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These data represent 1 sq. mile Hexagons and are derived from the Western Governors Association Crucial Habitat Assessment Tool. The hexagons have been attributed with summary values from the datasets described above. Field names correspond to the number datasets above as follows: {1:’wetland_deds’, 2:’wetland_ceds’, 3:’cropland_ceds’, 4:’lasp_grsp_casp_suit’, 5:’lasp_grsp_suit’, 6:’riparian_suit’, 7:’mean_sat_thick_ft’, 8:’tillage_suit’, 9:’wind_suit’, 10:’ann_aq_deplet_ft’, 11:’wetland_deds_2040’, 12:’wetland_ceds_2040’, 13:’lbgrasslands_2017’, 14:’lbgrasslands_2022’, 15:’lbgrasslands_2027’, 16:’mean_sat_thick_2050_ft’, 17:’tillage_suit_2050’}. Zonal statistic attribution methods are as follows: {1:’SUM’, 2:’SUM’,...
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The Zahle cluster is named for the city of Zahle, Lebanon, but it covers most of the country and includes some offshore events as well. Most events are small and there are few arrival time data beyond ~30° epicentral distance. The distribution of stations is quite good and the calibration analysis is robust. All events have depth constraint. Depths range through most of the crust. Number of events: 69 Calibration type: direct calibration using data to 0.7 degrees; hypocentroid calibration level = 1.0 km Epicentral calibration range: 1 - 3 km Date range: 19950423 - 20180107 Latitude range: ...
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A vented conductivity, temperature and depth sensor (CTD, InSitu Aqua Troll) was installed at site NR1 (N 47° 04’ 16.1”/W 122° 42’ 15.5”) and continuously measured water temperature, water depth, specific conductance, and salinity at 15-minute intervals from February 11, 2016 to July 18, 2016 (159 days). The sensor was replaced with a vented water-level logger (InSitu Level Troll) on July 19, 2016 and deployed until March 19, 2018 (608 days). The site is tidally influenced and located approximately 4.1 km upstream from the mouth of the Nisqually River and within the tidal prism. The elevation (NAVD88) of the top of the deployment pipe was surveyed by RTN-GPS. Tape-down measurements from the top of the pipe to the...
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Shallow subsurface electrical conductivity was mapped at Stateline National Wildlife Refuge (NWR) in northeast Montana using the DUALEM421 electromagnetic sensor (Dualem, Inc., ON, Canada) in the winter of 2017. Data were acquired by towing the DUALEM421 sensor on a sled behind an all-terrain vehicle or snow machine, with the sensor at a nominal height of 0.3 meters (m) above ground surface. Approximately 3 line-kilometers (km) of data were acquired over an area of approximately .2 square-kilometers. Data were manually edited to remove sensor dropouts, lag corrected for apparent offsets between recorded GPS location and data locations for each coil pair, and averaged to a sounding distance of 1m along the survey...
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The Denver fossil algae database were gathered from the inception of Denver Region in 1953 by Richard Rezak. His specialty was algae, carbonate platforms, and off-shore modern reefs. He developed a very useful litho-stratigraphic tool while studying Proterozoic algae and stromatolites in Glacier National Park. This lead to his studies of modern analogs in the Caribbean and South Seas. His catalogs were converted into digital form, Excel and Filemaker Pro database. The Catalog consist of 1001 fossil localities. His supplementary data has been added whenever possible - sources field map locality points, E&R files with enhanced faunal lists, as well as formal publications
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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, CMGP, 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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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...
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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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For the Green River Basin Landscape Conservation Design (GRB LCD) assessment, we mapped the vulnerability of riparian habitat for terrestrial species and process. Using a vulnerability framework, we defined Sensitivity (S) as the percent riparian vegetation within the valley bottom and Exposure (E) as the amount of human modification within the valley bottom. For each 12-digit hydrologic unit code within the GRB LCD we summarized the riparian sensitivity and exposure to human modification. We also computed Potential Impact (PI), and Adaptive Capacity (AC) metrics at the HUC12 level. PI is the square root transformed product of human modification exposure and riparian sensitivity. AC for riparian exposure to human...
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
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This dataset consists of point gravity station data for 95 stations in the middle Carson River basin as published on figure 7 in the U.S. Geological Survey Scientific Investigations Report 2011-5055. The points have values of the complete Bouguer anomaly and observed gravity. In addition, 641 selected gravity stations from the U.S. Geological Survey Data Series 42 titled "Gravity data of Nevada" used in this study are included for reference and users are advised to reference that publication for information on those data. Reference cited Ponce, D.A., 1997, Gravity data of Nevada: U.S. Geological Survey Data Series 42, 27 p., https://doi.org/10.3133/ds42.


map background search result map search result map Water Data for Nisqually River at Site NR1 Vulnerability of Riparian Habitat to Land Uses in the Green River Basin Conservation Parcels Scored - Rio Mora Crucial Habitat Assessment Shapefiles USGS Denver Micro-fossil collection: Fossil Algae Development: Development delineation: Edwin B. Forsythe NWR, NJ, 2010 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 Salmonberry (i.e. Cloudberry) locations 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 Lebanon, Zahle: 1995-2018 Stateline NWR, Montana, 2017 Gravity station data, middle Carson River basin, Nevada (from U.S. Geological Survey Scientific Investigations Report 2011-5055, figure 7) Broken Forest Canopy Identified by Lidar for the Navigational Pool 13 of the Mississippi River Herring River Stateline NWR, Montana, 2017 Shapefiles Development: Development delineation: Cape Lookout, NC, 2014 Herring River 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 Development: Development delineation: Edwin B. Forsythe NWR, NJ, 2010 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 Broken Forest Canopy Identified by Lidar for the Navigational Pool 13 of the Mississippi River 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 Gravity station data, middle Carson River basin, Nevada (from U.S. Geological Survey Scientific Investigations Report 2011-5055, figure 7) Lebanon, Zahle: 1995-2018 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 Salmonberry (i.e. Cloudberry) locations Vulnerability of Riparian Habitat to Land Uses in the Green River Basin Conservation Parcels Scored - Rio Mora Crucial Habitat Assessment USGS Denver Micro-fossil collection: Fossil Algae