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(Hyperlink to Official Landing Page for Geospatial Fabric products) The Geospatial Fabric provides a consistent, documented, and topologically connected set of spatial features that create an abstracted stream/basin network of features useful for hydrologic modeling.The GIS vector features contained in this Geospatial Fabric (GF) data set cover the lower 48 U.S. states, Hawaii, and Puerto Rico. Four GIS feature classes are provided for each Region: 1) the Region outline ("one"), 2) Points of Interest ("POIs"), 3) a routing network ("nsegment"), and 4) Hydrologic Response Units ("nhru"). A graphic showing the boundaries for all Regions is provided at http://dx.doi.org/doi:10.5066/F7542KMD. These Regions are identical...
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This dataset describes irrigation water use in Kansas in 2015. Volumes of water used, irrigated area, and average irrigation application depths are provided for three sets of subareas: (1) Irrigation water use analysis regions that include Groundwater Management Districts (GMDs) with the areas outside of GMDs divided into eastern, central, and western Kansas; (2) Regional Planning Areas (RPAs), which are 14 areas determined by the Kansas Water Office based on hydrologic and administrative boundaries, each with a set of goals outlined in the Kansas Water Vision (https://kwo.ks.gov/water-plan/water-vision); and (3) the 105 Kansas counties. Volumes of water used, irrigated area, and average application depths are also...
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Groundwater-quality data collected between 1993 and 2015 were compiled from the U.S. Geological Survey (USGS) National Water Information System (NWIS) database for 722 wells in the San Joaquin Valley (SJV). Groundwater-quality data retrieved included lab analyses of complete major ion data (calcium, magnesium, sodium, potassium, chloride, sulfate, nitrate, alkalinity, bicarbonate, carbonate, silica, and TDS) for 613 samples, and an additional 109 samples with measured values of specific conductance. Most of these wells were sampled as part of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project or the USGS National Water Quality Assessment (NAWQA) Program. In addition...
This research examines the effects of climate change on the species composition of forests in the southern Great Lakes region in USA (Illinois, Indiana, and Ohio) by simultaneously addressing five key components necessary for realistic predictions of future forest composition. We simulated transient (1), species-level (2), forest response to climate change at a spatial scale that accounted for competitive effects (3), and regional site diversity (4), in the spatial configuration of forests within the regional landuse matrix (5). The JABOWA-II forest growth model was used to provide species-specific responses of 45 tree species to site conditions (e.g. climatic, edaphic) while accounting for competition for limited...
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Predictions of raven occurrence in the absence of anthropogenic environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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National-scale geologic, geophysical, and mineral resource raster and vector data covering the United States, Canada, and Australia are provided in this data release. The data were compiled as part of the tri-national Critical Minerals Mapping Initiative (CMMI). The CMMI, established in 2019, is an international science collaboration between the U.S. Geological Survey (USGS), Geoscience Australia (GA), and the Geological Survey of Canada (GSC). One aspect of the CMMI is to use national- to global-scale earth science data to map where critical mineral prospectivity may exist using advanced machine learning approaches (Kelley, 2020). The geoscience information presented in this report include the training and evidential...
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: ARDS, Alaska, Alaska Mineral Resource Data, Australia, Canada, All tags...
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RGB-averaged orthoimages were created from aerial imagery collected on November 26, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RBG-averaged orthoimages were created to document ground conditions two-months after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RBG-averaged orthoimages help researchers estimate the land surface after Hurricane Dorian and were created to document inter-annual changes in shoreline position and coastal morphology in response to storm events using aerial imagery collections and a structure from motion (SFM) workflow. These data can be used with geographic information...
Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Atlantic Ocean, Bathymetry and Elevation, Beaufort Inlet, CMHRP, Cape Hatteras, All tags...
