20161025 10454100 1.0 FALSE INDEKS_BAHAYA_TSUNAMI 002 10576432.172500 15698212.172500 -1224817.053300 673222.946700 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>0.00020000000000000001</ZTolerance><MTolerance>0.00020000000000000001</MTolerance><HighPrecision>true</HighPrecision><WKID>3395</WKID><LatestWKID>3395</LatestWKID></ProjectedCoordinateSystem> 20161025 10454100 20161025 10454100 Version 6.2 (Build 9200) ; Esri ArcGIS 10.3.0.4322 bahaya.DBO.INDEKS_BAHAYA_TSUNAMI 1 95.009707 141.019439 6.076845 -11.007615 Raster Dataset dataset EPSG 8.2.6 Pixel 63268 170726 30.000000 30.000000 32 1 Upper Left FALSE LZ77 1 pixel codes SDR TRUE row and column 30.000000 30.000000 20161025 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