Le jeudi 02 octobre 2014 09:02:00, Lukasz Tracewski a écrit : > Hi, > I only recently started my adventure with GDAL and GIS in general, so > please accept my apologies for perhaps maybe the most accurate formulation > of the problem. I also did my best to find the answer already on this > mailing list and outside, but to no avail - again possibly due to lack of > experience. Last year Hansen et al. prepared a detailed map, 30 meters > resolution, of forest cover for the whole planet. The data is publicly > accessible, both for online viewing and download. Both can be found here: > http://earthenginepartners.appspot.com/science-2013-global-forest The > forest cover images are GeoTIFF and have pixel values in range [0, 100] > that describes percentage of forest cover. I have some georeferenced > images that essentially are composed of ones and zeros, e.g.:0 1 1 0 00 1 > 1 1 00 1 0 0 0... Those images are in 1000 meters scale and can spawn over > whole continents. My aim is to calculate forest cover for them: wherever > the value is "1", this pixel should be added to the forest cover. Say the > Hansen image looks like this:10 20 30 40 5010 80 80 0 00 0 0 0 0... Then > rows and column of this images should be multiplied by respective rows and > columns of my own image, producing: 0 * 10 + 20 * 1 + 30 * 1 + 40 * 0 + 50 > * 0 + 10 * 0 + 80 * 1 + ... = 210 Mind that scale of both images is > different, so the example above is actually not accurate. The real > calculations should average pixel values, then sum them and then convert > to area. Can anyone point me where to start? Maybe you know of any > examples that could give me a hint?
Lukasz, There are likely many ways of doing that. Here's a potential workflow 1) With gdalwarp -r averge -ts you could make sure both raster have same dimensions 2) Use gdal_calc.py to do the multiplication pixel by pixel. 3) Use gdalinfo -stats to compute statistics on the raster generated by 2). Multiply the MEAN value by the raster width and raster height, and that will give you the sum. Even > > Thanks,Lucas -- Spatialys - Geospatial professional services http://www.spatialys.com _______________________________________________ gdal-dev mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/gdal-dev
