<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20200723</CreaDate>
<CreaTime>08351600</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="TRUE">BANGI_20200710_TNB</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
<nativeExtBox>
<westBL Sync="TRUE">101.771657</westBL>
<eastBL Sync="TRUE">101.779839</eastBL>
<southBL Sync="TRUE">2.923273</southBL>
<northBL Sync="TRUE">2.932276</northBL>
<exTypeCode Sync="TRUE">1</exTypeCode>
</nativeExtBox>
<itemLocation>
<linkage Sync="TRUE">file://\\DESKTOP-R5IQKF7\H$\PRASARANA\1. DATA GIS UKM 2019-2020\1. IMAGE UAV (BASE MAP)\UKM GEOREF 2020\UKM_WGS84.gdb</linkage>
<protocol Sync="TRUE">Local Area Network</protocol>
</itemLocation>
</itemProps>
<coordRef>
<type Sync="TRUE">Geographic</type>
<geogcsn Sync="TRUE">GCS_WGS_1984</geogcsn>
<csUnits Sync="TRUE">Angular Unit: Degree (0.017453)</csUnits>
<peXml Sync="TRUE">&lt;GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' 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/10.8'&gt;&lt;WKT&gt;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],AUTHORITY[&amp;quot;EPSG&amp;quot;,4326]],VERTCS[&amp;quot;EGM96_Geoid&amp;quot;,VDATUM[&amp;quot;EGM96_Geoid&amp;quot;],PARAMETER[&amp;quot;Vertical_Shift&amp;quot;,0.0],PARAMETER[&amp;quot;Direction&amp;quot;,1.0],UNIT[&amp;quot;Meter&amp;quot;,1.0],AUTHORITY[&amp;quot;EPSG&amp;quot;,5773]]&lt;/WKT&gt;&lt;XOrigin&gt;-400&lt;/XOrigin&gt;&lt;YOrigin&gt;-400&lt;/YOrigin&gt;&lt;XYScale&gt;11258999068426.238&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;8.983152841195215e-09&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;LeftLongitude&gt;-180&lt;/LeftLongitude&gt;&lt;WKID&gt;4326&lt;/WKID&gt;&lt;LatestWKID&gt;4326&lt;/LatestWKID&gt;&lt;VCSWKID&gt;5773&lt;/VCSWKID&gt;&lt;LatestVCSWKID&gt;5773&lt;/LatestVCSWKID&gt;&lt;/GeographicCoordinateSystem&gt;</peXml>
</coordRef>
<lineage>
<Process Date="20200723" Time="083542" ToolSource="c:\program files (x86)\arcgis\desktop10.7\ArcToolbox\Toolboxes\Data Management Tools.tbx\ProjectRaster">ProjectRaster G:\Amartur\UAV_Img\200710_TNB\ortho.tif "E:\UKM GEOREF 2020\UKM_CASSINI_BEFORE_GEOREF.gdb\TNB_200710" PROJCS['My_Cassini_Soldner_Selangor',GEOGCS['GCS_Kertau',DATUM['D_Kertau',SPHEROID['Everest_1830_Modified',6377304.063,300.8017]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Cassini'],PARAMETER['False_Easting',-21759.457],PARAMETER['False_Northing',55960.954],PARAMETER['Central_Meridian',101.5082303],PARAMETER['Scale_Factor',1.0],PARAMETER['Latitude_Of_Origin',3.680348333],UNIT['Meter',1.0]] NEAREST "4.01389793608228E-02 4.03561050621265E-02" Kertau_To_WGS_1984 # GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],VERTCS['unknown',VDATUM['unknown'],PARAMETER['Vertical_Shift',0.0],PARAMETER['Direction',1.0],UNIT['Meter',1.0]] NO_VERTICAL</Process>
<Process Date="20200728" Time="082941" ToolSource="c:\program files (x86)\arcgis\desktop10.7\ArcToolbox\Toolboxes\Data Management Tools.tbx\ProjectRaster">ProjectRaster "E:\UKM GEOREF 2020\UKM_CASSINI_BEFORE_GEOREF.gdb\TNB_200710" "E:\UKM GEOREF 