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hobu merged 2 commits into from
Oct 14, 2025
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Adding DTM creation example to README #196

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Adding DTM creation example to README
kylemann16 Oct 14, 2025
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fix numbered list
kylemann16 Oct 14, 2025
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71 changes: 71 additions & 0 deletions README.rst
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Expand Up @@ -406,6 +406,77 @@ USE-CASE : Take a LiDAR map, create a mesh from the ground points, split into ti
buffer.close()


Digital Terrain Model (DTM) Creation Example
................................................................................

The following is a script sample that can be used to create a DTM from a PDAL-
readable pointcloud.

Method:

#. read point cloud file
#. remove noise
#. clean up invalid values
#. classify ground points using `SMRF <https://pdal.io/en/2.9.2/stages/filters.smrf.html>`__
#. write with `GDAL writer <https://pdal.io/en/2.9.2/stages/writers.gdal.html>`__

.. note:: If your pointcloud already has ground classified, you can skip all but
the reader and writer and achieve the same result.

.. code-block:: python

import pdal

pc_path = 'https://github.com/PDAL/data/raw/refs/heads/main/autzen/autzen.laz'
out_file = 'autzen_dtm.tif'


# read
reader = pdal.Reader.las(pc_path)

# remove noisy points
lownoise_filter = pdal.Filter.range(
limits='Classification![7:7]', tag='lownoise'
)
highnoise_filter = pdal.Filter.range(
limits='Classification![18:]', tag='highnoise'
)

# saving incorrectly labeled returns here, some people want this, some don't
prepare_ground = pdal.Filter.assign(
value=[
'Classification=0',
'ReturnNumber=1 WHERE ReturnNumber < 1',
'NumberOfReturns=1 WHERE NumberOfReturns < 1',
],
tag='prepare_ground_classifier',
)

# classify ground
smrf_classifier = pdal.Filter.smrf(tag='ground_classifier')

# write with gdal, resolution in feet for autzen
gdal_writer = pdal.Writer.gdal(
filename=out_file,
where='Classification == 2',
data_type='float32',
resolution=10,
output_type='idw',
window_size=3,
pdal_metadata=True,
)

# collect pdal stages and execute pipline
pipeline = (
reader
| lownoise_filter
| highnoise_filter
| prepare_ground
| smrf_classifier
| gdal_writer
)
pipeline.execute()


.. _`Numpy`: http://www.numpy.org/
.. _`schema`: http://www.pdal.io/dimensions.html
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