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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, 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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This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Aptos map area, California. Backscatter data are provided as two separate grids depending on mapping system and processing method. This metadata file refers to the data included in "BackscatterB_EM300_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...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acoustic Reflectivity, Aptos, Backscatter, Bathymetry, CMHRP, All tags...
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This database contains geometries and basic parameters for fault sections conisdered in earthquake rupture forecasts and probabilistic seismic hazard models (specifically, NSHM23).
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.
This data release contains mean high water (MHW) shorelines for sandy beaches along the coast of California for the years 1998/2002, 2015, and 2016. The MHW elevation in each analysis region (Northern, Central, and Southern California) maintained consistency with that of the National Assessment of Shoreline Change. The operational MHW line was extracted from Light Detection and Ranging (LiDAR) digital elevation models (DEMs) using the ArcGIS smoothed contour method. The smoothed contour line was then quality controlled to remove artifacts, as well as remove any contour tool interpretation of human-made infrastructure (such as jetties, piers, and sea walls), using satellite imagery from ArcGIS.
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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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These data are a geospatial representation of potential damage resulting from fires following the HayWired earthquake scenario, a magnitude 7.0 earthquake occurring on the Hayward Fault on April 18, 2018, with an epicenter in the city of Oakland, CA. These data take information about prevailing conditions (for example, average wind speed and direction) and potential hazard information (for example, ground shaking and liquefaction) and model the resulting fire-based damages which could occur following the HayWired scenario mainshock. The results are presented as a series of Voronoi polygons centered on known fire stations in the region. This vector .SHP dataset was developed and intended for use in GIS applications...
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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 peak ground acceleration with a 10 percent probability of exceedance in 50 years.
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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 horizontal spectral response acceleration for 0.2-second period with a 50 percent probability of exceedance in 50 years.
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These data are a geospatial representation of potential moderate or high ground shaking intensity for seven M5 or greater aftershocks resulting from the HayWired earthquake scenario, a magnitude 7.0 earthquake occurring on the Hayward Fault on April 18, 2018, with an epicenter in the city of Oakland, CA. These data take existing ground shaking data for the HayWired mainshock and seven aftershocks (M6.21 Palo Alto, M5.69 Palo Alto, M5.22 Palo Alto, M5.26 Palo Alto, M5.98 Mountain View, M6.40 Cupertino, and M5.35 Sunnyvale) and combine them into a single ground shaking intensity surface intended for estimating possible repeat exposure to moderate or high intensity ground shaking. This vector .SHP dataset was developed...
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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...
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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...
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...


map background search result map search result map BackscatterB [EM300]--Offshore Aptos, California Peak ground acceleration with a 10% probability of exceedance in 50 years 0.2-second spectral response acceleration (5% of critical damping) with a 50% probability of exceedance in 50 years Unvegetated to vegetated marsh ratio in Fire Island National Seashore and Central Great South Bay salt marsh complex, New York Moderate or high intensity ground shaking resulting from the HayWired scenario earthquake mainshock (April 18, 2018) and seven M5 or greater aftershocks (May 28, 2018 to October 1, 2018) in the San Francisco Bay area, California. Fire following the Mw 7.0 HayWired earthquake scenario 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 ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD & VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parramore 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: Parramore Island, VA, 2014 DisOcean: Distance to the ocean: Smith Island, VA, 2014 DisOcean: Distance to the ocean: Wreck Island, VA, 2014 Mean high water (MHW) shorelines along the coast of California used to calculated shoreline change from 1998 to 2016 Digital Shoreline Analysis System (DSAS) version 5.0 transects with shoreline rate change calculations at Barter Island Alaska, 1947 to 2020 NSHM23_FSD_v2 Ship navigation tracklines from a 2018 multibeam survey near Noyes Submarine Canyon, southeast Alaska DisOcean: Distance to the ocean: Wreck Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014 DisOcean: Distance to the ocean: Smith Island, VA, 2014 Development: Development delineation: Parker River, MA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman 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: Parramore 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: Monomoy Island, MA, 2013-2014 BackscatterB [EM300]--Offshore Aptos, California Ship navigation tracklines from a 2018 multibeam survey near Noyes Submarine Canyon, southeast Alaska Fire following the Mw 7.0 HayWired earthquake scenario Moderate or high intensity ground shaking resulting from the HayWired scenario earthquake mainshock (April 18, 2018) and seven M5 or greater aftershocks (May 28, 2018 to October 1, 2018) in the San Francisco Bay area, California. Mean high water (MHW) shorelines along the coast of California used to calculated shoreline change from 1998 to 2016 NSHM23_FSD_v2 0.2-second spectral response acceleration (5% of critical damping) with a 50% probability of exceedance in 50 years Peak ground acceleration with a 10% probability of exceedance in 50 years