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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: Atlantic Ocean, Barrier Island, Bayesian Network, CMHRP, Cape Cod, 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...
Airborne electromagnetic (AEM) and magnetic survey data were collected during February 2016 along 300 line kilometers in the western Yukon Flats near Stevens Village, Alaska. Data were acquired with the CGG RESOLVE frequency-domain helicopter-borne electromagnetic systems together with a Scintrex Cesium Vapour CS-3 magnetometer. The AEM average depth of investigation is about 100 m. The survey was flown at a nominal flight height of 30 m above terrain along widely spaced reconnaissance lines. This data release includes raw and processed AEM data and laterally-constrained inverted resistivity depth sections along all flight lines. This release also includes unprocessed and processed magnetic data that has been drift...
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This part of DS 781 presents data for the sediment-thickness isopachs for the Pigeon Point to Monterey Bay, California, map region. The vector data file is included in "Isopachs_PigeonPointToMonterey.zip," which is accessible from https://doi.org/10.5066/F7N29V0Z. As part of the USGS's California State Waters Mapping Project, a 50-m-resolution grid of sediment thickness for the seafloor within the limit of California’s State Waters between Pigeon Point and southern Monterey Bay was generated from seismic-reflection data collected in 2009, 2010, and 2011 (USGS activities (S-15-10-NC, S-N1-09-MB, and S-06-11-MB) supplemented with outcrop and geologic structure from DS 781. Isopach contours at 2.5-meter intervals were...
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In 2004, about 90 migrating elk drowned after attempting to cross thin ice on the Mores Creek arm of Lucky Peak Lake upstream of the Highway 21 bridge. To better understand the depths over a range of reservoir pool elevations in the Mores Creek Arm, the U.S. Geological Survey, in cooperation with the Lucky Peak Power Plant Project, conducted high-resolution multibeam echosounder (MBES) bathymetric surveys on the Mores Creek arm on Lucky Peak Lake. The MBES data will assist reservoir managers and wildlife biologists with regulating reservoir water surface elevations (WSE) to support successful big game migration across Mores Creek on Lucky Peak Lake. Data collection provided nearly 100 percent coverage of bed elevations...
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This part of DS 781 presents data for the transgressive contours for the Point Conception to Hueneme Canyon, California, region. The vector file is included in "TransgressiveContours_PointConceptionToHuenemeCanyon.zip," which is accessible from http://dx.doi.org/10.5066/F7891424. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the 3-nautical mile limit between Point Conception and Hueneme Canyon was generated from seismic-reflection data collected in 2014 (USGS activity 2014-632-FA) supplemented with outcrop and geologic structure (fault) information following the methodology of Wong (2012). Water depths determined from bathymetry data were...
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This part of DS 781 presents data for the isopachs for the Point Conception to Hueneme Canyon, California, region. The vector data file is included in "Isopachs_PointConceptionToHuenemeCanyon.zip," which is accessible from https://doi.org/10.5066/F7891424. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the 3-nautical mile limit between Point Conception and Hueneme Canyon was generated from seismic-reflection data collected in 2014 (USGS activity 2014-632-FA) supplemented with outcrop and geologic structure (fault) information following the methodology of Wong (2012). This sediment thickness layer was merged with a previously published sediment...
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This dataset is the output of a python script/ArcGIS model that identifes dikes as having a difference in elevation above a certain threshold. If the elevation difference was below a certain threshold the area was not considered a dike; however, if the difference in elevation between two points was significantly high then the area was marked as a dike. Areas continuous with eachother were considered part of the same dike. Post processing occured. Users examined the data output, comparing the proposed dike locations to aerial imagery, flowline data, and the DEM. Dikes that appeared to be false positives were deleted from the data set.
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Airborne electromagnetic (AEM), magnetic, and radiometric data were acquired November 2019 to March 2020 along 24,030 line-kilometers (line-km) over the Mississippi Alluvial Plain (MAP). Data were acquired by CGG Canada Services, Ltd. with three different airborne sensors: the CGG Canada Services, Ltd. TEMPEST time-domain AEM instrument that is used to map subsurface geologic structure at depths up to 300 meters (m), depending on the subsurface resistivity; a Scintrex CS-3 cesium vapor magnetometer that detects changes in deep (hundreds of meters to kilometers) geologic structure based on variations in the magnetic properties of different formations; and a Radiation Solutions RS-500 spectrometer that detects the...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Arkansas, Arkansas River, GGGSC, Geology, Geophysics, and Geochemistry Science Center, Geophysics, All tags...
