20211029 10142200 1.0 FALSE INDEKS_BAHAYA_KKEKERINGAN 002 10572236.164321 15698436.164321 -1224895.108968 673304.891032 1 Projected GCS_WGS_1984 Linear Unit: Meter (1.000000) WGS_1984_World_Mercator <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/10.3'><WKT>PROJCS[&quot;WGS_1984_World_Mercator&quot;,GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,0.0],PARAMETER[&quot;Standard_Parallel_1&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3395]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30198300</YOrigin><XYScale>149134210.44795552</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>3395</WKID><LatestWKID>3395</LatestWKID></ProjectedCoordinateSystem> 20211029 10142200 20211029 10142200 Version 6.2 (Build 9200) ; Esri ArcGIS 10.3.0.4322 INDEKS_BAHAYA_KKEKERINGAN 1 94.972013 141.021451 6.077582 -11.008308 File Geodatabase Raster Dataset dataset EPSG 8.2.6 Pixel 18982 51262 100.000000 100.000000 32 1 Upper Left FALSE LZ77 1 pixel codes FGDBR TRUE row and column 100.000000 100.000000 20211029 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