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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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These data represent simulated soil temperature and moisture conditions for current climate, and for future climate represented by all available climate models at two time periods during the 21st century. These data were used to: 1) quantify the direction and magnitude of expected changes in several measures of soil temperature and soil moisture, including the key variables used to distinguish the regimes used in the R and R categories; 2) assess how these changes will impact the geographic distribution of soil temperature and moisture regimes; and 3) explore the implications for using R and R categories for estimating future ecosystem resilience and resistance.
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The file "Chloride_specific_conductance_regression_model_forms_for_estimating_high-frequency_chloride_concentrations.csv" contains the regression equation forms for two types of regressions: 1) single linear (SLR) and 2) piecewise (or segmented; SEG) regression between specific conductance (SC) and chloride (Cl) concentrations for 56 USGS water-quality monitoring stations across the eastern United States, plus four regional regressions developed by pooling data for sites within a region (see Moore and others (in review) for more information). Some sites, and all regions, have both SLR and SEG models reported in this table. The analysis included in the Moore and others (in review) study used results from the SLR...
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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...
Geographic distribution data were collected based on county level occurrences (or converted from point occurrences to county level occurrences) within the five focal states (Minnesota, North Dakota, South Dakota, Nebraska & Iowa) and each U.S. state or Canadian province bordering those focal states (Wisconsin, Illinois, Missouri, Kansas, Wyoming, & Montana in the USA and Saskatchewan, Ontario & Manitoba in Canada).
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LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant...
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LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types. HDist includes the year of disturbance that is recorded for that pixel. In LF 2022, the time since disturbance code is the same for both HDist...
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LANDFIRE (LF) 2022 Fuel Vegetation Type (FVT) represents the LF Existing Vegetation Type Ecological Systems (EVT) product, modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances...
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Using publicly available data for Albany and Schenectady counties, New York, a series of geospatial overlays were created at 1:24,000 scale to examine the bedrock geology, groundwater table, soils, and surficial geology. Bedrock and surficial geology were refined using extant bedrock maps, well and borehole data from water- and gas-wells, soil data, and lidar data. Groundwater data were collected from New York State Department of Environmental Conservation and U.S. Geological Survey water-well databases to estimate the groundwater table. Soil data were used to examine soil thickness over bedrock and infiltration. An inventory of closed depressions was created using reconditioned lidar-derived bare-earth digital...
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Using publicly available data for Erie and Niagara counties, New York, a series of geospatial overlays were created at 1:24,000 scale to examine the bedrock geology, groundwater table, soils, and surficial geology. Bedrock and surficial geology were refined using extant bedrock maps, well and borehole data from water- and gas-wells, soil data, and lidar data. Groundwater data were collected from New York State Department of Environmental Conservation and U.S. Geological Survey water-well databases to estimate the groundwater table. Soil data were used to examine soil thickness over bedrock and infiltration. An inventory of closed depressions was created using reconditioned lidar-derived bare-earth digital elevation...
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These data represent total vegetation and surface water along approximately 12 kilometers of the Paria River upstream from the confluence of the Colorado River at Lees Ferry, Arizona. They are derived from airborne, multispectral imagery obtained in late May 2009, 2013, and 2021, collected with a push-broom sensor with 4 spectral bands depicting Blue, Green, Red and Near-Infrared wavelengths at a spatial resolution of 20 centimeters. The vegetation classification data were created using a supervised classification algorithm provided by Harris Geospatial in ENVI version 5.6.3 (Exelis Visual Information Solutions, Boulder, Colorado). The water data were created using a Green Normalized Difference Vegetation Index...
Tags: Arizona, Botany, Cloud Optimized GeoTIFF data, Colorado River, Ecology, All tags...
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LANDFIRE's (LF) 2022 Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. CC supplies information for fire behavior models to determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. To create this product, plot level CC values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance CC and Canopy Height (CH) are used as predictors of disturbed CC using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and...
