20251118
14335800
1.0
FALSE
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]]"
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]]"
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]]"
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
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 #"
Extract_Ortho_ProjectRaster
002
293972.984715
294266.300761
6640014.453208
6640272.134650
1
file://\\STD-5CG4110W3H\C$\Users\mpr\Documents\ArcGIS\Projects\Drone skript test\Drone skript test.gdb
Local Area Network
Projected
GCS_ETRS_1989
Linear Unit: Meter (1.000000)
ETRS_1989_UTM_Zone_32N
<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'><WKT>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],AUTHORITY["EPSG",25832]],VERTCS["NN2000_height",VDATUM["Norway_Normal_Null_2000"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0],AUTHORITY["EPSG",5941]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>450445547.3910538</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>25832</WKID><LatestWKID>25832</LatestWKID><VCSWKID>5941</VCSWKID><LatestVCSWKID>5941</LatestVCSWKID></ProjectedCoordinateSystem>
20251118
14472000
20251118
14472000
Microsoft Windows 10 Version 10.0 (Build 22631) ; Esri ArcGIS 13.1.0.41833
ortofoto_2025_midt
1
5.321817
5.327296
59.848751
59.846295
Ortofoto av midtre del av SIM,Svartasmoget
File Geodatabase Raster Dataset
dataset
EPSG
4.3(4.0.0)
Pixel
3753
4272
0,068660
0,068660
8
1
Upper Left
FALSE
LZ77
4
pixel codes
FGDBR
TRUE
row and column
0,068660
0,068660
20251118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