<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20231109</CreaDate>
<CreaTime>12440600</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="TRUE">nlcd_2006_impervious_l48_202</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
<nativeExtBox>
<westBL Sync="TRUE">646192.882482</westBL>
<eastBL Sync="TRUE">973569.454375</eastBL>
<southBL Sync="TRUE">1665757.725203</southBL>
<northBL Sync="TRUE">2139333.101085</northBL>
<exTypeCode Sync="TRUE">1</exTypeCode>
</nativeExtBox>
<itemLocation>
<linkage Sync="TRUE">file://\\2TK9490CK1\C$\Users\mevans\OneDrive - State of Indiana\Documents\ArcGIS\Projects\IndianaMap Publishing\IndianaMap Publishing.gdb</linkage>
<protocol Sync="TRUE">Local Area Network</protocol>
</itemLocation>
</itemProps>
<coordRef>
<type Sync="TRUE">Projected</type>
<geogcsn Sync="TRUE">GCS_WGS_1984</geogcsn>
<csUnits Sync="TRUE">Linear Unit: Meter (1.000000)</csUnits>
<projcsn Sync="TRUE">Albers_Conical_Equal_Area</projcsn>
<peXml Sync="TRUE">&lt;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/2.9.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;Albers_Conical_Equal_Area&amp;quot;,GEOGCS[&amp;quot;GCS_WGS_1984&amp;quot;,DATUM[&amp;quot;D_WGS_1984&amp;quot;,SPHEROID[&amp;quot;WGS_1984&amp;quot;,6378137.0,298.257223563]],PRIMEM[&amp;quot;Greenwich&amp;quot;,0.0],UNIT[&amp;quot;Degree&amp;quot;,0.0174532925199433]],PROJECTION[&amp;quot;Albers&amp;quot;],PARAMETER[&amp;quot;false_easting&amp;quot;,0.0],PARAMETER[&amp;quot;false_northing&amp;quot;,0.0],PARAMETER[&amp;quot;central_meridian&amp;quot;,-96.0],PARAMETER[&amp;quot;standard_parallel_1&amp;quot;,29.5],PARAMETER[&amp;quot;standard_parallel_2&amp;quot;,45.5],PARAMETER[&amp;quot;latitude_of_origin&amp;quot;,23.0],UNIT[&amp;quot;Meter&amp;quot;,1.0]]&lt;/WKT&gt;&lt;XOrigin&gt;-16901100&lt;/XOrigin&gt;&lt;YOrigin&gt;-6972200&lt;/YOrigin&gt;&lt;XYScale&gt;266467840.99085236&lt;/XYScale&gt;&lt;ZOrigin&gt;-100000&lt;/ZOrigin&gt;&lt;ZScale&gt;10000&lt;/ZScale&gt;&lt;MOrigin&gt;-100000&lt;/MOrigin&gt;&lt;MScale&gt;10000&lt;/MScale&gt;&lt;XYTolerance&gt;0.001&lt;/XYTolerance&gt;&lt;ZTolerance&gt;0.001&lt;/ZTolerance&gt;&lt;MTolerance&gt;0.001&lt;/MTolerance&gt;&lt;HighPrecision&gt;true&lt;/HighPrecision&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
</coordRef>
<lineage>
<Process Date="20231109" Time="124409" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\Clip">Clip nlcd_2006_impervious_l48_20210604.img "646192.882482398 1665757.72520337 973569.454375453 2139333.10108452" "C:\Users\mevans\OneDrive - State of Indiana\Documents\ArcGIS\Projects\IndianaMap Publishing\IndianaMap Publishing.gdb\nlcd_2006_impervious_l48_202" https://gisdata.in.gov/server/rest/services/Hosted/Indiana_Boundary_USCB_2020/FeatureServer/0 255 ClippingGeometry MAINTAIN_EXTENT</Process>
</lineage>
</DataProperties>
<SyncDate>20231109</SyncDate>
<SyncTime>12440700</SyncTime>
<ModDate>20231109</ModDate>
<ModTime>12440700</ModTime>
</Esri>
<dataIdInfo>
<envirDesc Sync="TRUE">Microsoft Windows 10 Version 10.0 (Build 19045) ; Esri ArcGIS 12.9.10.32739</envirDesc>
<dataLang>
<languageCode Sync="TRUE" value="eng"/>
<countryCode Sync="TRUE" value="USA"/>
</dataLang>
<idCitation>
<resTitle Sync="TRUE">NLCD Impervious Surfaces 2006</resTitle>
<presForm>
<PresFormCd Sync="TRUE" value="011"/>
</presForm>
</idCitation>
<spatRpType>
<SpatRepTypCd Sync="TRUE" value="002"/>
