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For an example of how to do this in code (Python/GDAL), look at this example in the GDAL cookbook, in particular the world2Pixel() function. I've added some comments to show what the variables are:- def world2Pixel(geoMatrix, x, y): """ Uses a gdal geomatrix (gdal.GetGeoTransform()) to calculate the pixel location of a geospatial coordinate """ ...


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If you have a source image with these limits φmin, λmin and φmax, λmax that has been warped to target image with these limits Nmin, Emin and Nmax, Emax surely you can do simple bilinear interpolation to map a general point from φ, λ to N, E? Just rearrange (φ - φmin) / (φmax - φmin) = (N - Nmin) / (Nmax ...


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It seems like a an resampling issue. I guess you used Nearest Neighbor, which is also the defualt setting. Nearest neighbor can lead to small pixel displacement of up to half a pixel. You can try to set the resampling method to bilinear and have a look if it fits your needs better. Bilinear interpolates pixel values by leaving the cells untouched in position ...


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The resampling method 'near' or 'nearest' is generally to be considered only for succinct/classified data, it attempts to assign a cell value based on the closest source pixel: This is most commonly integer (int8, int32, int64) types but can be of type float (float32, float64) where each cell represnts classified values and generally values appear more ...



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