This dataset consists of rate-of-change statistics for the shorelines at Barter Island, Alaska for the time period 1947 to 2020. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate shoreline change rates.
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These metadata describe ship navigation tracklines from a 2018 multibeam echosounder survey near Noyo Submarine Canyon and vicinity, southeast Alaska. Data were collected by the National Oceanic and Atmospheric Administration (NOAA) aboard the NOAA survey vessel Fairweather and the data were post-processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) for PCMSC research projects. The tracklines are provided as a GIS shapefile.
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This part of DS 781 presents data for the isopachs of the Point Sur to Point Arguello, California, region. The vector data file is included in the “Isopachs_PointSurToPointArguello.zip,” which is accessible from https://doi.org/10.5066/P97CZ0T7. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the 3-nautical mile limit between Point Sur and Point Arguello was generated from seismic-reflection data collected between 2008 and 2014, and supplemented with geologic structure (fault and fold) information following the methodology of Wong (2012). Reference Cited: Wong, F. L., Phillips, E.L., Johnson, S.Y., and Sliter, R.W., 2012, Modeling of depth...
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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 photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the Digital Shoreline Analysis System software to compute their rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling scientists 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...
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This data release contains coastal wetland synthesis products for Massachusetts, developed in collaboration with the Massachusetts Office of Coastal Zone Management. 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 tools to estimate the vulnerability and ecosystem service potential of these wetlands....
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Buzzards Bay, Cape Cod, Cape Cod Bay, Cape Cod National Seashore, Danvers River, 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 photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the Digital Shoreline Analysis System software to compute their rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling scientists 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...
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Note: The 2022 data release "Geospatial Characterization of Salt Marshes in Chesapeake Bay" incorporates the Blackwater region salt marsh dataset. (https://doi.org/10.5066/P997EJYB) This data release contains coastal wetland synthesis products for the geographic region of Blackwater salt marsh complex, Chesapeake Bay, Maryland. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and others, 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...
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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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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...


map background search result map search result map Isopachs--Pigeon Point to Monterey, California Western Lake Erie Restoration Assessment Dikes Isopachs--Point Conception to Hueneme Canyon, California Transgressive Contours--Point Conception to Hueneme Canyon, California Airborne electromagnetic and magnetic survey data and inverted resistivity models, western Yukon Flats, Alaska, February 2016 Unvegetated to vegetated marsh ratio in Fire Island National Seashore and Central Great South Bay salt marsh complex, New York Baseline for the southern coast Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Isopachs—Point Sur to Point Arguello, California 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, 2010 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Monomoy Island, MA, 2013-2014 Development: Development delineation: Parker River, MA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD & VA, 2014 Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2019 - March 2020 Digital Shoreline Analysis System (DSAS) version 5.0 transects with shoreline rate change calculations at Barter Island Alaska, 1947 to 2020 Elevation of marsh units in Blackwater salt marsh complex, Chesapeake Bay, Maryland Unvegetated to vegetated ratio of marsh units in Massachusetts salt marshes Mores Creek Arm Bathymetric Survey - Depth Contours, Lucky Peak Lake, Boise County, Idaho, May 11 - 13, 2021 2015 Mean High Water Shorelines of the Puerto Rico Coast used in Shoreline Change Analysis 2016 NOAA Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis Ship navigation tracklines from a 2018 multibeam survey near Noyes Submarine Canyon, southeast Alaska Mores Creek Arm Bathymetric Survey - Depth Contours, Lucky Peak Lake, Boise County, Idaho, May 11 - 13, 2021 Development: Development delineation: Parker River, MA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Monomoy Island, MA, 2013-2014 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, 2010 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD & VA, 2014 Elevation of marsh units in Blackwater salt marsh complex, Chesapeake Bay, Maryland Isopachs--Pigeon Point to Monterey, California Airborne electromagnetic and magnetic survey data and inverted resistivity models, western Yukon Flats, Alaska, February 2016 Ship navigation tracklines from a 2018 multibeam survey near Noyes Submarine Canyon, southeast Alaska Isopachs--Point Conception to Hueneme Canyon, California Transgressive Contours--Point Conception to Hueneme Canyon, California 2016 NOAA Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis 2015 Mean High Water Shorelines of the Puerto Rico Coast used in Shoreline Change Analysis Western Lake Erie Restoration Assessment Dikes Unvegetated to vegetated ratio of marsh units in Massachusetts salt marshes Isopachs—Point Sur to Point Arguello, California Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2019 - March 2020