My notes from reading 'An evaluation of void filling interpolation methods for SRTM data'.
The CIGAR version of SRTM contains a number of improvements, mostly around filling voids. I probably won’t be using SRTM for gpxz, but I like their thorough void-filling methodology.
Here’s my notes from reading the paper on the dataset:
- SRTM contains 3,000,000 voids, including up to 9% of Nepal
- Voids especially in mountainous and desert regions
- Uses EGM96 vertical datum
- Process done with tiles with large overlap.
- They plan to use ASTER DEM to fill holes in the future
- In an early version they had cliffs between tiles. Need to check for this, and avoid by using large overlaps.
- Released 2008 so sources might be dated.
- Nice map of voids, coloured by proportion
- Log plot of void size
- Use gtopo30 as filler
- Quantitative classification of voids into 15 categories
- Plains, grouped by altitude
- Geostatistical methods have a lot of parameters
- Multiple error metrics.
- Just from their sample imagery, IDW, spline, and kriging all look good. IDW and kriging look similar.
- Kriging and spline are usually the best interpolation method.
- Kriging always best for flat, spline bad for flat.
- Kriging fine for mountains, spline sometimes a bit better.
- Kriging only best for small voids.