</spatRpType>
<dataExt>
<geoEle>
<GeoBndBox esriExtentType="search">
<exTypeCode Sync="TRUE">1</exTypeCode>
<westBL Sync="TRUE">-88.583357</westBL>
<eastBL Sync="TRUE">-84.183721</eastBL>
<northBL Sync="TRUE">42.014875</northBL>
<southBL Sync="TRUE">37.516205</southBL>
</GeoBndBox>
</geoEle>
</dataExt>
<idAbs/>
<searchKeys>
<keyword>Land Cover</keyword>
<keyword>Impervious Surfaces</keyword>
<keyword>Impervious Surface Coverage</keyword>
</searchKeys>
<idPurp>This dataset is a 30m x 30m cell size raster representing the percentage of impervious surface per cell in 2006. This data was downloaded from the MRLC on 11/9/2023.</idPurp>
<idCredit/>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<mdLang>
<languageCode Sync="TRUE" value="eng"/>
<countryCode Sync="TRUE" value="USA"/>
</mdLang>
<distInfo>
<distFormat>
<formatName Sync="TRUE">File Geodatabase Raster Dataset</formatName>
</distFormat>
</distInfo>
<mdHrLv>
<ScopeCd Sync="TRUE" value="005"/>
</mdHrLv>
<mdHrLvName Sync="TRUE">dataset</mdHrLvName>
<refSysInfo>
<RefSystem>
<refSysID>
<identCode Sync="TRUE" code="0"/>
</refSysID>
</RefSystem>
</refSysInfo>
<spdoinfo>
<rastinfo>
<rasttype Sync="TRUE">Pixel</rasttype>
<rowcount Sync="TRUE">15786</rowcount>
<colcount Sync="TRUE">10913</colcount>
<rastxsz Sync="TRUE">29.998770</rastxsz>
<rastysz Sync="TRUE">29.999707</rastysz>
<rastbpp Sync="TRUE">8</rastbpp>
<vrtcount Sync="TRUE">1</vrtcount>
<rastorig Sync="TRUE">Upper Left</rastorig>
<rastcmap Sync="TRUE">TRUE</rastcmap>
<rastcomp Sync="TRUE">LZ77</rastcomp>
<rastband Sync="TRUE">1</rastband>
<rastdtyp Sync="TRUE">pixel codes</rastdtyp>
<rastifor Sync="TRUE">FGDBR</rastifor>
<rastplyr Sync="TRUE">TRUE</rastplyr>
</rastinfo>
</spdoinfo>
<spref>
<horizsys>
<planar>
<planci>
<plance Sync="TRUE">row and column</plance>
<coordrep>
<absres Sync="TRUE">29.998770</absres>
<ordres Sync="TRUE">29.999707</ordres>
</coordrep>
</planci>
</planar>
</horizsys>
</spref>
<eainfo>
<detailed Name="VAT_nlcd_2006_impervious_l48_202">
<enttyp>
<enttypl Sync="TRUE">VAT_nlcd_2006_impervious_l48_202</enttypl>
<enttypt Sync="TRUE">Table</enttypt>
<enttypc Sync="TRUE">101</enttypc>
</enttyp>
<attr>
<attrlabl Sync="TRUE">OBJECTID</attrlabl>
<attalias Sync="TRUE">OBJECTID</attalias>
<attrtype Sync="TRUE">OID</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdef Sync="TRUE">Internal feature number.</attrdef>
<attrdefs Sync="TRUE">Esri</attrdefs>
<attrdomv>
<udom Sync="TRUE">Sequential unique whole numbers that are automatically generated.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl Sync="TRUE">Value</attrlabl>
<attalias Sync="TRUE">Value</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Count</attrlabl>
<attalias Sync="TRUE">Count</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Red</attrlabl>
<attalias Sync="TRUE">Red</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Green</attrlabl>
<attalias Sync="TRUE">Green</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Blue</attrlabl>
<attalias Sync="TRUE">Blue</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Opacity</attrlabl>
<attalias Sync="TRUE">Opacity</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
</detailed>
</eainfo>
<mdDateSt Sync="TRUE">20231109</mdDateSt>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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=</Data>
</Thumbnail>
</Binary>
</metadata>
