Hillshading

Question

Hey there!. I am doing landscape archaeology in eastern Bolivia and I have been working with SRTM to get elevation data for the region. This part of the world is a bit tricky because there is really not that much change in elevation so all DEMs tend to be relatively flat but with lot of noise because of the trees.

Nevertheless SRTM has worked for me really nicely, at least at the biggest scale. At this point I would like to focus a bit more in a specific part of the region and decided to use the japanese/nasa aster data. The DEM looks fantastic but I have been having a lot of troubles trying to generate a decent hillshade.

I am attaching a file that compares the results of both. I have generated both using the same procedure (Project to WGS84 UTM 20S, Hillshade with Z-factor 1, since data is in MTS). You see that the results are dramatically different. Is there any other recommended procedure to generate better results with ASTER? Any help would be greatly appreciated!.

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EduardoMachicado · Answer

Thanks for your answer. I have been fiddling around with the ASTER this past days and getter better results. One of the main issues was that I wasn't really paying attention to the fact that values between both DEMs were so different which of course made me realize that ASTER was actually in feet and using a Z factor of 1 was wrong.

I do not need to generate more accuracy really. It would be helpful though to know if there is a tutorial on how to filter the noise from the ASTER. The water bodies look a bit weird even when the Z factor is correct, I imagine that they need some sort of post processing.

Does anyone know about any good tutorials for this (Filtering, Smoothing, etc.)?

curtvprice · Answer

Is there any other recommended procedure to generate better results with ASTER? Any help would be greatly appreciated!.

Two different sensors are going to give you different levels of accuracy; there is no way to get around that. Some SRTM data has had additional pre-processing done to it (ie burning in water bodies etc) that would make the datasets even more different. You may be able to do some filtering to remove noise, but you cannot create accuracy that isn't there.

I noticed that the Aster data has rough areas in one of the water bodies (smooth areas in SRTM). Makes me wonder whether the Aster was acquired during a drier time of year when some of that water body (toward the lower left of your subset image) was dry.