Paper: Fusing DEMs
Notes from two papers discussing similar methods for merging elevation rasters.
1. Distance-based blending of SRTM and ASTER
Robinson, N., Regetz, J., & Guralnick, R. P. (2014). EarthEnv-DEM90: A nearly-global, void-free, multi-scale smoothed, 90m digital elevation model from fused ASTER and SRTM data. ISPRS Journal of Photogrammetry and Remote Sensing, 87, 57-67.
- Merged dataset from ASTER and CIGAR SRTM
- Highlights importance off well-documented methodology
- They shifted ASTER by a 1/2 pixel to align cell edges (instead off centres) with exact degree lines.
- Voids filled with Delta Surface Fill (DSF) using an ancillary dataset.
- Extrapolates dH over the hole, then adds that to the ancillary dataset.
- Which is nice in that it works for datasets that have a regular bias compared to the size of the hole, like a different datum.
- Grid search to choose the best interpolation smoothing and tension parameters, taking training data from shifting actual holes.
- SRTM was also shifted by a half pixel.
- Both DEMs were smoothed to reduce noise. Smoothing factor was chosen based on an estimate of noise.
- This probably not a bad idea for SRTM and ASTER (which are very noisy) but I’m hoping won’t be needed for gpxz)
- They used weighted average blending with weight ~ exp(x^2).
- This resulted in equal weights at a distance of 2km (about 200 pixels) and 1% at 6km.
2. Error-based blending
Petrasova, A., Mitasova, H., Petras, V., & Jeziorska, J. (2017). Fusion of high-resolution DEMs for water flow modeling. Open Geospatial Data, Software and Standards, 2(1), 1-8.
- Distance-weighted blending with spatially varying blending zone width based on elevation difference.
- DEMs must have common CRS and resolution (though I just thing for their discretisation and notation, the theory should hold otherwise.)
- Large elevation differences along the edge of the hires raster (typically representing vegetation or built structures) should be removed first.
- DEMs are averaged in a blend zone by weight that varies from 0 to 1 across the zone. The weight can be a function of distance into the blend zone: most simply directly proportional, or could be logistic. (Something like logistic would be less smooth, but would make the result closer to the either input DEM.)
- They suggest a blend width increasing with height difference decreased by transition angle (which you specify).
- dH is smoothed with a 5 pixel radius.