2020\UKM_RSO_BEFORE_GEOREF.gdb\TNB_200710" PROJCS['Kertau_RSO_Malaya_Meters',GEOGCS['GCS_Kertau',DATUM['D_Kertau',SPHEROID['Everest_1830_Modified',6377304.063,300.8017]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Rectified_Skew_Orthomorphic_Natural_Origin'],PARAMETER['False_Easting',804671.299775],PARAMETER['False_Northing',0.0],PARAMETER['Scale_Factor',0.99984],PARAMETER['Azimuth',-36.97420943711801],PARAMETER['Longitude_Of_Center',102.25],PARAMETER['Latitude_Of_Center',4.0],PARAMETER['XY_Plane_Rotation',-36.86989764584402],UNIT['Meter',1.0]] NEAREST "4.01389793608228E-02 4.03561050621265E-02" # # PROJCS['My_Cassini_Soldner_Selangor',GEOGCS['GCS_Kertau',DATUM['D_Kertau',SPHEROID['Everest_1830_Modified',6377304.063,300.8017]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Cassini'],PARAMETER['False_Easting',-21759.457],PARAMETER['False_Northing',55960.954],PARAMETER['Central_Meridian',101.5082303],PARAMETER['Scale_Factor',1.0],PARAMETER['Latitude_Of_Origin',3.680348333],UNIT['Meter',1.0]] NO_VERTICAL</Process>
<Process Date="20230911" Time="162842" ToolSource="c:\program files (x86)\arcgis\desktop10.8\ArcToolbox\Toolboxes\Data Management Tools.tbx\ProjectRaster">ProjectRaster TNB_200710 "H:\PRASARANA\1. DATA GIS UKM 2019-2020\1. IMAGE UAV (BASE MAP)\UKM GEOREF 2020\UKM_WGS84.gdb\BANGI_20200710_TNB" GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],VERTCS['EGM96_Geoid',VDATUM['EGM96_Geoid'],PARAMETER['Vertical_Shift',0.0],PARAMETER['Direction',1.0],UNIT['Meter',1.0]] NEAREST "3.62828395156741E-07 3.64803412622363E-07" Kertau_To_WGS_1984 # PROJCS['Kertau_RSO_Malaya_Meters',GEOGCS['GCS_Kertau',DATUM['D_Kertau',SPHEROID['Everest_1830_Modified',6377304.063,300.8017]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Rectified_Skew_Orthomorphic_Natural_Origin'],PARAMETER['False_Easting',804671.299775],PARAMETER['False_Northing',0.0],PARAMETER['Scale_Factor',0.99984],PARAMETER['Azimuth',-36.97420943711801],PARAMETER['Longitude_Of_Center',102.25],PARAMETER['Latitude_Of_Center',4.0],PARAMETER['XY_Plane_Rotation',-36.86989764584402],UNIT['Meter',1.0]] NO_VERTICAL</Process>
</lineage>
</DataProperties>
<SyncDate>20230911</SyncDate>
<SyncTime>16281700</SyncTime>
<ModDate>20230911</ModDate>
<ModTime>16281700</ModTime>
</Esri>
<dataIdInfo>
<envirDesc Sync="TRUE"> Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388</envirDesc>
<dataLang>
<languageCode Sync="TRUE" value="eng"/>
<countryCode Sync="TRUE" value="USA"/>
</dataLang>
<idCitation>
<resTitle Sync="TRUE">BANGI_20200710_TNB</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">101.771657</westBL>
<eastBL Sync="TRUE">101.779839</eastBL>
<northBL Sync="TRUE">2.932276</northBL>
<southBL Sync="TRUE">2.923273</southBL>
</GeoBndBox>
</geoEle>
</dataExt>
<idAbs/>
<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="4326"/>
<idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
<idVersion Sync="TRUE">6.2(3.0.1)</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<spdoinfo>
<rastinfo>
<rasttype Sync="TRUE">Pixel</rasttype>
<rowcount Sync="TRUE">24679</rowcount>
<colcount Sync="TRUE">22551</colcount>
<rastxsz Sync="TRUE">0.000000</rastxsz>
<rastysz Sync="TRUE">0.000000</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">4</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">0.000000</absres>
<ordres Sync="TRUE">0.000000</ordres>
</coordrep>
</planci>
</planar>
</horizsys>
</spref>
<mdDateSt Sync="TRUE">20230911</mdDateSt>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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</Data>
</Thumbnail>
</Binary>
</metadata>
