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In September 2018, the USGS Woods Hole Coastal and Marine Science Center (WHCMSC), in collaboration with the US Army Corps of Engineers (USACE), conducted high-resolution geophysical mapping and sediment sampling to determine the distribution of historical mine tailings on the floor of Lake Superior. Large amounts of waste material from copper mining, locally known as “stamp sands”, were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present day. Mapping was focused offshore of the town of Gay on the Keweenaw Peninsula of Michigan, where ongoing erosion and re-deposition of the stamp sands has buried miles of native, white-sand beaches and is steadily...
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In spring and summer 2017, the U.S. Geological Survey’s Gas Hydrates Project conducted two cruises aboard the research vessel Hugh R. Sharp to explore the geology, chemistry, ecology, physics, and oceanography of sea-floor methane seeps and water column gas plumes on the northern U.S. Atlantic margin between the Baltimore and Keller Canyons. Split-beam and multibeam echo sounders and a chirp subbottom profiler were deployed during the cruises to map water column backscatter, sea-floor bathymetry and backscatter, and subsurface stratigraphy associated with known and undiscovered sea-floor methane seeps. The first cruise, known as the Interagency Mission for Methane Research on Seafloor Seeps and designated as field...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: 7160, Accomac Canyon, Atlantic Margin, Atlantic Ocean, CMHRP, 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 Hatteras, 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, 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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This dataset consists of short-term (less than 37 years) shoreline change rates for the sheltered north coast of Alaska from Icy Cape to Cape Prince of Wales. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.4, an ArcGIS extension developed by the U.S. Geological Survey. Rates of shoreline change were calculated using an end point rate-of-change (epr) method based on available shoreline data between 1980 and 2016. 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 rates of change.
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This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
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This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
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This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...
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This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios...
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High-resolution single-channel minisparker seismic-reflection data were collected by the U.S. Geological Survey in March and April 2007 from San Francisco to San Gregorio, offshore San Mateo County, California. Data were collected aboard the R/V Fulmar, during field activity F-02-07-NC. Minisparker data were collected using a SIG 2-mille minisparker sound source combined with a single-channel streamer, and recorded with a Triton SB-Logger.
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This dataset consists of short-term (less than 37 years) shoreline change rates for the north coast of Alaska from Icy Cape to Cape Prince of Wales. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.4, an ArcGIS extension developed by the U.S. Geological Survey. Rates of shoreline change were calculated using a linear regression rate-of-change (lrr) method based on available shoreline data between 1980s and 2016. 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 rates of change.
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This part of the data release contains high-resolution swath bathymetry data collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, Middle River in March 2018, and Mokelumne River in March 2018 using an interferometric bathymetric sidescan sonar systems mounted to the USGS R/V Parke Snavely. Data are provided in 1-m resolution GeoTIFF formats. These data were collected as part of a study on the effects of invasive aquatic vegetation on sediment transport in the Sacramento-San Joaquin Delta.
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This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...
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This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios...
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Time series data of water surface elevation, wave height, and water column currents and temperature were acquired at seven locations for 86 days off of Waiakane on the south coast of the island of Molokai, Hawaii, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs.
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These data are part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary (SBNMS) region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. The data were collected in collaboration with the Stellwagen Bank National Marine Sanctuary and will aid research on the ecology of fish and invertebrate species that inhabit the region. Sediment samples were collected aboard the Sanctuary's research vessel, R/V Auk at 679 locations on and near Stellwagen Bank using a customized Van Veen grab sampler integrated into the USGS SEABed...
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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...


map background search result map search result map Swath bathymetric data from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018 Minisparker seismic-reflection data of field activity F-02-07-NC collected offshore San Mateo County, California, from 2007-03-22 to 2007-04-06 CoSMoS v3.1 flood hazard projections: 1-year storm in San Barbara County CoSMoS v3.1 water level projections: 20-year storm in Santa Barbara County Waikane, Molokai, Hawaiian Islands, wave and water level data, 2018 CoSMoS v3.1 flood depth and duration projections: 20-year storm in San Francisco County CoSMoS v3.1 water level projections: average conditions in San Francisco County CoSMoS v3.1 flood hazard projections: 100-year storm in San Francisco County Location and analyses of sediment samples collected on Stellwagen Bank off Boston, Massachusetts from November 5, 2013 to April 30, 2019 on U.S. Geological Survey field activities points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Coast Guard Beach, MA, 2013-2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Monomoy Island, MA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: 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: Cape Hatteras, NC, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cobb Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Wreck Island, VA, 2014 Seismic Reflection, EdgeTech SB-424 Chirp shot points collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS field activity 2018-043-FA, (CSV text and Esri point shapefile, GCS WGS 84) Digital Shoreline Analysis System (DSAS) version 4.4 transects with short-term linear regression rate calculations for the exposed north coast of Alaska, from Icy Cape to Cape Prince of Wales Digital Shoreline Analysis System (DSAS) version 4.4 transects with short-term end-point rate-of-change calculations for the sheltered north coast of Alaska, from Icy Cape to Cape Prince of Wales Multibeam echo sounder - navigation tracklines for Reson 7160 data collected during USGS field activities 2017-001-FA and 2017-002-FA CoSMoS v3.1 ocean-currents hazards: 1-year storm in Santa Cruz County Waikane, Molokai, Hawaiian Islands, wave and water level data, 2018 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Wreck Island, VA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Coast Guard Beach, MA, 2013-2014 CoSMoS v3.1 flood depth and duration projections: 20-year storm in San Francisco County CoSMoS v3.1 water level projections: average conditions in San Francisco County CoSMoS v3.1 flood hazard projections: 100-year storm in San Francisco County Seismic Reflection, EdgeTech SB-424 Chirp shot points collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS field activity 2018-043-FA, (CSV text and Esri point shapefile, GCS WGS 84) shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Monomoy Island, MA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cobb Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Parker River, MA, 2014 CoSMoS v3.1 ocean-currents hazards: 1-year storm in Santa Cruz County Minisparker seismic-reflection data of field activity F-02-07-NC collected offshore San Mateo County, California, from 2007-03-22 to 2007-04-06 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cape Hatteras, NC, 2014 Multibeam echo sounder - navigation tracklines for Reson 7160 data collected during USGS field activities 2017-001-FA and 2017-002-FA Digital Shoreline Analysis System (DSAS) version 4.4 transects with short-term end-point rate-of-change calculations for the sheltered north coast of Alaska, from Icy Cape to Cape Prince of Wales Digital Shoreline Analysis System (DSAS) version 4.4 transects with short-term linear regression rate calculations for the exposed north coast of Alaska, from Icy Cape to Cape Prince of Wales