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I have been using FUSION and the command line FUSION Lidar Toolkit (LTK) to process Lidar data. A broad Google search ("Lidar Python") yielded libLAS and pyLAS as Python lidar libraries, however, these appear to provide only read and write access to LAS data. I am particularly interested in creating intensity and density images in addition to canopy surface models from point clouds. Is there a generally accepted set of tools in Python that can accomplish the same sort of tasks FUSION LTK is capable of?

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It is not a direct answer to your question, but as I've been working on a Python software for the reconstruction of botanical trees from LIDAR-acquired point cloud data, perhaps the technology stack I've been using could give you some ideas. In particular, the visualization layer is built using VTK, which is very powerful. – cjauvin Mar 3 '14 at 20:15
ArcMap 10.1 has ultilities to handle Lidar Datacloud filters for display and analysis with other layers. C++ is probably the best method to handle the data rich .las files as recommended above. – user28345 Mar 21 '14 at 17:18
I don't see how this answer's the OP's question. He wants a tool in Python. If you are suggesting C++, you should back up that claim with a detailed reason. – Devdatta Tengshe Mar 22 '14 at 16:31
up vote 9 down vote accepted

laspy is another good LAS read/write software. It supports working with the data directly in numpy arrays and a number of other nice Pythonic features. It isn't processing software per se, however.

PDAL has the ability to use Python as an in-pipeline filtering language, but this isn't a processing engine either.

There isn't too much in the Python quiver for LiDAR and point cloud processing. I think some of this has to do with the volumes of data typically processed and the typical response to reach for C/C++ when faced with the challenge. I do hope that as Python improves (PyPy is driving lots of things, and it is the reason that I worked to have laspy developed) more Python point cloud processing software becomes available. I think the outlook is improving but things still aren't quite there yet.

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