20220608
08320400
1.0
FALSE
PCop_Maks_vannhastighet_33N.tif
file://\\nsv2-nasuni-01\prosjekt\O10240\10240464-01\10240464-01-03 ARBEIDSOMRAADE\10240464-01 RIVASS\10240464-01-05 MODELLER\Results\SAMLET\PCop_Maks_vannhastighet_33N.tif
Local Area Network
002
262013.155691
267566.155691
6626512.240647
6639624.240647
1
Projected
GCS_ETRS_1989
Linear Unit: Meter (1.000000)
ETRS_1989_UTM_Zone_33N
<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'><WKT>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],AUTHORITY["EPSG",25833]]</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>25833</WKID><LatestWKID>25833</LatestWKID></ProjectedCoordinateSystem>
32
FALSE
LZW
1
TIFF
TRUE
continuous
floating point
3.4e+38
Clip PCop_Vmaks "599471.637734345 6620642.49111455 603885.158733054 6633399.78411094" "C:\Users\eld\OneDrive - Multiconsult\Skrivebord\Kastes\Merge_NF\pcop_vmaks_clip.tif" Resultater_Samlet\Klippefil_Samlet 3,4e+38 ClippingGeometry NO_MAINTAIN_EXTENT
ProjectRaster pcop_vmaks_clip.tif "\\nsv2-nasuni-01\prosjekt\O10240\10240464-01\10240464-01-03 ARBEIDSOMRAADE\10240464-01 RIVASS\10240464-01-05 MODELLER\Results\SAMLET\PCop_Maks_vannhastighet_33N.tif" 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]] "Nearest neighbor" "1 1" # # 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]] NO_VERTICAL
20220608
08501500
20220608
08501500
Microsoft Windows 10 Version 10.0 (Build 19042) ; Esri ArcGIS 12.9.0.32739
PCop_Maks_vannhastighet_33N_1
1
10.753684
10.867022
59.828810
59.708237
PCop_maksH
Maksimal vannhastighet ved København-regnet
Raster Dataset
dataset
EPSG
4.3(4.0.0)
2
1
0
262013.155691 6626512.240647
262013.155691 6639624.240647
267566.155691 6639624.240647
267566.155691 6626512.240647
264789.655691 6633068.240647
5553
1.000000
13112
1.000000
PCop_Vmaks
700725395456.000000
0.000000
32
20220608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