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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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Introduction In 2012, Hurricane Sandy created an open breach in the barrier island system along the south shore of Long Island, N.Y. This breach formed at a location known as Old Inlet and migrated rapidly westward over the winter storm season following Hurricane Sandy. In response, the National Park Service sought assistance from the USGS New York Water Science Center to help evaluate the hydrodynamics and geomorphology of the breach. The evaluation is centered on measurement of water velocities and depths within the breach, and collection of water levels with the Great South Bay adjacent to the breach. This project is part of a larger ongoing study prepared in coordination with the National Park Service...
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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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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 forecast products to coastal wetlands, including the Fire Island National Seashore and Central Great South Bay salt marshes, with the intent of providing Federal, State, and local managers with tools to estimate...
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Fire Island National Seashore (FIIS) is located on the barrier island along the extreme southern shore of western and central Suffolk County, New York. Interspersed throughout FIIS are seventeen residential beach communities that in the summer months greatly increase in population due to the arrival of summer residents and vacationers. Wastewater from the numerous homes and businesses in the barrier island communities generally is discharged directly into the shallow ground-water system through use of private septic systems. Contaminants entering the ground-water system can pose a threat to coastal habitats, as they are transported by ground water that discharges to ocean and estuary shorelines. In October 2004,...
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The Bathymetry surface was created by plotting depths of all data points collected relative to North American Vertical Datum of 1988 (NAVD 88), which was converted using the Vertical Datum Transformation tool created by the National Oceanic and Atmospheric Administration's (NOAA) National Geodetic Survey, Office of Coast Survey, and Center for Operation Oceanographic Products and Services. The elevation of the bathymetric raster surface was interpolated between these points in a GIS using a spline interpolator. A total of 432 points were used for interpolation. The points were used as the input to create a polygon feature class. The Spline tool was applied using the points and polygon to interpolate the bathymetric...
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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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The Bathymetry surface was created by plotting depths of all data points collected relative to North American Vertical Datum of 1988 (NAVD 88), which was converted using the Vertical Datum Transformation tool created by the National Oceanic and Atmospheric Administration's (NOAA) National Geodetic Survey, Office of Coast Survey, and Center for Operation Oceanographic Products and Services. The elevation of the bathymetric raster surface was interpolated between these points in a GIS using a spline interpolator. A total of 432 points were used for interpolation. The points were used as the input to create a polygon feature class. The Spline tool was applied using the points and polygon to interpolate the bathymetric...
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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...
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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...
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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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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 by Defne and Ganju (2018). MN was based on the calculated difference in height between mean high water (MHW) and mean low water (MLW) using the VDatum (v3.5) database ( http://vdatum.noaa.gov/ ). Through scientific...
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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 Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands, including the Fire Island National Seashore and central Great South...


map background search result map search result map Simulation of the Shallow Ground-Water Flow System at Fire Island National Seashore, Long Island, New York Bathymetric and Tidal Discharge data for Wilderness Breach, Fire Island National Seashore, Long Island, NY, May 14, 2015 Bathymetry Raster Surface Bathymetry Contours Conceptual marsh units for Fire Island National Seashore and central Great South Bay salt marsh complex, New York Unvegetated to vegetated marsh ratio in Fire Island National Seashore and Central Great South Bay salt marsh complex, New York Mean tidal range in marsh units of Fire Island National Seashore and Central Great South Bay salt marsh complex, New York DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2010 Development: Development delineation: Fire Island, NY, 2010–2011 DisOcean: Distance to the ocean: Fire Island, NY, 2010 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fire Island, NY, 2010–2011 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2012 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): 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: 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: Fire Island, NY, 2014 Development: Development delineation: Fire Island, NY, 2014–2015 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2014–2015 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 Bathymetry Contours Bathymetric and Tidal Discharge data for Wilderness Breach, Fire Island National Seashore, Long Island, NY, May 14, 2015 Bathymetry Raster Surface Development: Development delineation: Fire Island, NY, 2014–2015 Development: Development delineation: Fire Island, NY, 2010–2011 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: Fire Island, NY, 2014 DisOcean: Distance to the ocean: Fire Island, NY, 2010 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2012 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2014–2015 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2010 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2012 Simulation of the Shallow Ground-Water Flow System at Fire Island National Seashore, Long Island, New York points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fire Island, NY, 2010–2011 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fire Island, NY, 2012 Unvegetated to vegetated marsh ratio in Fire Island National Seashore and Central Great South Bay salt marsh complex, New York Mean tidal range in marsh units of Fire Island National Seashore and Central Great South Bay salt marsh complex, New York Conceptual marsh units for Fire Island National Seashore and central Great South Bay salt marsh complex, New York