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CSFTools

Tools to processing LiDAR point cloud based on CSF.

CSFTools provides a set of Python based tools, including:

  • csfground.py: to filter a point cloud
  • csfdem.py: a simple gridding and interpolation algorithm to generate a DEM/DSM/CHM
  • csfnormalize.py: normalize point cloud
  • csfclassify.py: use a scalar field to classify the point cloud into 2 classes
  • csflai.py: compute leaf area index (LAI) from airborne discrete-return LiDAR data
  • csfcrown.py: segment tree crowns from CHM

More details, please refer to User Manual.

Installation

This preprocessing tool requires a few python libraries, to make it easier to install, we recommend to use anaconda (python 3.6+), which has already been integrated with a few scientific computing libraries. Other libs:

  • laspy: supporting reading and writing of las file. https://github.com/laspy/laspy run:

     pip install laspy
    

    or download the source and run:

     python setup.py build
     python setup.py install
    
  • GDAL

     conda install gdal
    
  • joblib: supporting parallel computing for python

     pip install joblib
    
  • mahotas: computer vision library, supporting watershed transform, etc.

     conda config --add channels conda-forge
     conda install mahotas
    
  • CSF: ground filtering library, go to: https://github.com/jianboqi/CSF, and download all the source code: Under the folder python, run:

     python setup.py build
     python setup.py install
    

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Tools to processing LiDAR point cloud

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