borevitzlab / DEM-o-matic

Creates synthetic digital elevation models (DEMs) from point data.

DEM-o-matic

Creates synthetic digital elevation models (DEMs) from point data.

Prerequisites:

• GDAL (I installed mine through installing QGIS, which might be easier)

• Python 3

Usage:

1. Add points to dem_orig.csv. Contour interpolation will be done between consecutive points of the same elevation, in order.

2. Open a terminal in the folder with interp.py and run python3 interp.py dem_orig.csv <interpolation interval> where <interpolation interval> is the distance between points in Easting/Northing units, e.g. 10. Too fine values may cause sharp contours, while too sparse values may result in rough contours.

3. Run gdal_grid with the appropriate settings. Example outputs are produced with gdal_grid -a invdist:power=3.0:smoothing=5.0:maxpoints=6 -outsize 1200 1200 -of GTiff -l dem dem.vrt dem.tiff. See gdal_grid documentation for details on interpolation algorithms.

4. The resulting dem.tiff should be readable by QGIS/ArcGIS. Some programs may take a .png instead; this can be done using gdal_translate with something like (gdal_translate -of PNG -scale -outsize 120 120 dem.tiff dem.png )

Further steps:

• To 3D print, run a .png through heightmap2stl (using grayfix.py may also be needed to fix grayscale log values, e.g. python grayfix.py dem.png dem_fix.png)

• Import a voxel version to MagicaVoxel with FileToVox

• Import to Sketchup with the BitmapToMesh plugin (may not work, try other plugins or maybe convert to STL and use Sketchup-STL)