20200121 18370100 1.0 FALSE Ortos2018_clip1 002 -54840.610100 -38261.438200 188542.900500 200494.240600 1 Projected GCS_ETRS_1989 Linear Unit: Meter (1.000000) ETRS_1989_Portugal_TM06 <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/10.6'><WKT>PROJCS[&quot;ETRS_1989_Portugal_TM06&quot;,GEOGCS[&quot;GCS_ETRS_1989&quot;,DATUM[&quot;D_ETRS_1989&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-8.133108333333334],PARAMETER[&quot;Scale_Factor&quot;,1.0],PARAMETER[&quot;Latitude_Of_Origin&quot;,39.66825833333333],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3763]]</WKT><XOrigin>-5623200</XOrigin><YOrigin>-14394800</YOrigin><XYScale>450265407.00157917</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>3763</WKID><LatestWKID>3763</LatestWKID></ProjectedCoordinateSystem> 20200122 11412200 20200122 11412200 Version 6.2 (Build 9200) ; Esri ArcGIS 10.6.0.8321 Ortos2018_clip1 1 -8.789627 -8.590403 41.472858 41.364294 Ortos 2018 Ortos 2018 Ortos 2018 File Geodatabase Raster Dataset dataset EPSG 6.14(9.3.0.0) Pixel 47806 66317 0,249999 0,249997 8 1 Upper Left FALSE LZ77 4 pixel codes FGDBR TRUE row and column 0,249999 0,249997 20200122 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