Nicolas, > It's easy to go from coordinate space to pixel space in python using > something like. > > pixel_x = int(-124114.3 - geo_transform[0])/geo_transform[1]) > > What is the trick when there is an image rotation?
Compute the inverse geotransform with https://gdal.org/api/raster_c_api.html?highlight=invgeotransform#_CPPv419GDALInvGeoTransformPdPd (gdal.InvGeoTransform(gt) in Python ) And then use the coordinates in coordinate space as the input for this inverse geotransform column = inv_gt[0] + X * inv_gt[1] + Y * inv_gt[2] row = inv_gt[3] + X * inv_gt[4] + Y * inv_gt[5] > Also, as a second > very beginner question, what is the difference between geo_transform[2] > and geo_transform[4]? There are defined by the relationships at https://gdal.org/user/raster_data_model.html#affine-geotransform Even -- Spatialys - Geospatial professional services http://www.spatialys.com _______________________________________________ gdal-dev mailing list [email protected] https://lists.osgeo.org/mailman/listinfo/gdal-dev
