Since I originally posted this 3D printing conversion method, several other options are now available to convert a raster DEM/DTM (digital elevation/terrain model) to a 3D format. Here are just a few worth checking out before I list a workflow using a GDAL/Python script method as posted by Jake from Zurich.
First get yourself a GDAL/Python environment running. I recommend Anaconda Python. Once Anaconda is installed type "conda install gdal". Done.
Second head over to gis.stackexchange and copy Jake's gdal_rastertotrn.py code. I find that filename hard to read "*totrn.py" (where trn must mean terrain). I would prefer simply the script name "gdal2PLY.py" (which is now also on github). Okay now to deal with NoData and the large HiRISE DTM listed above.
1.) find minimum Z value
where -tr 5 5 means target resolution of 5m in X, Y
where -r bilinear means the resampling method (bilinear should be smooth enough)
4.) Load in Meshlab to visualize and/or convert to other formats (like STL or OBJ).
- Blender (free) has a plug-in to open up HiRISE DTMs. See instructions here. From Blender, I think you can export to STL or OBJ? http://www.uahirise.org/dtm/howto.php
- SpaceBlenders - We also support a variation on this tool but it requires getting your hands dirty with some configurations to get the GDAL library installed with Blender: https://github.com/USGS-Astrogeology/SpaceBlender (based on a NAU capstone)
- GRASS: https://grass.osgeo.org/screenshots/3D/
- Unity: https://alastaira.wordpress.com/2013/11/12/importing-dem-terrain-heightmaps-for-unity-using-gdal/
- new to me (2019). AMES Stereo Pipeline (ASP) using their point2mesh routine. It is always good to dig through their routines for gems. https://ti.arc.nasa.gov/tech/asr/groups/intelligent-robotics/ngt/stereo/
Since I am a GDAL user, I usually first dig around for a method using it (since it has support for several planetary formats). When I ran across this script by Jake it was just the simple solution I was after. I wanted GDAL support in a command-line version with no fancy interface or setup. I would let Jake's original post stand on its own but there are a couple steps a I had to take to get it working for me.
- It currently doesn't support NoData values. It supports them but it doesn't strip them. This seems like a tangible thing to handle in the code but I haven't tried so below is a work-around.
- I assume you will want to be careful on the size of the input DEM. Thus here, for my Mars HiRISE example (DTEEC_025123_2045_026811_2045_A01.IMG in PDS v3 format), I sub-sample it to 5m/p. This DEM is located in Mawrth Valles. Image credit: NASA/JPL/University of Arizona/USGS.
NoData and Resampling Workflow
Second head over to gis.stackexchange and copy Jake's gdal_rastertotrn.py code. I find that filename hard to read "*totrn.py" (where trn must mean terrain). I would prefer simply the script name "gdal2PLY.py" (which is now also on github). Okay now to deal with NoData and the large HiRISE DTM listed above.
- $ gdalinfo -mm DTEEC_025123_2045_026811_2045_A01.IMG
Computed Min/Max=-2790.594,-2063.563
NoData Value=-3.4028226550889045e+038
- 2.) map the DEMs Nodata to a nice round value below the minimum (for our example say -2791). Note during this step we can also sub-sample the file to a lower resolution. We could create a giant PLY but I doubt many apps will be able to open it.
$ gdalwarp -dstnodata -2791 -tr 5 5 -r bilinear DTEEC_025123_2045_026811_2045_A01.IMG temp_DTEEC_5m_nodata.tif
where -tr 5 5 means target resolution of 5m in X, Y
where -r bilinear means the resampling method (bilinear should be smooth enough)
- 3. ) Now simply run Jake's script in your GDAL/Python environment.
4.) Load in Meshlab to visualize and/or convert to other formats (like STL or OBJ).
Figure: resultant binary PLY formatted surface in meshlab. I added some "radiance scaling" under Render - Shaders to highlight the topography breaks. Note this will still have a NoData plane but since it is near the minimum value it doesn't mess-up the exaggeration.
Future: Still need a better method to handle the NoData...
