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Sediment samples and samples for water-toxicity testing were collected during 2014 from several streams in San Antonio, Texas known locally as the Westside creeks (Alazán, Apache, Martínez, and San Pedro Creeks) and from the San Antonio River. Samples were collected once during base-flow and again after periods of storm-water runoff (post-storm conditions) to determine baseline sediment- and water-quality conditions. Streambed-sediment samples were analyzed for selected constituents, including trace elements and organic contaminants such as pesticides, polychlorinated biphenyls (PCBs), brominated flame retardants, and polycyclic aromatic hydrocarbons (PAHs).
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A one-year seismic hazard forecast for the Central and Eastern United States, based on induced and natural earthquakes, has been produced by the U.S. Geological Survey. The model assumes that earthquake rates calculated from several different time windows will remain relatively stationary and can be used to forecast earthquake hazard and damage intensity for the year 2016. This assessment is the first step in developing an operational earthquake forecast for the CEUS, and the analysis could be revised with updated seismicity and model parameters. Consensus input models consider alternative earthquake catalog durations, smoothing parameters, maximum magnitudes, and ground motion estimates, and represent uncertainties...
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The data set consists of time, depth, reflection coefficient synthetic, sonic velocity, density, and amplitude used to create synthetic seismogram - City of Hollywood Utility, G-2961, (HOL-IW1), Broward County, Florida.
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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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Located in the northern tropical Pacific Ocean, Majuro is the capital of the Republic of the Marshall Islands. Majuro Atoll consists of a large, narrow landmass and a set of smaller perimeter islands surrounding a lagoon that is over 100 square miles in size. The waters surrounding the Majuro Atoll land areas are relatively shallow with poorly mapped bathymetry. However, the Pacific Ocean on the exterior of the coral atoll and the lagoon within its interior consist of deep bathymetry with steep slopes. The highest elevation of the Majuro Atoll is estimated at only 3-meters above sea level, which is the island community of Laura located on the western part of the atoll. At the eastern edge of the atoll lies the capital...
Categories: Data; Tags: 3D Elevation Program, 3DEP, American Society of Photogrammetry and Remote Sensing, Base Maps, Bathymetric, All tags...
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This USGS Data Release represents geospatial and tabular data for the Denali Sampling Project. This dataset represents the 'Sample Site Locations (Vector GIS dataset)' for the 2015 Sample Data Release. These data support the following publication:Drew A. Ignizio, ScienceBase Team, 2015, SAMPLE Denali Observations from 2010-2015, USGS Open File Report.
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This USGS Data Release represents geospatial and tabular data for the Denali Sampling Project. This dataset represents the 'Sample Transects (Vector GIS dataset)' for the 2015 Sample Data Release. These data support the following publication:Drew A. Ignizio, ScienceBase Team, 2015, SAMPLE Denali Observations from 2010-2015, USGS Open File Report.
We investigated population dynamics in chorus frogs (Pseudacris maculata) relative to extrinsic (air temperatures and snowpack) and intrinsic (density dependence) characteristics at 2 sites in Colorado, USA. We used capture-mark-recapture (cmr) data (i.e., 1 or 0, provided here) and a Bayesian model framework to assess our a priori hypotheses about interactions among covariates and chorus frog survival and population growth rates. Files include: Cameron_Lily_cmr_NOV2020.csv, Cameron_Matthews_cmr_NOV2020.csv, and Cameron_covariates_NOV2020.csv. Data associated with paper by Kissel et al. 2021.
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This metadata record documents 11 comma delimited tables representing the amount of reported best management practice (BMP) implementation for the years from 1985 to 2014 at three geographic scales: county or land-river modeling segment, River Input Monitoring (RIM) station drainage areas, and the entire Chesapeake Bay Watershed (CBWS). Data originated from the Chesapeake Bay Watershed jurisdictions including Maryland, Pennsylvania, Virginia, Delaware, New York, West Virginia, and the District of Columbia. Data were reported to the Chesapeake Bay Program for an annual review of progress toward meeting nitrogen, phosphorus, and sediment reduction goals.
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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...


map background search result map search result map Coal Mines Trout Unlimited-Coldwater Fisheries Data Condition Index - Aquatic - Focal Species Wind Turbines in Colorado, 2011 2015 Sample Transects Modified Mercalli Intensity based on horizontal spectral response acceleration for 1.0-second period, with 1-percent probability of exceedance in 1 year for the Western United States Sediment-quality and water-toxicity data from 10 sites on the Westside Creeks and San Antonio River, San Antonio, Texas, 2014 G-2946 : Synthetic Seismogram Data for Correlation Between Seismic-Reflection Profiles and Well Data, Broward County, Florida G-2961 (HOL-IW1) : Synthetic Seismogram Data for Correlation Between Seismic-Reflection Profiles and Well Data, Broward County, Florida One Meter Topobathymetric Digital Elevation Model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016 1) Best management practice implementation in the Chesapeake Bay watershed from 1985 to 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 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 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Metompkin Island, VA, 2014 Chorus frog density and population growth, Cameron Pass, Colorado, 1986-2020 Chorus frog density and population growth, Cameron Pass, Colorado, 1986-2020 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 Sediment-quality and water-toxicity data from 10 sites on the Westside Creeks and San Antonio River, San Antonio, Texas, 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 One Meter Topobathymetric Digital Elevation Model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016 G-2946 : Synthetic Seismogram Data for Correlation Between Seismic-Reflection Profiles and Well Data, Broward County, Florida G-2961 (HOL-IW1) : Synthetic Seismogram Data for Correlation Between Seismic-Reflection Profiles and Well Data, Broward County, Florida 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 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Lookout, NC, 2014 2015 Sample Transects Wind Turbines in Colorado, 2011 Trout Unlimited-Coldwater Fisheries Data Coal Mines Condition Index - Aquatic - Focal Species 1) Best management practice implementation in the Chesapeake Bay watershed from 1985 to 2014 Modified Mercalli Intensity based on horizontal spectral response acceleration for 1.0-second period, with 1-percent probability of exceedance in 1 year for the Western United States