[pdal] Surface modeling

[Andreas Yankopolus]

I’m trying to convert LPC data into surface-height and surface-type rasters, where the surface height captures building/tree height and surface type differentiates between natural and man-made surfaces (similar to the USGS NLCD, but higher resolution). The goal is to use these rasters for radio propagation prediction. I’m using USGS 3DEP LPC data, which has tagged ground returns.

I’m looking at the first return for surface height, but it clearly needs filtering to remove birds, power lines, and other spurious data. Perhaps there are metrics on return strength, covariance, etc. that could be a basis for removing initial returns.

The dimensionality features seem a possibility for differentiating trees and buildings. Worst case, I can use NLCD data here.

Is there previous work in these areas that I can build on with PDAL? I’m also looking at LAStools, which appears to have binaries that could be replicated with PDAL pipelines.

Ground detection with PDAL and void filling with gdal_fillnodata is giving me a reasonable terrain-height raster. That’s the easiest part of the problem.

Cheers,

Andreas