<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20220505</CreaDate>
<CreaTime>12124500</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="TRUE">GEO_008_2016_11_Clip</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
<nativeExtBox>
<westBL Sync="TRUE">4477966.813497</westBL>
<eastBL Sync="TRUE">4480093.813497</eastBL>
<southBL Sync="TRUE">4565911.871002</southBL>
<northBL Sync="TRUE">4567682.871002</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="121246" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\Clip">Clip GEO_008_2016_11.tif "4477966.9007 4565912.4839 4480093.9081 4567681.8992" "D:\Google Drive\Teaching\Hist 501D Digital History\MappingViolence\MappingViolence.gdb\GEO_008_2016_11_Clip" "Walled City" 256 ClippingGeometry NO_MAINTAIN_EXTENT</Process>
</lineage>
</DataProperties>
<SyncDate>20220505</SyncDate>
<SyncTime>12124500</SyncTime>
<ModDate>20220505</ModDate>
<ModTime>12124500</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_008_2016_11</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">40.226260</westBL>
<eastBL Sync="TRUE">40.245367</eastBL>
<northBL Sync="TRUE">37.916827</northBL>
<southBL Sync="TRUE">37.904275</southBL>
</GeoBndBox>
</geoEle>
</dataExt>
<idAbs/>
<searchKeys>
<keyword>MappingViolence</keyword>
</searchKeys>
<idPurp>Google Earth Imagery 2016_11</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">1771</rowcount>
<colcount Sync="TRUE">2127</colcount>
<rastxsz Sync="TRUE">1.000000</rastxsz>
<rastysz Sync="TRUE">1.000000</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">1.000000</absres>
<ordres Sync="TRUE">1.000000</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>
