[pdal] Surface modeling

[Andrew Bell]

Andreas,

You'd need to open a ticket and include your exact pipeline in order to
debug this, but I suspect there is an error in your syntax. Still, the
error you're getting seems odd.

On Thu, Apr 29, 2021 at 5:01 PM Andreas Yankopolus <andreas at yank.to> wrote:

> Bradley,
>
> Thanks for your example pipeline. Running it here with pdal 2.2.0, it
> prints “Parser error = !” when sent a pipeline with these statements. I’ve
> tracked the error messages to the blocks with "Classification = 6 WHERE …”
> and "Classification = 4 WHERE  …”.
>
> These blocks look valid based one the filters.assign description:
> https://pdal.io/stages/filters.assign.html
>
> For generating the surface height raster, I’d think to write the point
> with the highest Z value for the raster pixel. For surface type, perhaps
> label the raster pixel with the most common point classification. I’ll post
> a first cut.
>
> Cheers,
>
> Andreas
>
>
> On Apr 28, 2021, at 11:44, Bradley Chambers <brad.chambers at gmail.com>
> wrote:
>
> On Wed, Apr 28, 2021 at 9:34 AM Howard Butler <howard at hobu.co> wrote:
>
>>
>> > On Apr 27, 2021, at 4:11 PM, Andreas Yankopolus <andreas at yank.to>
>> wrote:
>>
>> > 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.
>>
>> I like to say that "PDAL is something you can use to build LAStools"
>> about its scope in relation to that product. PDAL isn't pre-canned
>> workflows for attacking a few kinds of LiDAR processing challenges. It's a
>> bunch of building blocks for processing point cloud data in the context of
>> ETL pipelines.
>>
>> That said, once constructed, those workflows can be quite valuable. Fancy
>> classification pipelines haven't typically been shared freely, however.
>
>
> Your mileage will certainly vary, but one pipeline that was derived from
> this notebook (
> https://github.com/rockestate/point-cloud-processing/blob/master/notebooks/point-cloud-processing.ipynb)
> is shared below. It classifies noise, ground, vegetation, and building
> returns. In my experience, it does a reasonable job but can still require
> fine tuning of the parameters.
>
> [
>     {
>         "type": "filters.assign",
>         "assignment": "Classification[:]=0"
>     },
>     {
>         "type": "filters.elm"
>     },
>     {
>         "type": "filters.smrf",
>         "where": "Classification != 7"
>     },
>     {
>         "type": "filters.hag_delaunay"
>     },
>     {
>         "type": "filters.outlier",
>         "multiplier": 16,
>         "class": 18,
>         "where": "!(Classification==2 || Classification==7)"
>     },
>     {
>         "type": "filters.approximatecoplanar",
>         "where": "HeightAboveGround >= 2 && !(Classification==2 ||
> Classification==7 || Classification==18)"
>     },
>     {
>         "type": "filters.outlier",
>         "class": 18,
>         "where": "!(Classification==2 || Classification==7 ||
> Classification==18) && Coplanar == 1"
>     },
>     {
>         "type": "filters.assign",
>         "value": "Classification=6 WHERE (Coplanar == 1 &&
> !(Classification == 7 || Classification==18))"
>     },
>     {
>         "type": "filters.covariancefeatures",
>         "mode": "normalized",
>         "feature_set": "Dimensionality",
>         "knn": 45
>     },
>     {
>         "type": "filters.assign",
>         "value": "Classification=4 WHERE (!(Classification==2 ||
> Classification==6) && HeightAboveGround >= 3.0 && Planarity < 0.8 &&
> Scattering > 0.1 && Verticality > 0.1)"
>     }
> ]
>
>
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-- 
Andrew Bell
andrew.bell.ia at gmail.com
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