[pdal] Extract terrain from TLS point cloud

[Silvia Franceschi]

Dear Luigi,
finally I could start to work again on the DTM extraction and I was trying
to apply the same commands as in your slides.
Unfortunately I am not so smart to understand how to do this kind of
assignment in a PDAL pipeline:

- normalZ [0:0.6] : Classification ->1
- normalZ ! [0:0.6] : Classification ->2
- merge soil / no soil

I tried using the filter.assign but it seems that I can not assign values
of a field while filtering on an other field.
And also I can not understand what you mean with merge soil/no soil...

The pipeline I did is like this:

{
    "pipeline": [
{
            "type": "readers.las",
            "filename":"aaa.las"
        },
{
            "type":"filters.range",
            "limits":"Classification[2:2]"
        },
{
            "type":"filters.normal",
            "knn": 30
    },
{
            "type":"filters.assign",
            "assignment" : "normalZ[0:6]=Classification[2]",
            "assignment" : "normalZ[0:6]!=Classification[1]"
    },
        {
            "type": "writers.las",
            "filename":"bbb.las"
        }
    ]
}

Could you please address me to the right commands to use to finalize the
pipeline?

Thank you for the big help!

Best regards

Silvia




On Mon, May 13, 2019 at 9:24 AM Luigi Pirelli <luipir at gmail.com> wrote:

> we had similar problems with TLS in urban context regarding first part pf
> the cars
> you can see our strategy to clean the first PMF effect in slides from
> http://slides.com/darango/deck-10-11-12-11-12#/11
> to
> http://slides.com/darango/deck-10-11-12-11-12#/1
> <http://slides.com/darango/deck-10-11-12-11-12#/11>5
>
> the main idea is to do noise cleaning, PMF, filter on normal, filter on
> kdistance, PMF again
>
> not clear to me if you can have a good discrimination of the ground part
> of the threes using normals due to nature of these surfaces.
>
> cheers
>
> Luigi Pirelli
>
>
> **************************************************************************************************
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>
> **************************************************************************************************
>
>
> On Sat, 11 May 2019 at 10:01, Silvia Franceschi <
> silvia.franceschi at gmail.com> wrote:
>
>> Dear all,
>> I am trying to extract the ground points from a point cloud of a
>> terrestrial laser scanner (TLS) in a forestry environment, but the result
>> is not so good as the one I got using data from ALS.
>> What I did is:
>> 1. denoise the dataset using the filter.outlier and a filter.range for Z
>> ranges:
>>             "type": "filters.outlier",
>>             "method": "statistical",
>>             "multiplier": 3,
>>             "mean_k": 8
>> 2. apply a filter.elm and a filter.smrf to the cleaned dataset
>> For the SMRF filter I used these parameters:
>>             "type": "filters.smrf",
>>             "slope":0.2,
>>             "window":16,
>>             "threshold":0.45,
>>             "scalar":1.2
>>
>> Unfortunately the resulting ground points contain also the first part of
>> of the trunks of the trees, how is it possible?
>>
>> I am doing some testing changing the values of the SMRF parameters but
>> the results are almost the same.
>>
>> Do some of you have experience with such kind of data? Am I missing some
>> operation for filtering? Could you please help me understanding at least
>> where to focus the attention to try to obtain something...
>>
>> Thank you in advance.
>>
>> Silvia
>>
>>
>> --
>> ing. Silvia Franceschi
>> Via Roma, 64
>> 38030 Castello di Fiemme (TN)
>>
>> tel: 0039 -3384501332
>> _______________________________________________
>> pdal mailing list
>> pdal at lists.osgeo.org
>> https://lists.osgeo.org/mailman/listinfo/pdal
>
>

-- 
ing. Silvia Franceschi
Via Roma, 64
38030 Castello di Fiemme (TN)

tel: 0039 -3384501332
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