I'm fairly new to working with rasters. I found out that in my area the ASTER digital elevation data has a "bump" artifact in it, where there's a large (non existant in real life) bump in the elevation. I downloaded the SRTM elevation data, and although lower resolution doesn't seem to have the bump.
I thought about subtracting the STRM from ASTER data to see the difference between the two, and the result seems to have caught the bump pretty well.
Now i'm struggling with how to correct the original aster data. I thought about subtracting this "difference result" from the original aster data, but this effectively just converts it to the STRM data. So then I though I'd only select the most extreme scores from the "difference result" so it would only correct areas where the two data sets are off.
My problems: I don't know how to only select the extreme scores. (how do you calculate means and standard deviations of a raster?)
I don't know if this is a good way to do this. Any input would be helpful to solve this problem. I've found some journal articles that use machine learning to classify "bumps" etc. But that's too complicated for my purposes. I just want to more or less have it semi-accurate, don't need it to be perfect.
Extra thought: What if I could make a "mask" from the extreme scores of the "difference result" and then just default to SRTM in those areas?