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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 from a 1998 multibeam survey of the sea floor offshore of Fire Island Inlet, New York. There are five datasets: bathymetry grid, shaded-relief image, backscatter intensity image, shaded-relief colored by backscatter intensity image, and trackline navigation. The bathymetry shows the shape of the sea floor. Of particular interest are the size, shape, and orientation of bed forms that may indicate sediment movement. The shaded-relief image provides a visualization of the bathymetry that accentuates small features that cannot be effectively shown as contours alone. The image of backscatter intensity provides qualitative information on the sediment texture and roughness of the sea floor. The image of...
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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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Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, Shinnecock Inlet, and southwest of Montauk Point were about 1 kilometer (km) wide and 10 km long. The area was mapped by the U.S. Geological Survey with support from the Canadian Hydrographic Service and the University...
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Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, Shinnecock Inlet, and southwest of Montauk Point were about 1 kilometer (km) wide and 10 km long. The area was mapped by the U.S. Geological Survey with support from the Canadian Hydrographic Service and the University...
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Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, Shinnecock Inlet, and southwest of Montauk Point were about 1 kilometer (km) wide and 10 km long. The area was mapped by the U.S. Geological Survey with support from the Canadian Hydrographic Service and the University...
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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...
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Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and use along their Atlantic Coast breeding range. A smartphone application called iPlover was developed to collect standardized data on habitat characteristics at piping plover nest locations. The application capitalized on a network of trained monitors that observe piping plovers throughout their U.S. Atlantic coast breeding range as...
Categories: Data; Tags: Assateague Island, Atlantic Margin, CMGP, Cape Cod, Cape Lookout, 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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Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, Shinnecock Inlet, and southwest of Montauk Point were about 1 kilometer (km) wide and 10 km long. The area was mapped by the U.S. Geological Survey with support from the Canadian Hydrographic Service and the University...
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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...


map background search result map search result map Bathymetry and Backscatter Intensity of the Sea Floor South of Long Island, New York Offshore of Fire Island Inlet, New York GeoTIFF image of the backscatter intensity of the sea floor offshore of Fire Island Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84) GeoTIFF image of shaded-relief bathymetry, colored by backscatter intensity, of the sea floor offshore of Fire Island Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84) Tracklines of a multibeam survey of the sea floor offshore of Fire Island Inlet, New York, in 1998 (polyline shapefile, geographic, WGS 84) USGS 1:62500-scale Quadrangle for Fire Island, NY 1903 USGS 1:62500-scale Quadrangle for Fire Island, NY 1903 USGS 1:62500-scale Quadrangle for Fire Island, NY 1903 Table and accompanying photographs for biogeomorphic classification of shorebird nesting sites on the U.S. Atlantic coast from March to September, 2016 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2010–2011 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2010 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2010–2011 Development: Development delineation: Fire Island, NY, 2012 DisOcean: Distance to the ocean: Fire Island, NY, 2012 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2012 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): 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, 2014 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, 2014–2015 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2014–2015 Offshore of Fire Island Inlet, New York GeoTIFF image of the backscatter intensity of the sea floor offshore of Fire Island Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84) GeoTIFF image of shaded-relief bathymetry, colored by backscatter intensity, of the sea floor offshore of Fire Island Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84) Tracklines of a multibeam survey of the sea floor offshore of Fire Island Inlet, New York, in 1998 (polyline shapefile, geographic, WGS 84) USGS 1:62500-scale Quadrangle for Fire Island, NY 1903 USGS 1:62500-scale Quadrangle for Fire Island, NY 1903 USGS 1:62500-scale Quadrangle for Fire Island, NY 1903 Development: Development delineation: Fire Island, NY, 2012 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2014 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2010–2011 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2010–2011 DisOcean: Distance to the ocean: Fire Island, NY, 2012 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2012 DisOcean: Distance to the ocean: Fire Island, NY, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2014–2015 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2010 ElevMHW: Elevation adjusted to local mean high water: 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, 2014–2015 Bathymetry and Backscatter Intensity of the Sea Floor South of Long Island, New York Table and accompanying photographs for biogeomorphic classification of shorebird nesting sites on the U.S. Atlantic coast from March to September, 2016