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These raster data represent the results of a case study in Arizona on how vertebrate richness metrics can be used with existing state and federal guidance in wind and solar energy facility siting. Each of the four geodatabases (see Cross References) contain eight native terrestrial wildlife group models in Arizona: 1) all vertebrates, 2) amphibians, 3) reptiles, 4) birds, 5) mammals, 6) bats, 7) raptors and 8) long-distant migratory birds. An XML workbook is included that lists all terrestrial native vertebrate species in Arizona which cross-walks these species to the name of the National Gap Analysis Project species distribution model.
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This data set includes the relative production scenarios for eight (8) grass species based on linear models from Epstein, et al. (1998). We selected two indicator species for each community: shortgrass prairie: blue grama (Bouteloua gracilis; BOGR) and buffalo grass (Bouteloua dactyloides; BODA); mixedgrass prairie: sideoats grama (Bouteloua curtipendula; BOCU) and little bluestem (Schizachyrium scoparium; SCSC); tallgrass prairie: big bluestem (Andropogon gerardii; ANGE) and Indiangrass (Sorghastrum nutans; SONU); and semiarid grasslands: black grama (Bouteloua eriopoda; BOER) and tobosagrass (Pleuraphis mutica; PLMU). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided...
This data set includes the relative production scenarios for bufflaograss [0.72(Temp) - 0.12(Precip) - 0.04(Sand) + 3.08]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier...
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This data set provides industrial-scale onshore wind turbine locations, corresponding facility information, and turbine technical specifications, in the United States to March 2014. The database has nearly 49,000 wind turbine records that have been collected, digitized, locationally verified, and internally quality assured and quality controlled. Turbines from the Federal Aviation Administration Digital Obstacle File, product date March 2, 2014, were used as the primary source of turbine data points. Verification of the position of turbines was done by visual interpretation using high-resolution aerial imagery in ESRI ArcGIS Desktop. Turbines without Federal Aviation Administration Obstacle Repository System (FAA...
Categories: Data; Types: ArcGIS REST Map Service, Citation, Map Service; Tags: Alabama, Alaska, Arizona, Arkansas, California, All tags...
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The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for the People's Republic of China. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral...
Tags: Asia, China, Economic Geology, Energy Resources, Fujian Province, All tags...
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This data provides locations and technical specifications of legacy and current versions of the United States Wind Turbines database. Almost all of which are utility-scale. Utility-scale turbines are ones that generate power and feed it into the grid, supplying a utility with energy. They are usually much larger than turbines that would feed a homeowner or business. Each release, typically done quarterly, updates the database with newly installed wind turbines, removes wind turbines that have been identified as dismantled, and applies other verifications based on updated imagery and ongoing quality-control. Turbine data were gathered from the Federal Aviation Administration's (FAA) Digital Obstacle File (DOF)...
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This data release contains spatial data on the location, number, size and extent of energy-related surface disturbances on the Colorado Plateau of Utah, Colorado, and New Mexico as of 2016. The database includes: 1) polygons of oil and gas pads generated from automated and manual classification of aerial imagery, and 2) polylines of roads derived from the U.S. Census Bureau TIGER/Line Shapefile, supplemented with additional oil and gas access roads digitized from aerial imagery. Pad polygons and road segments are attributed with a "spud year" date based on spud information from the nearest well point. Spudding is the process of beginning to drill a well in the oil and gas industry, and the spud year is a close approximation...
This data set includes the relative production scenarios for sideoats grama [1.13(Temp) + 0.41(Precip) - 0.004(Precip)^2- 0.07(Sand) - 12.3]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et...
This data set includes the relative production scenarios for little bluestem [0.26(Precip) - 4.04]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier scenario (ACCESS...
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The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for 10 countries of interest in Southwest Asia (area of study): Afghanistan, Cambodia, Laos, India, Indonesia, Iran, Nepal, North Korea, Pakistan, and Thailand. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains...
Tags: Afghanistan, Asia, Cambodia, Economic Geology, Energy Resources, All tags...
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This archive documents five 30-year SUTRA simulations summarized in Burns at al. (2020), and provides output from one short (2-year) simulation to allow verification that the archive model code runs properly. A modified version of SUTRA 2.2 was used to evaluate Reservoir Thermal Energy Storage by simulating layered system conditions (grid spacing varies depending on simulation run time to prevent boundary effects). This version of SUTRA is summarized in Burns et al. (2015), but in short, the primary differences from the current public-release version (v3) are that cell-by-cell thermal and hydraulic properties can be defined (allowing representation of the layered Portland system) and viscosity and density of water...
