NJ, 2012 1970s Shorelines for Vieques and Culebra, Puerto Rico shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2012 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2013–2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2010 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2012 Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2008 Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2014 Mean tidal range of marsh units in Eastern Shore of Virginia salt marshes 2010 Shorelines for Vieques, Culebra, and Main Island of Puerto Rico Shorelines of the Florida panhandle (FLph) coastal region used in shoreline change analysis 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 Multichannel Seismic-Reflection and Navigation Data Collected Using Sercel GI Guns and Geometrics GeoEel Digital Streamers During the Mid-Atlantic Resource Imaging Experiment (MATRIX), USGS Field Activity 2018-002-FA Split-beam Echo Sounder and Navigation Data Collected Using a Simrad EK80 Wide Band Tranceiver and ES38-10 Transducer During the Mid-Atlantic Resource Imaging Experiment (MATRIX), USGS Field Activity 2018-002-FA. Beach foreshore slope for the West Coast of the United States Beach foreshore slope for the East Coast of the United States