[pdal] PCL

[Bradley Chambers]

VoxelDownsize will return either the center coordinate of each occupied
voxel or the actual coordinate of the first detected point to occupy a
voxel.

The Sample filter downsamples points, such that no two points can be closer
than a given radius. It does not grid or compute any statistics.

VoxelCentroidNearestNeighbor returns the point that is nearest the centroid
of all points within a given voxel. (VoxelCenterNearestNeighbor does the
same, but for the point closest to the voxel center.)

We do not have a filter that grids the data and computes summary
statistics. We do have some that do similar things as intermediate steps.
It would be pretty trivial to develop though.

In the meantime, maybe you would have luck writing with the GDAL writer,
saving just the mean elevation band, and then reading that raster with the
GDAL reader to interpret it as a point cloud? The only caveat I can think
of here is that the mean elevation computation will consider points that
extend beyond the current raster cell (root 2 times the cell size by
default).

On Mon, Nov 2, 2020 at 2:02 PM alison.cramer3 <alisoncramer at nevada.unr.edu>
wrote:

> Okay well that is good to know.  Is there an option in the PDAL
> voxeldownsize
> to choose average?  Kind of like creating a raster, but gridding my point
> cloud to take to average height value?  similar to the raster function in
> cloudcompare, but I don't want a raster, I want a gridded point cloud.  I
> used filters.sample, but this is random sampling, is it not?
>
>
>
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