20170516
15530500
1.0
FALSE
Prism_Precipitation_01.img
002
-2951222.321755
3001441.354457
114449.407370
3324622.527539
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/10.3'><WKT>PROJCS["NAD_1983_Albers",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Albers"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-96.0],PARAMETER["Standard_Parallel_1",29.5],PARAMETER["Standard_Parallel_2",45.5],PARAMETER["Latitude_Of_Origin",23.0],UNIT["Meter",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
RLE
1
IMAGINE Image
TRUE
continuous
floating point
-3.4028231e+038
20170516
15531100
20170516
15531100
Version 6.2 (Build 9200) ; Esri ArcGIS 10.3.0.4322
Prism_Precipitation_01.img
1
-135.936937
-55.462423
53.013207
19.905675
30-year (1981-2010) monthly/quarterly/annual average precipitation data created by the PRISM Climate Group, collected for USDA-NRCS National Water and Climate Center by Geography, Portland State University
PRISM
Precipitation
BAGIS
30-year (1981-2010) monthly/quarterly/annual average precipitation data created by the PRISM Climate Group, collected for USDA-NRCS National Water and Climate Center by Geography, Portland State University
Geography, Portland State University
Public for BAGIS Users
Raster Dataset
dataset
2
1
0
-2951222.321755 114449.407370
-2951222.321755 3324622.527539
3001441.354457 3324622.527539
3001441.354457 114449.407370
25109.516351 1719535.967455
6364
935.365128
3432
935.365128
Layer_1
40.981106
0.114173
32
20170516
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