Filters: Tags: Sedgwick County (X) > Date Range: {"choice":"year"} (X)
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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global third-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Black Tailed Prairie Dogs,
Colorado,
Great Plains,
Habitat Suitability,
Rangeland and Resources Research Unit,
Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global second-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Black Tailed Prairie Dogs,
Colorado,
Great Plains,
Habitat Suitability,
Rangeland and Resources Research Unit,
Layered geospatial PDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features. This map is derived from GIS (geospatial information system) data. It represents a repackaging of GIS data in traditional map form, not creation of new information. The geospatial data in this map are from selected National Map data holdings and other government sources.
Probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Probability is measured from 0 to 1 with 0 being low habitat suitability and 1 being high suitability. Probability data is created from fitting a global second-order model to county level raster data. For details on model fitting and data used to produce probability raster see report. https://www.fws.gov/science/catalog
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Black Tailed Prairie Dogs,
Colorado,
Great Plains,
Habitat Suitability,
Rangeland and Resources Research Unit,
Probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Probability is measured from 0 to 1 with 0 being low habitat suitability and 1 being high suitability. Probability data is created from fitting a global third-order model to county level raster data. For details on model fitting and data used to produce probability raster see report. https://www.fws.gov/science/catalog
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Black Tailed Prairie Dogs,
Colorado,
Great Plains,
Habitat Suitability,
Rangeland and Resources Research Unit,
Layered geospatial PDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features. This map is derived from GIS (geospatial information system) data. It represents a repackaging of GIS data in traditional map form, not creation of new information. The geospatial data in this map are from selected National Map data holdings and other government sources.
The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the best available National Hydrography Dataset (NHD), the 10-meter 3D Elevation Program Digital Elevation Model (3DEP DEM), and the National Watershed Boundary Dataset (WBD). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to create a stream network with linear referencing, feature naming, "value added attributes" (VAAs), elevation-derived catchments, and other features for hydrologic data analysis. The stream network with linear referencing is a system of data relationships applied to hydrographic systems so that one stream reach "flows" into another and "events" can be tied to and traced...
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