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LANDFIRE (LF) 2022 Fuel Vegetation Cover (FVC) represents the LF Existing Vegetation Cover (EVC) product, modified to represent pre-disturbance EVC in areas where disturbances have occurred over the past 10 years. EVC is mapped as continuous estimates of canopy cover for tree, shrub, and herbaceous lifeforms with a potential range from 10% to 100%. Continuous EVC values are binned to align with fuel model assignments when creating FVC. FVC is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVC is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
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The U.S. Geological Survey (USGS), in cooperation with the Federal Emergency Management Agency, Pennsylvania Department of Environmental Protection, Pennsylvania Department of Transportation, and Susquehanna River Basin Commission, prepared hydro-conditioned geographic information systems (GIS) layers for use in the Pennsylvania StreamStats application. These data were used to update the peak flow and low flow regression equations for Pennsylvania. This dataset consists of flow direction rasters for each 8-digit Hydrologic Unit Code (HUC) area in Pennsylvania, one of the layer types needed to delineate watersheds within the HUC-8 areas, merged into a single dataset. The 59 HUCs represented by this dataset are 02040101,...
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The U.S. Geological Survey (USGS), in cooperation with the Federal Emergency Management Agency, Pennsylvania Department of Environmental Protection, Pennsylvania Department of Transportation, and Susquehanna River Basin Commission, prepared hydro-conditioned geographic information systems (GIS) layers for use in the Pennsylvania StreamStats application. These data were used to update the peak flow and low flow regression equations for Pennsylvania. This dataset consists of stream definition 900 cell threshold rasters for each 8-digit Hydrologic Unit Code (HUC) area in Pennsylvania, one of the layer types needed to delineate watersheds within the HUC-8 areas, merged into a single dataset. The 59 HUCs represented...
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This data release contains the U.S. salient statistics and world production data extracted from the SALT data sheet of the USGS Mineral Commodity Summaries 2022.
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This data release contains the U.S. salient statistics and world production data extracted from the STONE (CRUSHED) data sheet of the USGS Mineral Commodity Summaries 2022.
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This data release contains the U.S. salient statistics and world production data extracted from the WOLLASTONITE data sheet of the USGS Mineral Commodity Summaries 2022.
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This data release contains the U.S. salient statistics and world production data extracted from the PHOSPHATE ROCK data sheet of the USGS Mineral Commodity Summaries 2022.
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This data release contains the U.S. salient statistics and world production data extracted from the SELENIUM data sheet of the USGS Mineral Commodity Summaries 2022.


map background search result map search result map Historical and 21st century soil temperature and moisture data for drylands of western U.S. and Canada USGS National and Global Oil and Gas Assessment Project-Northern Alaska Province, Gas Hydrate Assessment Unit Boundaries and Assessment Input Data Forms Chloride-specific conductance regression model forms for estimating high-frequency chloride concentrations 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 Flow direction raster for Pennsylvania StreamStats Stream definition 900 cell threshold raster for Pennsylvania StreamStats Geospatial datasets to assess karst aquifer systems in Albany and Schenectady counties, New York County-Level Geographic Distributions for 47 Exotic Plant Species in Midwest USA and Central Canada, Compiled 2019 Geospatial datasets to assess karst aquifer systems in Erie and Niagara counties, New York Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA Geospatial datasets to assess karst aquifer systems in Albany and Schenectady counties, New York Geospatial datasets to assess karst aquifer systems in Erie and Niagara counties, New York 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 LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI USGS National and Global Oil and Gas Assessment Project-Northern Alaska Province, Gas Hydrate Assessment Unit Boundaries and Assessment Input Data Forms Flow direction raster for Pennsylvania StreamStats Stream definition 900 cell threshold raster for Pennsylvania StreamStats Chloride-specific conductance regression model forms for estimating high-frequency chloride concentrations Historical and 21st century soil temperature and moisture data for drylands of western U.S. and Canada County-Level Geographic Distributions for 47 Exotic Plant Species in Midwest USA and Central Canada, Compiled 2019 LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS