20171222 11502600 1.0 FALSE MNA_TERRAIN_2017 002 2485000.000000 2513500.000000 1109500.000000 1136000.000000 1 Projected GCS_CH1903+ Linear Unit: Meter (1.000000) CH1903+_LV95 <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/10.1'><WKT>PROJCS[&quot;CH1903+_LV95&quot;,GEOGCS[&quot;GCS_CH1903+&quot;,DATUM[&quot;D_CH1903+&quot;,SPHEROID[&quot;Bessel_1841&quot;,6377397.155,299.1528128]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Hotine_Oblique_Mercator_Azimuth_Center&quot;],PARAMETER[&quot;False_Easting&quot;,2600000.0],PARAMETER[&quot;False_Northing&quot;,1200000.0],PARAMETER[&quot;Scale_Factor&quot;,1.0],PARAMETER[&quot;Azimuth&quot;,90.0],PARAMETER[&quot;Longitude_Of_Center&quot;,7.439583333333333],PARAMETER[&quot;Latitude_Of_Center&quot;,46.95240555555556],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,2056]]</WKT><XOrigin>-27386400</XOrigin><YOrigin>-32067900</YOrigin><XYScale>140996569.55187955</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>2056</WKID><LatestWKID>2056</LatestWKID></ProjectedCoordinateSystem> 20180323 10221400 20180323 10221400 Esri ArcGIS 10.2.0.3370 MNA_TERRAIN_2017 1 5.944909 6.320187 46.371046 46.128395 Ce MNT est le résultat d'une acquisition lasergrammétrique aérienne datant de février 2017. Résolution 0.5 m altimétrie Ce MNT est le résultat d'une acquisition lasergrammétrique aérienne datant de février 2017. Résolution 0.5 m SITG File Geodatabase Raster Dataset dataset EPSG 8.1.1 Pixel 53000 57000 0.500000 0.500000 32 1 Upper Left FALSE LZ77 1 pixel codes FGDBR TRUE row and column 0.500000 0.500000 20180323 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