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This U.S. Geological Survey (USGS) metadata release consists of 17 different spatial layers in GeoTIFF format. They are: 1) average water capacity (AWC.zip), 2) percent sand (Sand.zip), 3) percent silt (Silt.zip), 4) percent clay (Clay.zip), 5) soil texture (TEXT_PRMS.zip), 6) land use/land cover (LULC.zip), 7) snow values (Snow.zip), 8) summer rain values (SRain.zip), 9) winter rain values (WRain.zip), 10) leaf presence values (keep.zip), 11) leaf loss values (loss.zip), 12) percent tree canopy (CNPY.zip), 13) percent impervious surface (Imperv.zip), 14) snow depletion curve numbers (Snow.zip), 15) rooting depth (RootDepth.zip), 16) permeability values (Lithology_exp_Konly_Project.zip), and 17) water bodies. All...
Growing concern about climate change and energy security has led to increasing interest in developing renewable, domestic energy sources for meeting electricity, heating and fuel needs in the United States. Illinois has significant potential to produce bioenergy crops, including corn, soybeans, miscanthus (Miscanthus giganteus), and switchgrass (Panicum virgatum). However, land requirements for bioenergy crops place them in competition with more traditional agricultural uses, in particular food production. Additionally, environmental and economic conditions, including soil quality, climate, and variable agricultural costs, vary significantly across Illinois. The intent of this study is to examine the spatial and...
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This U.S. Geological Survey (USGS) Data Release provides derivative statistics of water used by Kansas irrigators in the Kansas irrigation water-use analysis regions. The published application rate statistics from the previous 4 years (2010–13) are shown with the 2014 statistics and are used to calculate a 5-year average. The 2014 annual total precipitation and the current 30-year climatic normal (based on 1981–2010) are also shown by region. The amount of water used, irrigated acres, and application rates are further grouped by crop type. The amount of water used and irrigated acres are further grouped by irrigation method. Total reported irrigation water use in 2014 was 3.3 million acre-feet of water applied to...
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This U.S. Geological Survey (USGS) Data Release represents geospatial and tabular data on irrigation water use in Kansas. The data release was produced in compliance with open data requirements. The dataset consists of 3 separate items with similar attributes aggregated to different geographic extents: 1. Kansas counties; 2. Kansas regional planning areas used in the Kansas Water Plan; and 3. Kansas irrigation water-use analysis regions. Reported 2014 water withdrawn for irrigation, acres irrigated, and application rates along with the published application rate statistics from the previous 4 years (2010–13) are shown with the 2014 statistics and are used to calculate a 5-year average. The 2014 annual total...
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This 50-m-resolution surface presents bathymetric change of South San Francisco Bay, California (hereafter referred to as South Bay). This surface compares a 1-m-resolution digital elevation model (DEM) of the southern portion of San Francisco Bay (Fregoso and others, 2021), comprised of bathymetry data in the South Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 50-m-resolution DEM of South Bay comprised of historic surveys from 1979 to 1985 (referred to as the 1980s because the majority of the surveys were in that decade). The creation of this change surface involved the resampling of the 1-m-resolution 2010s DEM to match the 50-m-resolution...
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A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the southern portion of San Francisco Bay, was constructed from bathymetric surveys collected from 2005 to 2020. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and interferometric side-scan sonar systems. Of those 93 surveys, 75 consist of swaths of data ranging from 18- to just over 100-meters wide. These swaths were separated by data gaps ranging from 10- to just over 300-meters wide. The no-data areas required interpolation to create a continuous surface....
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(Hyperlink to Official Landing Page for Geospatial Fabric products) This dataset contains a set of attributes describing the "nhru" GIS features (Hydrologic Response Units)in the Geospatial Fabric Features dataset(http://dx.doi.org/doi:10.5066/F7542KMD) that have been developed in support of the USGS PRMS watershed model. These tables are organized according to Geospatial Fabric Region; see the thumbnail of the Geospatial Fabric Features Regions (https://www.sciencebase.gov/catalog/item/535edb4ae4b08e65d60fc837). Each table contains a key field, "hru_id", that can be used to relate to the nhru feature class in the Geospatial Fabric Feature dataset for the corresponding Region. The methodologies used to derive the...
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(Hyperlink to Official Landing Page for Geospatial Fabric products) This dataset contains a set of attributes describing the "nhru" GIS features (Hydrologic Response Units)in the Geospatial Fabric Features dataset(http://dx.doi.org/doi:10.5066/F7542KMD) that have been developed in support of the USGS PRMS watershed model. These tables are organized according to Geospatial Fabric Region; see the thumbnail of the Geospatial Fabric Features Regions (https://www.sciencebase.gov/catalog/item/535edb4ae4b08e65d60fc837). Each table contains a key field, "hru_id", that can be used to relate to the nhru feature class in the Geospatial Fabric Feature dataset for the corresponding Region. The methodologies used to derive the...
