[pdal] Best practice for classifying ground on large cloud?

[Bradley Chambers]

You should also look at
https://pdal.io/apps/tile.html if you haven’t already. It helps with
buffered tile creation. There will be some work required on your part to
delete the buffer and merge the filtered result at the end however.

Brad

On Wed, Aug 12, 2020 at 14:48 Andrew Cunliffe <andrewmcunliffe at gmail.com>
wrote:

> Does anyone have recommendations for best practice for classifying ground
> points on large clouds?
>
> I'd like to use SMRF to classify ground points in a large cloud (ca. 920
> 000 000 points), but am exceeding the system memory (128GB).
>
> It seems logical to split a large cloud into buffered tiles (to minimise
> edge effects), then run a classifier on each tile, delete the buffer and
> merge the tiles together again. It seems like this should be possible with
> filters.splitter, but is this the right way to go?
>
> Any suggestions on implementation much appreciated!
> Regards,
> Andy
>
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