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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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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 transgressive contours of the Punta Gorda to Point Arena, California, region. The vector data file is included in the "TransgressiveContours_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...
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This digital elevation model provides a tool for calibrating tsunami risk to observations of the 1945 Makran tsunami in Karachi Harbour. The DEM bathymetry is derived from soundings made mainly during the first eight years after the tsunami. Although deficient in portraying intertidal backwaters and upland topography, the DEM accurately depicts the sheltered setting of one of the two tide gauges that recorded the 1945 tsunami.
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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...
This data release documents proposed updates to geologic inputs (faults) for the upcoming 2023 National Seismic Hazard Model (NSHM). This version (1.0) conveys differences between 2014 NSHM fault sources and those recently released in the earthquake geology inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0 data release by Hatem et al. (2021). A notable difference between the 2014 and 2023 datasets is that slip rates are provided at points for 2023 instead of generalized along the entire fault section length as in 2014; consequently, slip rates are not provided for fault sections in the draft 2023 dataset. Geospatial data (shapefile, kml and geojson) are provided in this data release with...
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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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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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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.
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Bathymetric change grids covering the periods of time from 1992 to 1998 and from 1994 to 2004 are presented. The grids cover a portion of the Sacramento River near Rio Vista, California, extending partially upstream on Cache and Steamboat sloughs by the Ryer Island Ferry, as well as continuing up the Sacramento River towards Isleton. 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. Army Corps of Engineers, California Department of Water Resources, and NOAA�s National Ocean Service.
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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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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.


map background search result map search result map 0.2-second spectral response acceleration (5% of critical damping) with a 50% probability of exceedance in 50 years Bathymetric and topographic grid intended for simulations of the 1945 Makran tsunami in Karachi Harbour Bathymetric change analyses of the southernmost portion of the Mokelumne River, California, from 1934 to 2018 Bathymetric change analyses of the Sacramento River near Rio Vista, California, and the junction of Cache and Steamboat sloughs, from 1992 to 2004 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 Transgressive Contours--Punta Gorda to Point Arena, California 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 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: 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: Smith Island, VA, 2014 DisOcean: Distance to the ocean: Wreck Island, VA, 2014 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) Summary of proposed changes to geologic inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0 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 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Myrtle Island, VA, 2014 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 Bathymetric change analyses of the Sacramento River near Rio Vista, California, and the junction of Cache and Steamboat sloughs, from 1992 to 2004 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Smith Island, VA, 2014 Bathymetric and topographic grid intended for simulations of the 1945 Makran tsunami in Karachi Harbour 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 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) 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 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Lookout, NC, 2014 Transgressive Contours--Punta Gorda to Point Arena, California Summary of proposed changes to geologic inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0 0.2-second spectral response acceleration (5% of critical damping) with a 50% probability of exceedance in 50 years