Are there ways to improve processing time for TIN interpolation?
I'm using TIN interpolation as a step in a larger process. The interpolation step is taking a very long time (10+ hours to a few days), and I often end up with missing areas (see example below).
I'm only using ~2000 input points. My output raster is a 1m elevation raster grid covering about 25km x 5km so ~125 million cells. Output raster needs to match the resolution of another layer, so I can't just reduce the resolution.
The input values are essentially coming from elevation contours along a valley slope, but the valleys I'm working with are fairly steep, with frequent gradient changes - there is some room to use sparser input data, but I suspect not enough to cut processing time down to a few hours.
I've tried dividing the data into smaller blocks, but this doesn't seem to save any real time over processing it as a block. It does help with the missing data issues, however.
I've tried saving the output as both memory layers and on disk as a TIF, this doesn't seem to affect the processing time.
I'm using QGIS 3.8.3, have also tried on the LTR (3.4.12). I'm also open to a solution in R, as I use it for other steps in the process, but haven't found a TIN interpolation algorithm in R. I prefer the TIN algorithm to IDW or kriging because of how it respects the input contours and goes through known points.