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We created a probabilistic classification model using the nonparametric machine learning technique 'Random Forests' for oil and gas development potential from low (0) to high (1) across the western US. The six predictor variables used in the model were: geophysical data showing aeromagnetic, isostatic gravity, and Bouguer gravity anomalies, geology, topography and bedrock depth. Our binary response variable was geospatial point data on producing and non-producing oil and gas wells. Our estimates provide insights into the trajectory and eventual endpoint of oil and gas development, but the rate and exact location of development will be subject to additional factors not considered such as market demand, the capacity...
This data provides locations and technical specifications of the current version of the United States Wind Turbines database. Each release, typically done quarterly, updates the database with newly installed wind turbines, removes wind turbines that have been identified as dismantled, and applies other verifications based on updated imagery and ongoing quality-control. Turbine data were gathered from the Federal Aviation Administration's (FAA) Digital Obstacle File (DOF) and Obstruction Evaluation Airport Airspace Analysis (OE-AAA), the American Clean Power Association (ACP), Lawrence Berkeley National Laboratory (LBNL), and the United States Geological Survey (USGS), and were merged and collapsed into a single...
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This study took place in the Santa Barbara channel region of southern California, USA. The Santa Barbara channel is a well-known biogeographic transition zone and nearshore rocky reefs and kelp forests are home to many important commercial and recreationally fished species. In particular, rockfishes (genus Sebastes) are long-lived, piscivorous reef fishes that are important predators and are both commercially and recreationally fished. Kelp bass (Paralabrax clathratus), another important fish predator makes up a major sport fishery in southern CA. Finally, CA sheephead (Semicossyphus pulcher) are predators on grazing urchins and have been shown to exert top down control on kelp forests in the area (Hamilton and...
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This data set provides industrial-scale onshore wind turbine locations in the United States through July 22, 2013, corresponding facility information, and turbine technical specifications. The database has more than 47,000 wind turbine records that have been collected, digitized, locationally verified, and internally quality controlled. Turbines from the Federal Aviation Administration Digital Obstacle File, through product release date July 22, 2013, were used as the primary source of turbine data points. Verification of the turbine positions was done by visual interpretation using high-resolution aerial imagery in ESRI ArcGIS Desktop. Turbines without Federal Aviation Administration Obstacle Repository System...
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These data were compiled to predict hourly Glen Canyon Dam operations and hydropower impacts. The objective of our study was to estimate hydropower impacts under different future LTEMP sEIS alternatives. These data represent hourly outflow in cubic feet per second, generation in megawatt hours, and economic value of hydropower in nominal dollars. These data were created for operations at Glen Canyon Dam for October 2023 through November 2027. These data were created by the U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring and Research Cetner using mathematical modeling methods.
This data set includes the relative production scenarios for blue grama [4.15(Temp) -0.3(Precip) - 0.15(Temp)^2 + 0.08]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier...
This data set includes the relative production scenarios for black grama [0.37(Temp) - 0.06(Precip) + 0.24]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier scenario...
This data set includes the relative production scenarios for tobosagrass [0.08(Temp) - 0.58]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier scenario (ACCESS...
This data set includes the relative production scenarios for Indiangrass [0.17(Precip) + 0.02(Sand) - 7.4]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier scenario...
map background search result map search result map Onshore Industrial Wind Turbine Locations for the United States to March 2014 Web services Santa Barbara Channel Geohab Landscape-scale wildlife species richness metrics Potential productivity and change estimates for eight grassland species to evaluate vulnerability to climate change in the southern Great Plains SUTRA model used to evaluate Saline or Brackish Aquifers as Reservoirs for Thermal Energy Storage in the Portland Basin, Oregon, USA Oil and gas development potential in the US Intermountain West United States Wind Turbine Database - Current Version (ver. 6.1, November 2023) Compilation of Geospatial Data (GIS) for the Mineral Industries and Related Infrastructure of Select Countries in Southwest Asia Spatial data of oil and gas pads and access roads on the Colorado Plateau, Utah, Colorado, and New Mexico Compilation of Geospatial Data (GIS) for the Mineral Industries and Related Infrastructure of the People's Republic of China Predicted hydropower impacts of different management scenarios for Lake Powell releases Predicted hydropower impacts of different management scenarios for Lake Powell releases Landscape-scale wildlife species richness metrics Spatial data of oil and gas pads and access roads on the Colorado Plateau, Utah, Colorado, and New Mexico Potential productivity and change estimates for eight grassland species to evaluate vulnerability to climate change in the southern Great Plains Oil and gas development potential in the US Intermountain West Compilation of Geospatial Data (GIS) for the Mineral Industries and Related Infrastructure of the People's Republic of China Onshore Industrial Wind Turbine Locations for the United States to March 2014 Compilation of Geospatial Data (GIS) for the Mineral Industries and Related Infrastructure of Select Countries in Southwest Asia United States Wind Turbine Database - Current Version (ver. 6.1, November 2023)