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The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg Inlet and along the southern end of Long Beach Island near Beach Haven, New Jersey was conducted from May 31 to June 10, 2018, followed by a sea floor sampling survey conducted from October 22 to 23, 2018, as part...
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The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg Inlet and along the southern end of Long Beach Island near Beach Haven, New Jersey was conducted from May 31 to June 10, 2018, followed by a sea floor sampling survey conducted from October 22 to 23, 2018, as part...
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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...
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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, 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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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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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: Accomac Canyon, Atlantic Ocean, CMHRP, Chincoteague Ridge, Coastal and Marine Hazards and Resources 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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This part of DS 781 presents data for the bathymetry map of Offshore Scott Creek, California. The raster data file is included in "Bathymetry_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets,...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acoustic Reflectivity, CMHRP, Coastal and Marine Hazards and Resources Program, Continental/Island Shelf, Marine Nearshore Subtidal, All tags...
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This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore of Scott Creek map area, California. The vector data file is included in "Faults_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File...
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This shapefile contains center-beam depths for approximately 5727 trackline kilometers of Simrad EM122 multibeam-bathymetry data collected in the Bering Sea during U.S. Geological Survey - Coastal and Marine Geology Program cruise MGL1111 aboard the R/V Marcus G. Langseth. The depth values were extracted from gridded data which were reduced for position, elevation, orientation, water-column sound-speed, and refraction effects.
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High-resolution single-channel Chirp and minisparker seismic-reflection data were collected by the U.S. Geological Survey in September and October 2006, offshore Bolinas to San Francisco, California. Data were collected aboard the R/V Lakota, during field activity L-1-06-SF. Chirp data were collected using an EdgeTech 512 chirp subbottom system and were recorded with a Triton SB-Logger. Minisparker data were collected using a SIG 2-mille minisparker sound source combined with a single-channel streamer, and both were recorded with a Triton SB-Logger.
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High-resolution single-channel minisparker seismic-reflection data were collected by the U.S. Geological Survey in September and October 2006 offshore Bolinas to San Francisco, California. Data were collected aboard the R/V Lakota, during field activity L-1-06-SF. 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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Bathymetric change grids covering the periods of time from 1934 to 2011, from 2011 to 2018, and from 1934 to 2018 are presented. The grids cover a portion of the Mokelumne River, California, starting at its terminus at the San Joaquin River and moving upriver to the confluences of the north and south branches of the Mokelumne. Positive grid values indicate accretion, or a shallowing of the surface bathymetric surface, and negative grid values indicate erosion, or a deepening of the bathymetric surface. Bathymetry data sources include the U.S. Geological Survey, California Department of Water Resources, and NOAA's National Ocean Service.


map background search result map search result map Bathymetry--Offshore of Scott Creek map area, California Faults--Offshore of Scott Creek map area, California MGL1109centerdepth.shp: Multibeam bathymetry data collected by the U.S. Geological Survey in the Gulf of Alaska in 2011 during cruise MGL1109, along-track center-beam depths extracted from 100-meter gridded data in shapefile format, geographic coordinates MGL1111centerdepth.shp: Multibeam bathymetry data collected by the U.S. Geological Survey in the Bering Sea in 2011 during cruise MGL1111, along-track center-beam depths extracted from 100-meter gridded data in shapefile format, geographic coordinates Bathymetric change analyses of the southernmost portion of the Mokelumne River, California, from 1934 to 2018 Chirp and minisparker seismic-reflection data of field activity L-1-06-SF collected offshore Bolinas to San Francisco, California from 2006-09-25 to 2006-10-03 Minisparker seismic-reflection data from field activity L-1-06-SF collected offshore Bolinas to San Francisco, California from 2006-09-25 to 2006-10-03 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 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Lookout, NC, 2014 Development: Development delineation: Cape Lookout, NC, 2014 ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rhode Island National Wildlife Refuge, RI, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD & VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Metompkin Island, VA, 2014 DisOcean: Distance to the ocean: Wreck Island, VA, 2014 Sound velocity profiles - locations, images, and text files for sound velocity profiles calculated from XBT and CTD casts conducted during USGS field activities 2017-001-FA and 2017-002 FA Chirp seismic reflection data from the Edgetech 512i collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS field activity 2018-001-FA (shotpoints point shapefile, survey trackline shapefile, PNG profile images, and SEG-Y trace data). Multibeam Echosounder, Reson T-20P tracklines collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS Field Activity 2018-001-FA (Esri polyline shapefile, GCS WGS 84) Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami elevation model of Half Moon Bay, California Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami elevation model of Half Moon Bay, California DisOcean: Distance to the ocean: Wreck Island, VA, 2014 Bathymetric change analyses of the southernmost portion of the Mokelumne River, California, from 1934 to 2018 Development: Development delineation: Cape Lookout, NC, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Metompkin Island, VA, 2014 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 Faults--Offshore of Scott Creek map area, California Bathymetry--Offshore of Scott Creek map area, California Chirp seismic reflection data from the Edgetech 512i collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS field activity 2018-001-FA (shotpoints point shapefile, survey trackline shapefile, PNG profile images, and SEG-Y trace data). Multibeam Echosounder, Reson T-20P tracklines collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS Field Activity 2018-001-FA (Esri polyline shapefile, GCS WGS 84) Minisparker seismic-reflection data from field activity L-1-06-SF collected offshore Bolinas to San Francisco, California from 2006-09-25 to 2006-10-03 Chirp and minisparker seismic-reflection data of field activity L-1-06-SF collected offshore Bolinas to San Francisco, California from 2006-09-25 to 2006-10-03 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rhode Island National Wildlife Refuge, RI, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD & VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Lookout, NC, 2014 Sound velocity profiles - locations, images, and text files for sound velocity profiles calculated from XBT and CTD casts conducted during USGS field activities 2017-001-FA and 2017-002 FA MGL1109centerdepth.shp: Multibeam bathymetry data collected by the U.S. Geological Survey in the Gulf of Alaska in 2011 during cruise MGL1109, along-track center-beam depths extracted from 100-meter gridded data in shapefile format, geographic coordinates MGL1111centerdepth.shp: Multibeam bathymetry data collected by the U.S. Geological Survey in the Bering Sea in 2011 during cruise MGL1111, along-track center-beam depths extracted from 100-meter gridded data in shapefile format, geographic coordinates