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