<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20220505</CreaDate>
<CreaTime>11222100</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="TRUE">GEO_007_2015_07_Clip</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
<nativeExtBox>
<westBL Sync="TRUE">4477966.842283</westBL>
<eastBL Sync="TRUE">4480094.183967</eastBL>
<southBL Sync="TRUE">4565912.489722</southBL>
<northBL Sync="TRUE">4567682.638948</northBL>
<exTypeCode Sync="TRUE">1</exTypeCode>
</nativeExtBox>
<itemLocation>
<linkage Sync="TRUE">file://\\HIST-5SYQHH2-D\D$\Google Drive\Teaching\Hist 501D Digital History\MappingViolence\MappingViolence.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">WGS_1984_Web_Mercator_Auxiliary_Sphere</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;WGS_1984_Web_Mercator_Auxiliary_Sphere&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;Mercator_Auxiliary_Sphere&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;,0.0],PARAMETER[&amp;quot;Standard_Parallel_1&amp;quot;,0.0],PARAMETER[&amp;quot;Auxiliary_Sphere_Type&amp;quot;,0.0],UNIT[&amp;quot;Meter&amp;quot;,1.0],AUTHORITY[&amp;quot;EPSG&amp;quot;,3857]]&lt;/WKT&gt;&lt;XOrigin&gt;-20037700&lt;/XOrigin&gt;&lt;YOrigin&gt;-30241100&lt;/YOrigin&gt;&lt;XYScale&gt;148923141.92838538&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;WKID&gt;102100&lt;/WKID&gt;&lt;LatestWKID&gt;3857&lt;/LatestWKID&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
</coordRef>
<lineage>
<Process Date="20220505" Time="112221" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\Clip">Clip GEO_007_2015_07.tif "4477966.9007 4565912.4839 4480093.9081 4567681.8992" "D:\Google Drive\Teaching\Hist 501D Digital History\MappingViolence\MappingViolence.gdb\GEO_007_2015_07_Clip" "Walled City" 256 ClippingGeometry NO_MAINTAIN_EXTENT</Process>
</lineage>
</DataProperties>
<SyncDate>20220505</SyncDate>
<SyncTime>11222100</SyncTime>
<ModDate>20220505</ModDate>
<ModTime>11222100</ModTime>
</Esri>
<dataIdInfo>
<envirDesc Sync="TRUE">Microsoft Windows 10 Version 10.0 (Build 19042) ; Esri ArcGIS 12.9.0.32739</envirDesc>
<dataLang>
<languageCode Sync="TRUE" value="eng"/>
<countryCode Sync="TRUE" value="USA"/>
</dataLang>
<idCitation>
<resTitle Sync="TRUE">GEO_007_2015_07</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">40.226261</westBL>
<eastBL Sync="TRUE">40.245371</eastBL>
<northBL Sync="TRUE">37.916825</northBL>
<southBL Sync="TRUE">37.904279</southBL>
</GeoBndBox>
</geoEle>
</dataExt>
<idAbs/>
<searchKeys>
<keyword>MappingViolence</keyword>
</searchKeys>
<idPurp>Google Earth Imagery 2015_07.</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="3857"/>
<idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
<idVersion Sync="TRUE">6.18.3(9.3.1.2)</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<spdoinfo>
<rastinfo>
<rasttype Sync="TRUE">Pixel</rasttype>
<rowcount Sync="TRUE">1679</rowcount>
<colcount Sync="TRUE">1950</colcount>
<rastxsz Sync="TRUE">1.090944</rastxsz>
<rastysz Sync="TRUE">1.054288</rastysz>
<rastbpp Sync="TRUE">8</rastbpp>
<vrtcount Sync="TRUE">1</vrtcount>
<rastorig Sync="TRUE">Upper Left</rastorig>
<rastcmap Sync="TRUE">FALSE</rastcmap>
<rastcomp Sync="TRUE">LZ77</rastcomp>
<rastband Sync="TRUE">3</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">1.090944</absres>
<ordres Sync="TRUE">1.054288</ordres>
</coordrep>
</planci>
</planar>
</horizsys>
</spref>
<mdDateSt Sync="TRUE">20220505</mdDateSt>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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==</Data>
</Thumbnail>
</Binary>
</metadata>
