<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20171018</CreaDate>
<CreaTime>09054800</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<ArcGISstyle>FGDC CSDGM Metadata</ArcGISstyle>
<SyncOnce>TRUE</SyncOnce>
<DataProperties>
</DataProperties>
</Esri>
<dataIdInfo>
<idAbs>This land classification layer was derived from 2013 National Agricultural Imagery Program (NAIP) images. It classifies land within all municipal boundaries and Census-defined urban areas into one of five categories: tree/shrub, grass/herbaceous, impervious surface, water or wetland. The original process classified land into three types, but then water and wetland areas were masked out using polygons provided by the DNR. Pixel size is 1-meter.</idAbs>
<searchKeys>
<keyword>forest</keyword>
<keyword>urban forest</keyword>
<keyword>forestry</keyword>
<keyword>urban forestry</keyword>
<keyword>land cover</keyword>
<keyword>tree canopy</keyword>
<keyword>urban tree canopy</keyword>
<keyword>land classification</keyword>
</searchKeys>
<idPurp>Land classification raster for all municipal and urban areas in Wisconsin.</idPurp>
<idCredit>University of Wisconsin – Madison; Wisconsin Department of Natural Resources</idCredit>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
<idCitation>
<resTitle>FR_Community_Tree_Canopy</resTitle>
</idCitation>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">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</Data>
</Thumbnail>
</Binary>
</metadata>
