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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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This data release provides a map of the time-averaged shear-wave velocity in the upper 30 m (Vs30) for California using the method described by Thompson and others (2014). There are two adjustments to the algorithm described by Thompson and others (2014), which is built on the geology-based Vs30 map by Wills and Clahan (2006). In this data release, we use the Wills and others (2015) updated geology-based Vs30 map. The second change is that we have adjusted the kriging procedure so that measured Vs30 values do not affect the predictions across distinctly different geologic units. July 2022 Update (ver. 2.0) Resolution is now 3 arcseconds instead of 7.5 arcseconds Fixed a code error that prevented some of the Vs30...
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This data release comprises a georeferenced raster layer depicting the estimated susceptibility to intense rainfall-induced landslides in Puerto Rico, which is a supplement to: Hughes, K.S., and Schulz, W.H., 2020, Map depicting susceptibility to landslides triggered by intense rainfall, Puerto Rico: U.S. Geological Survey Open-File Report 2020–1022, 91 p., 1 plate, scale 1:150,000, https://doi.org/10.3133/ofr20201022. Users of this layer are strongly encouraged to read the text herein and available with Open-File Report 2020-1022. DEVELOPMENT OF THE LANDSLIDE SUSCEPTIBILITY MAP Landslides commonly occur in Puerto Rico during or soon after intense rainfall and present significant hazards to the built environment...
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Gravity data were collected in August of 2019 at 21 sites on and around Iliamna Volcano and Anchorage, Alaska. Measurements were taken with a Lacoste & Romberg G-161 meter and reduced to obtain the complete Bouguer anomaly. A total of 39 magnetic susceptibility measurements were taken at 13 locations using a ZH Instruments SM30 susceptibility meter. This data release includes susceptibility measurements, processed gravity data, shapefiles with field locations, and site photos.
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A seismic hazard model for South America, based on a smoothed (gridded) seismicity model, a subduction model, a crustal fault model, and a ground motion model, has been produced by the U.S. Geological Survey. These models are combined to account for ground shaking from earthquakes on known faults as well as earthquakes on un-modeled faults. This data set represents the results of calculations of hazard curves for a grid of points with a spacing of 0.1 degrees in latitude and longitude. This particular data set is for Modified Mercalli Intensity with a 10 percent probability of exceedance in 50 years. The maps and data were derived from PGA ground-motion conversions of Worden et al. (2012), and include soil amplification...
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This part of DS 781 presents data for the seafloor-character map Offshore of Aptos, California. Seafloor-character data are provided as two separate grids depending on resolution of the mapping system and processing method. This metadata file refers to the data included in "SeafloorCharacter_2m_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016,...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Aptos, Backscatter, Bathymetry, CMHRP, Coastal and Marine Hazards and Resources Program, All tags...
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This part of DS 781 presents data for the shaded-relief map of Offshore of Aptos map area, California. Shaded-relief data are provided as two separate grids depending on mapping agency and processing method. This metadata file refers to the data included in "BathymetryAHS_USGS_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State...
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This part of DS 781 presents data for the depth-to-transition map of the Punta Gorda to Point Arena, California, region. The raster data file is included in the "DepthToTransition_PuntaGordaToPointArena.zip," which is accessible from https://doi.org/10.5066/P9PNNI9H. 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 Punta Gorda and Point Arena was generated from seismic-reflection data collected between 2010 and 2012, and supplemented with geologic structure (fault) information following the methodology of Wong (2012). Water depths determined from bathymetry data were added to the sediment thickness data to provide...
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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, Raster; Tags: Atlantic Ocean, Barrier Island, CMHRP, Coastal Habitat, 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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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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In 2015 the U.S. Geological Survey, Pacific Coastal and Marine Science Center, in cooperation with the Alaska Department of Fish and Game (ADFG), collected bathymetry and acoustic-backscatter data near Cross Sound in southeast Alaska using a Reson 7111 multibeam echosounder mounded to the ADFG R/V Solstice. This section of the data release provides the bathymetry data as a GeoTIFF at 10-m spatial resolution. All files have accompanying FGDC metadata.


map background search result map search result map BathymetryA Hillshade [USGS]--Offshore Aptos, California Seafloor character, 2 m resolution--Offshore of Aptos, California Modified Mercalli Intensity, based on peak ground acceleration, with a 10% probability of exceedance in 50 years An Updated Vs30 Map for California with Geologic and Topographic Constraints (ver. 2.0, July 2022) Multibeam bathymetry data collected in 2015 near Cross Sound, southeast Alaska, during field activity 2015-629-FA Depth to Transition--Punta Gorda to Point Arena, California DisOcean: Distance to the ocean: Coast Guard Beach, MA, 2014 ElevMHW: Elevation adjusted to local mean high water: Coast Guard Beach, MA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parker River, MA, 2014 DisOcean: Distance to the ocean: Rhode Island National Wildlife Refuge, RI, 2014 DisOcean: Distance to the ocean: Assateague Island, MD & VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Fisherman Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Metompkin Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Myrtle Island, VA, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Parramore Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Ship Shoal Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: 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: Wreck Island, VA, 2014 Bouguer gravity and magnetic susceptibility measurements at Iliamna Volcano, Alaska 2019 Geographic Information System Layer of a Map Depicting Susceptibility to Landslides Triggered by Intense Rainfall, Puerto Rico ElevMHW: Elevation adjusted to local mean high water: Wreck Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Ship Shoal Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Fisherman Island, VA, 2014 DisOcean: Distance to the ocean: Coast Guard Beach, MA, 2014 ElevMHW: Elevation adjusted to local mean high water: Coast Guard Beach, MA, 2014 ElevMHW: Elevation adjusted to local mean high water: Myrtle 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: Wreck Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Metompkin Island, VA, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Parramore Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parker River, MA, 2014 BathymetryA Hillshade [USGS]--Offshore Aptos, California Seafloor character, 2 m resolution--Offshore of Aptos, California Multibeam bathymetry data collected in 2015 near Cross Sound, southeast Alaska, during field activity 2015-629-FA Depth to Transition--Punta Gorda to Point Arena, California Geographic Information System Layer of a Map Depicting Susceptibility to Landslides Triggered by Intense Rainfall, Puerto Rico Bouguer gravity and magnetic susceptibility measurements at Iliamna Volcano, Alaska 2019 An Updated Vs30 Map for California with Geologic and Topographic Constraints (ver. 2.0, July 2022) Modified Mercalli Intensity, based on peak ground acceleration, with a 10% probability of exceedance in 50 years