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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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Sandy ocean beaches in the United States are popular tourist and recreational destinations and constitute some of the most valuable real estate in the country. The boundary between land and water along the coastline is often the location of concentrated residential and commercial development and is frequently exposed to a range of natural hazards, which include flooding, storm effects, and coastal erosion. In response, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change hazards. One component of this research effort, the National Assessment of Shoreline Change Project (http://coastal.er.usgs.gov/shoreline-change/), documents changes in shoreline position as a proxy for coastal...
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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, CMHRP, Cape Ann, 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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Sandy ocean beaches in the United States are popular tourist and recreational destinations and constitute some of the most valuable real estate in the country. The boundary between land and water along the coastline is often the location of concentrated residential and commercial development and is frequently exposed to a range of natural hazards, which include flooding, storm effects, and coastal erosion. In response, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change hazards. One component of this research effort, the National Assessment of Shoreline Change Project, documents changes in shoreline position as a proxy for coastal change. Shoreline position is an easily understood...
Categories: Data; Types: Citation, Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Breton Islands, Breton National Wildlife Refuge, CMGP, Chandeleur Islands, Coastal and Marine Geology Program, 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, Cedar Island, All tags...
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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 aerial orthoimagery and 2007 topographic lidar datasets obtained from the National Oceanic and Atmospheric Administration's Ocean Service, Coastal Services Center. This 2018 data release includes rates that incorporate...
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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 2008-2009 color aerial orthoimagery and 2007 topographic lidar datasets obtained from NOAA's Ocean Service, Coastal Services Center. This 2018 update includes two new mean high water (MHW) shorelines for the Massachusetts...
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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 aerial orthoimagery and 2007 topographic lidar datasets obtained from the National Oceanic and Atmospheric Administration's Ocean Service, Coastal Services Center. This 2018 data release includes rates that incorporate...
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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 aerial orthoimagery and 2007 topographic lidar datasets obtained from the National Oceanic and Atmospheric Administration's Ocean Service, Coastal Services Center. This 2018 data release includes rates that incorporate...
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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 aerial orthoimagery and 2007 topographic lidar datasets obtained from the National Oceanic and Atmospheric Administration's Ocean Service, Coastal Services Center. This 2018 data release includes rates that incorporate...
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This data set contains rate of shoreline change statistics for New York State coastal wetlands. Analysis was performed in ArcMap 10.5.1 using historical vector shoreline data from the National Oceanic and Atmospheric Administration (NOAA). Rate of change statistics were calculated using the Digital Shoreline Analysis System (DSAS), created by U.S. Geological Survey, version 5.0. End-point rates, calculated by dividing the distance of shoreline movement by the time elapsed between the oldest and the most recent shoreline, were generated for wetlands where fewer than three historic shorelines were available. Linear regression rates, presented here, were determined by fitting a least-squares regression line to...
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Two marine geological surveys were conducted in Nantucket Sound, Massachusetts, in May 2016 and May 2017 by the U.S. Geological Survey as part of an agreement with the Massachusetts Office of Coastal Zone Management to map the geology of the sea floor offshore of Massachusetts. Samples of surficial sediment and photographs of the sea floor were collected at 76 sampling sites within the survey area, and sea-floor videos were collected at 75 of the sites. The sediment data and the observations from the photos and videos are used to explore the nature of the sea floor; in conjunction with high-resolution geophysical data, the observations are used to make interpretive maps of sedimentary environments and validate acoustic...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Atlantic Ocean, Beckman Coulter Multisizer 3, CMHRP, CSV, CZM, All tags...


map background search result map search result map Shorelines of the Louisiana coastal region used in shoreline change analysis Shorelines of the western North Carolina (NCwest) coastal region used in shoreline change analysis Linear regression rate of shoreline change statistics for New York State coastal wetlands 2010 profile-derived mean high water shorelines of the South Coast of MA used in shoreline change analysis Baseline for the coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Baseline for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Intersects for the coast south of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Baseline for the backshore of Outer Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 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, 2013–2014 DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2010 ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2014 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 DisOcean: Distance to the ocean: Cape Hatteras, NC, 2014 ElevMHW: Elevation adjusted to local mean high water: Cobb Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Smith Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Smith Island, VA, 2014 Location and grain-size analysis results of sediment samples collected in Nantucket Sound, Massachusetts, in May 2016 and May 2017 by the U.S. Geological Survey during field activities 2016-005-FA and 2017-022-FA (simplified point shapefile and CSV file) shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Smith Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Smith Island, VA, 2014 2010 profile-derived mean high water shorelines of the South Coast of MA used in shoreline change analysis 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, 2013–2014 Location and grain-size analysis results of sediment samples collected in Nantucket Sound, Massachusetts, in May 2016 and May 2017 by the U.S. Geological Survey during field activities 2016-005-FA and 2017-022-FA (simplified point shapefile and CSV file) Baseline for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 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 Baseline for the backshore of Outer Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Shorelines of the western North Carolina (NCwest) coastal region used in shoreline change analysis DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2010 ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2014 Baseline for the coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Intersects for the coast south of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 DisOcean: Distance to the ocean: Cape Hatteras, NC, 2014 Shorelines of the Louisiana coastal region used in shoreline change analysis Linear regression rate of shoreline change statistics for New York State coastal wetlands