<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="nb">
<Esri>
<CreaDate>20251118</CreaDate>
<CreaTime>14335800</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<lineage>
<Process Date="20251118" Time="143358" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Spatial Analyst Tools.tbx\ExtractByMask">ExtractByMask odm_orthophoto.tif Polygons "C:\Users\mpr\Documents\ArcGIS\Projects\Drone skript test\Drone skript test.gdb\Extract_Ortofoto" Inside "630100,295117525 6636598,47984993 630373,419949559 6636832,20742358 PROJCS["WGS_1984_UTM_Zone_31N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",3.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]"</Process>
<Process Date="20251118" Time="144036" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Spatial Analyst Tools.tbx\ExtractByMask">ExtractByMask odm_orthophoto.tif "Extract by Mask Input raster or feature mask data (Polygons)" "C:\Users\mpr\Documents\ArcGIS\Projects\Drone skript test\Drone skript test.gdb\Extract_Ortofoto" Inside "630100,295117525 6636598,47984993 630373,419949559 6636832,20742358 PROJCS["WGS_1984_UTM_Zone_31N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",3.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]"</Process>
<Process Date="20251118" Time="144108" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Spatial Analyst Tools.tbx\ExtractByMask">ExtractByMask odm_orthophoto.tif "Extract by Mask Input raster or feature mask data (Polygons)" "C:\Users\mpr\Documents\ArcGIS\Projects\Drone skript test\Drone skript test.gdb\Extract_Ortofoto" Inside "630100,295117525 6636598,47984993 630373,419949559 6636832,20742358 PROJCS["WGS_1984_UTM_Zone_31N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",3.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]"</Process>
<Process Date="20251118" Time="144720" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\ProjectRaster">ProjectRaster Extract_Ortofoto "C:\Users\mpr\Documents\ArcGIS\Projects\Drone skript test\Drone skript test.gdb\Extract_Ortho_ProjectRaster" PROJCS["ETRS_1989_UTM_Zone_32N",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",9.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]],VERTCS["NN2000_height",VDATUM["Norway_Normal_Null_2000"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] "Nearest neighbor" "6,86601231064655E-02 6,86601231063384E-02" ETRS_1989_To_WGS_1984 # PROJCS["WGS_1984_UTM_Zone_31N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",3.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]] NO_VERTICAL</Process>
<Process Date="20251118" Time="150046" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\Toolboxes\Data Management Tools.tbx\CopyMultiple">CopyMultiple "'C:\Users\mpr\Documents\ArcGIS\Projects\Drone skript test\Drone skript test.gdb\Extract_Ortho_ProjectRaster' RasterDataset;'C:\Users\mpr\Documents\ArcGIS\Projects\Drone skript test\Drone skript test.gdb\Extract_DSM_ProjectRaster' RasterDataset" "C:\Users\mpr\Documents\ArcGIS\Projects\Drone skript test\Drone scan haust 2025.gdb" Extract_Ortho_ProjectRaster;Extract_DSM_ProjectRaster "Extract_Ortho_ProjectRaster RasterDataset Extract_Ortho_ProjectRaster #;Extract_DSM_ProjectRaster RasterDataset Extract_DSM_ProjectRaster #"</Process>
<Process Date="20260224" Time="153257" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\ProjectRaster">ProjectRaster Extract_Ortho_ProjectRaster "C:\Users\hrk\OneDrive - Multiconsult\Dokumenter\ArcGIS\Projects\3Dtest\3Dtest.gdb\Extract_Ortho__ProjectRaster" PROJCS["ETRS_1989_UTM_Zone_33N",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",15.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]],VERTCS["N2000_height",VDATUM["N2000"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] "Nearest neighbor" "0,068660123106465 6,86601231062262E-02" # # PROJCS["ETRS_1989_UTM_Zone_32N",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",9.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]],VERTCS["NN2000_height",VDATUM["Norway_Normal_Null_2000"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] NO_VERTICAL</Process>
