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This was a tough problem to track down because I had thought that the effect was at the edges of tiles when it fact they are throughout the data. You're right that the phenomena isn't in the data before mosaicking the data. The problem results from the resampling process that is inherent in mosaicking. You need to use either the cubic convolution or bilinear ...


0

The easiest way to do this is by importing the path where gdal_merge.py is located, in my case, /usr/bin/ -- substitute with the path to gdal_merge on your system, which, obviously, could be a Windows path too. import sys sys.path.append('/usr/bin/') import gdal_merge as gm You will now have to build up an array for sys.argv, as if you were calling ...


0

Wondering if the issue could be with rasters that are derived from elevations (curvature) rather than the original dem data. Some issue similar to hill shade rasters, which can be problematic to mosaic as mentioned here 'HILLSHADE NOTE: (Do not MOSAIC hillshades: MOSAIC the DEM's first and then create a hillshade). When working with multiple DEM files, it ...


3

gdal_merge.py -o output.tif `ls *.tif` The back ticks mean execute whatever is inside the back ticks before the main command, so this will find all tif files in current directory, which will then be used as the input to gdal_merge.py. Instead of backticks, you can also use the $(command) syntax, ie, gdal_merge.py -o output.tif $(ls *.tif) is ...



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