20150909 23404400 1.0 FALSE evc_cc 002 -2362425.000000 2263815.000000 258945.000000 3177435.000000 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/10.1'><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> 20150910 00365300 20150910 00365300 Esri ArcGIS 10.2.2.3552 evc_cc 1 -127.987753 -65.254445 51.649681 22.765715 BAGIS Tag End Tag 30-meter cover density from Landfire EVC layer. This layer includes cover density for all vegetation types (trees, grass, shrub) 30-meter cover density from Landfire EVC layer. This layer includes cover density for all vegetation types (trees, grass, shrub) Geography, Portland State University Public for BAGIS Users File Geodatabase Raster Dataset dataset Pixel 97283 154208 30.000000 30.000000 8 1 Upper Left FALSE LZ77 1 pixel codes FGDBR TRUE row and column 30.000000 30.000000 20150910 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