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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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These data are a qualitatively derived interpretive polygon shapefile defining surficial sediment type and distribution, and geomorphology, for nearly 1,400 square kilometers of sea floor on the inner-continental shelf from Fenwick Island, Maryland to Fisherman’s Island, Virginia, USA. These data are classified according to Barnhardt and others (1998) bottom-type classification system, which was modified to highlight changes in secondary sediment-types such as mud and gravel across this primarily sandy shelf. Most of the geophysical and sample data used to create this interpretive layer were collected as part of the Linking Coastal Processes and Vulnerability: Assateague Island Regional Study project (GS2-2C), supported...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Assateague Island, Assateague Island National Seashore, Assawoman Island, Atlantic Ocean, Backscatter, 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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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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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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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...
thumbnail
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, Cedar Island, All tags...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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 Sediment Texture and Geomorphology of the Sea Floor from Fenwick Island, Maryland to Fisherman's Island, Virginia DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2010–2011 DisOcean: Distance to the ocean: Cedar Island, VA, 2010 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2010 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2010 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2010–2011 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 DisOcean: Distance to the ocean: Cedar Island, VA, 2012 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2012 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cedar Island, VA, 2012–2013 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2012 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013 DisOcean: Distance to the ocean: Cedar Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2013–2014 Geospatial characterization of salt marshes on the Eastern Shore of Virginia Conceptual marsh units of salt marshes on the Eastern Shore of Virginia Mean tidal range of marsh units in Eastern Shore of Virginia salt marshes Unvegetated to vegetated ratio of marsh units in Eastern Shore of Virginia salt marshes shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2012 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2010 DisOcean: Distance to the ocean: Cedar Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2010–2011 DisOcean: Distance to the ocean: Cedar Island, VA, 2010 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2010 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2010–2011 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 DisOcean: Distance to the ocean: Cedar Island, VA, 2012 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2012 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2013–2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cedar Island, VA, 2012–2013 Geospatial characterization of salt marshes on the Eastern Shore of Virginia Mean tidal range of marsh units in Eastern Shore of Virginia salt marshes Conceptual marsh units of salt marshes on the Eastern Shore of Virginia Unvegetated to vegetated ratio of marsh units in Eastern Shore of Virginia salt marshes Sediment Texture and Geomorphology of the Sea Floor from Fenwick Island, Maryland to Fisherman's Island, Virginia