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I think that's getting there - I was unaware of the arithmetic transforms. Modifying the initial curvature radius and playing with a combination of logs and other functions get me somewhat closer to a linear distribution and a better subsampling distribution.
Thanks Daniel.

The attached shows an example where this is working in principle: I have created an SF based on curvature and then subsampled by space inversely proportional to curvature. The settings I've used are 1m radius for the curvature local neighbourhood radius, which resulted in curvature levels from 0.000...

OK thanks, that looks like it might work for me.

Hi, I'm working with aerial lidar data. I've subsampled by space to get to a manageable file size, but what I would like to do now is further optimise the point cloud by reducing the density of points in areas where the ground surface is relatively smooth, and retain high density in areas where the ...