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Predictions of raven occurrence in the absence of natural environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the northern portion of San Francisco Bay, which includes San Pablo Bay, Carquinez Strait, and portions of Suisun Bay, was constructed from bathymetric surveys collected from 1999 to 2016. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and interferometric side-scan sonar systems. Of those 93 surveys, 75 consist of swaths of data ranging from 18- to just over 100-meters wide. These swaths were separated by data gaps ranging from 10- to just over 300-meters wide....
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Digital elevation models (DEMs) were created from aerial imagery collected between September 08 and September 13, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions post-Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface after Hurricane Dorian and were created to document inter-annual changes in shoreline position and coastal morphology in response to storm events using aerial imagery collections and a structure from motion (SFM) workflow. These data can be used with geographic information systems or...
Tags: Atlantic Ocean, Bathymetry and Elevation, Beaufort Inlet, CMHRP, Cape Hatteras, All tags...


map background search result map search result map GIS Features of the Geospatial Fabric for National Hydrologic Modeling Geospatial Fabric Attribute Tables for PRMS Soils Parameters based on SSURGO (Preliminary) Geospatial Fabric Attribute Tables for PRMS Landcover Parameters based on NLCD2001 (Preliminary) Irrigation water use in Kansas, 2014 Reported 2014 water withdrawn for irrigation, acres irrigated, and application rates in Kansas irrigation water-use analysis regions (spatial and tabular data). Modern groundwater-quality, depth, and well-construction data for selected wells in the San Joaquin Valley, California, 1993-2015 Irrigation water use in Kansas, 2015 Raven study site locations in the Great Basin, derived from survey locations 2007 - 2016 Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Digital elevation model (DEM) of northern San Francisco Bay, California, created using bathymetry data collected between 1999 and 2016 (MLLW) Data Layers for the National Hydrologic Model, version 1.1 Digital elevation model (DEM) of south San Francisco Bay, California, created using bathymetry data collected between 2005 and 2020 (MLLW) National-Scale Geophysical, Geologic, and Mineral Resource Data and Grids for the United States, Canada, and Australia: Data in Support of the Tri-National Critical Minerals Mapping Initiative Digital elevation models (DEMs) of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian RGB-averaged orthoimagery of coastal North Carolina, on 2019-11-26, two-months Post-Hurricane Dorian Bathymetric change of South San Francisco Bay, California: 1979 to 2020 Digital elevation model (DEM) of northern San Francisco Bay, California, created using bathymetry data collected between 1999 and 2016 (MLLW) Digital elevation model (DEM) of south San Francisco Bay, California, created using bathymetry data collected between 2005 and 2020 (MLLW) Bathymetric change of South San Francisco Bay, California: 1979 to 2020 RGB-averaged orthoimagery of coastal North Carolina, on 2019-11-26, two-months Post-Hurricane Dorian Digital elevation models (DEMs) of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian Modern groundwater-quality, depth, and well-construction data for selected wells in the San Joaquin Valley, California, 1993-2015 Irrigation water use in Kansas, 2014 Irrigation water use in Kansas, 2015 Reported 2014 water withdrawn for irrigation, acres irrigated, and application rates in Kansas irrigation water-use analysis regions (spatial and tabular data). Raven study site locations in the Great Basin, derived from survey locations 2007 - 2016 Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Data Layers for the National Hydrologic Model, version 1.1 GIS Features of the Geospatial Fabric for National Hydrologic Modeling Geospatial Fabric Attribute Tables for PRMS Soils Parameters based on SSURGO (Preliminary) Geospatial Fabric Attribute Tables for PRMS Landcover Parameters based on NLCD2001 (Preliminary) National-Scale Geophysical, Geologic, and Mineral Resource Data and Grids for the United States, Canada, and Australia: Data in Support of the Tri-National Critical Minerals Mapping Initiative