20200418 23000800 1.0 FALSE WesternNorthAmerica_DEM_100m.img 002 -5620101.438783 -1.438783 880488.419410 7210788.419410 1 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) NAD_1983_Albers <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.7'><WKT>PROJCS[&quot;NAD_1983_Albers&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Albers&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;central_meridian&quot;,-96.0],PARAMETER[&quot;Standard_Parallel_1&quot;,29.5],PARAMETER[&quot;Standard_Parallel_2&quot;,45.5],PARAMETER[&quot;latitude_of_origin&quot;,23.0],UNIT[&quot;Meter&quot;,1.0]]</WKT><XOrigin>-16901100</XOrigin><YOrigin>-6972200</YOrigin><XYScale>266467840.99085236</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision></ProjectedCoordinateSystem> 32 FALSE None 1 IMAGINE Image TRUE continuous floating point -3.4028235e+38 20200418 23000800 20200418 23000800 Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1.11595 WesternNorthAmerica_DEM_100m.img 1 -180.000000 180.000000 90.000000 16.255514 100 meters DEM for Western US, including Alaska, and Yukon and British Columbia, Canada. The DEM is resampled from 30 meters USGS and ASTER DEM using cubic convolution resampling method. The DEM was collected and compiled for USDA-NRCS National Water and Climate Center by Geography, Portland State University. DEM USGS 100 meters 100 meters DEM for Western US, including Alaska, and Yukon and British Columbia, Canada. The DEM is resampled from 30 meters USGS and ASTER DEM using cubic convolution resampling method. Geography, Portland State University Public for BAGIS Users Raster Dataset dataset 2 1 0 -5620101.438783 880488.419410 -5620101.438783 7210788.419410 -1.438783 7210788.419410 -1.438783 880488.419410 -2810051.438783 4045638.419410 56201 100.000000 63303 100.000000 Layer_1 6410.005371 -282.980896 32 20200418 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