</lineage>
<itemProps>
<itemName Sync="TRUE">Extract_Ortho__ProjectRaster</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
<nativeExtBox>
<westBL Sync="TRUE">-41028.794825</westBL>
<eastBL Sync="TRUE">-40712.271658</eastBL>
<southBL Sync="TRUE">6673918.921774</southBL>
<northBL Sync="TRUE">6674203.037363</northBL>
<exTypeCode Sync="TRUE">1</exTypeCode>
</nativeExtBox>
<itemLocation>
<linkage Sync="TRUE">file://\\STD-5CG4172YFL\C$\Users\hrk\OneDrive - Multiconsult\Dokumenter\ArcGIS\Projects\3Dtest\3Dtest.gdb</linkage>
<protocol Sync="TRUE">Local Area Network</protocol>
</itemLocation>
</itemProps>
<coordRef>
<type Sync="TRUE">Projected</type>
<geogcsn Sync="TRUE">GCS_ETRS_1989</geogcsn>
<csUnits Sync="TRUE">Linear Unit: Meter (1.000000)</csUnits>
<projcsn Sync="TRUE">ETRS_1989_UTM_Zone_33N</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/3.1.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;ETRS_1989_UTM_Zone_33N&amp;quot;,GEOGCS[&amp;quot;GCS_ETRS_1989&amp;quot;,DATUM[&amp;quot;D_ETRS_1989&amp;quot;,SPHEROID[&amp;quot;GRS_1980&amp;quot;,6378137.0,298.257222101]],PRIMEM[&amp;quot;Greenwich&amp;quot;,0.0],UNIT[&amp;quot;Degree&amp;quot;,0.0174532925199433]],PROJECTION[&amp;quot;Transverse_Mercator&amp;quot;],PARAMETER[&amp;quot;False_Easting&amp;quot;,500000.0],PARAMETER[&amp;quot;False_Northing&amp;quot;,0.0],PARAMETER[&amp;quot;Central_Meridian&amp;quot;,15.0],PARAMETER[&amp;quot;Scale_Factor&amp;quot;,0.9996],PARAMETER[&amp;quot;Latitude_Of_Origin&amp;quot;,0.0],UNIT[&amp;quot;Meter&amp;quot;,1.0],AUTHORITY[&amp;quot;EPSG&amp;quot;,25833]],VERTCS[&amp;quot;N2000_height&amp;quot;,VDATUM[&amp;quot;N2000&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;,3900]]&lt;/WKT&gt;&lt;XOrigin&gt;-5120900&lt;/XOrigin&gt;&lt;YOrigin&gt;-9998100&lt;/YOrigin&gt;&lt;XYScale&gt;450445547.3910538&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;25833&lt;/WKID&gt;&lt;LatestWKID&gt;25833&lt;/LatestWKID&gt;&lt;VCSWKID&gt;105793&lt;/VCSWKID&gt;&lt;LatestVCSWKID&gt;3900&lt;/LatestVCSWKID&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
</coordRef>
</DataProperties>
<SyncDate>20260224</SyncDate>
<SyncTime>15325700</SyncTime>
<ModDate>20260224</ModDate>
<ModTime>15325700</ModTime>
</Esri>
<dataIdInfo>
<envirDesc Sync="TRUE">Microsoft Windows 10 Version 10.0 (Build 22631) ; Esri ArcGIS 13.1.0.41833</envirDesc>
<dataLang>
<languageCode Sync="TRUE" value="nob"/>
<countryCode Sync="TRUE" value="NOR"/>
</dataLang>
<idCitation>
<resTitle Sync="TRUE">Ortofoto_midt_2025_2_0</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">5.321404</westBL>
<eastBL Sync="TRUE">5.327710</eastBL>
<northBL Sync="TRUE">59.848987</northBL>
<southBL Sync="TRUE">59.846059</southBL>
</GeoBndBox>
</geoEle>
</dataExt>
<idAbs/>
<searchKeys>
<keyword>Multiconsult</keyword>
<keyword>SIM</keyword>
<keyword>Svartasmoget</keyword>
</searchKeys>
<idPurp>Ortofoto av midtre del av SIM,Svartasmoget</idPurp>
<idCredit/>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<mdLang>
<languageCode Sync="TRUE" value="nob"/>
<countryCode Sync="TRUE" value="NOR"/>
</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="25833"/>
<idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
<idVersion Sync="TRUE">4.3(4.0.0)</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<spdoinfo>
<rastinfo>
<rasttype Sync="TRUE">Pixel</rasttype>
<rowcount Sync="TRUE">4138</rowcount>
<colcount Sync="TRUE">4610</colcount>
<rastxsz Sync="TRUE">0,068660</rastxsz>
<rastysz Sync="TRUE">0,068660</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">0,068660</absres>
<ordres Sync="TRUE">0,068660</ordres>
</coordrep>
</planci>
</planar>
</horizsys>
</spref>
<mdDateSt Sync="TRUE">20260224</mdDateSt>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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</Data>
</Thumbnail>
</Binary>
</metadata>
