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Sandy ocean beaches in the United States are popular tourist and recreational destinations and constitute some of the most valuable real estate in the country. The boundary between land and water along the coastline is often the location of concentrated residential and commercial development and is frequently exposed to a range of natural hazards, which include flooding, storm effects, and coastal erosion. In response, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change hazards. One component of this research effort, the National Assessment of Shoreline Change Project, documents changes in shoreline position as a proxy for coastal change. Shoreline position is an easily understood...
Categories: Data; Types: Citation, Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Bald Point State Park, CMGP, Coastal and Marine Geology Program, DSAS, Digital Shoreline Analysis System, All tags...
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wy_lvl7_coarsescale: Wyoming hierarchical cluster level 7 (coarse-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
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This dataset represents an update to U.S. Geological Survey Data Series 597. Locations and attributes of wind turbines in Colorado, 2009 (available at http://pubs.usgs.gov/ds/597/). This updated Colorado wind turbine Data Series provides geospatial data (fig. 1) for all 1,204 wind turbines established within the State of Colorado as of September 2011, an increase of 297 wind turbines from 2009.Attributes specific to each turbine include: turbine location, manufacturer and model, rotor diameter, hub height, rotor height, potential megawatt output, land ownership, county, and development status of the wind turbine. Wind energy facility data for each turbine include: facility name, facility power capacity, number of...
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Sandy ocean beaches in the United States are popular tourist and recreational destinations and constitute some of the most valuable real estate in the country. The boundary between land and water along the coastline is often the location of concentrated residential and commercial development and is frequently exposed to a range of natural hazards, which include flooding, storm effects, and coastal erosion. In response, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change hazards. One component of this research effort, the National Assessment of Shoreline Change Project, documents changes in shoreline position as a proxy for coastal change. Shoreline position is an easily understood...
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Sandy ocean beaches in the United States are popular tourist and recreational destinations and constitute some of the most valuable real estate in the country. The boundary between land and water along the coastline is often the location of concentrated residential and commercial development and is frequently exposed to a range of natural hazards, which include flooding, storm effects, and coastal erosion. In response, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change hazards. One component of this research effort, the National Assessment of Shoreline Change Project (http://coastal.er.usgs.gov/shoreline-change/), documents changes in shoreline position as a proxy for coastal...
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New active-source shallow seismic (shear-wave and acoustic-wave) measurements were obtained at 18 prioritized seismic monitoring station locations in the north San Francisco Bay area to measure site-specific ground motion amplification effects, soil depth, depth to bedrock (Z1.0 Vs=1 km/s), calculate site specific velocity-depth profiles and Vs30, and develop NEHRP site classifications for each location. This study was led by Principal Investigators Jamey Turner, Cooper Brossy, and Daniel O’Connell and field data were acquired by Glendon Adams and Lincoln Steele. Seismic monitoring sites that recorded high PGA values during the M6.0 Napa earthquake, proximal to higher population densities, and sites recommended...
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Sandy ocean beaches in the United States are popular tourist and recreational destinations and constitute some of the most valuable real estate in the country. The boundary between land and water along the coastline is often the location of concentrated residential and commercial development and is frequently exposed to a range of natural hazards, which include flooding, storm effects, and coastal erosion. In response, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change hazards. One component of this research effort, the National Assessment of Shoreline Change Project, documents changes in shoreline position as a proxy for coastal change. Shoreline position is an easily understood...
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wy_lvl2_finescale: Wyoming hierarchical cluster level 2 (fine-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
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The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color aerial orthoimagery and 2007 topographic lidar datasets obtained from the National Oceanic and Atmospheric Administration's Ocean Service, Coastal Services Center. This 2018 data release includes rates that incorporate...
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The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color aerial orthoimagery and 2007 topographic lidar datasets obtained from the National Oceanic and Atmospheric Administration's Ocean Service, Coastal Services Center. This 2018 data release includes rates that incorporate...
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The NABat sampling frame is a grid-based finite-area frame spanning Canada, the United States, and Mexico consisting of N total number of 10- by 10-km (100-km2) grid cell sample units for the continental United States, Canada, and Alaska and 5- by 5-km (25km2) for Hawaii and Puerto Rico. This grain size is biologically appropriate given the scale of movement of most bat species, which routinely travel many kilometers each night between roosts and foraging areas and along foraging routes. A Generalized Random-Tessellation Stratified (GRTS) Survey Design draw was added to the sample units from the raw sampling grids (https://doi.org/10.5066/P9M00P17). This dataset represents the final 2018 NABat Sampling grid with...
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This data release contains the boundaries of assessment units and input data for the assessment of undiscovered gas hydrate resources on the north slope of Alaska. The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown herein as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Assessment Unit, Continuous Assessment Unit, Earth Science, Economic geology, Energy Resources, 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 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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This data release contains the boundaries of assessment of undiscovered continuous tight-gas resources in the Mesaverde Group and Wasatch Formation, Uinta-Piceance Province, Utah and Colorado. The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown herein as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total...


map background search result map search result map Wind Turbines in Colorado, 2011 Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Louisiana Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Louisiana Shorelines of the Florida north (FLnorth) coastal region used in shoreline change analysis Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for central North Carolina (NCcentral) Attributed North American Bat Monitoring Program (NABat) Master Sample and Grid-Based Sampling Frame: Mexico Intersects for Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Intersects for the Buzzards Bay coastal region in Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 2 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 7 (Wyoming), Interim USGS National and Global Oil and Gas Assessment Project-Northern Alaska Province, Gas Hydrate Assessment Unit Boundaries and Assessment Input Data Forms USGS National and Global Oil and Gas Assessment Project - Piceance and Uinta Basins, Mesaverde Group Tight Gas Assessment Unit Boundaries and Assessment Input Data Forms 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 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 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 Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for central North Carolina (NCcentral) Development: Development delineation: Cape Lookout, NC, 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 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 Intersects for the Buzzards Bay coastal region in Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 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: Cape Lookout, NC, 2014 Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Louisiana Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Louisiana Shorelines of the Florida north (FLnorth) coastal region used in shoreline change analysis USGS National and Global Oil and Gas Assessment Project - Piceance and Uinta Basins, Mesaverde Group Tight Gas Assessment Unit Boundaries and Assessment Input Data Forms Wind Turbines in Colorado, 2011 Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 2 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 7 (Wyoming), Interim USGS National and Global Oil and Gas Assessment Project-Northern Alaska Province, Gas Hydrate Assessment Unit Boundaries and Assessment Input Data Forms Attributed North American Bat Monitoring Program (NABat) Master Sample and Grid-Based Sampling Frame: Mexico