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LiDAR Notebooks

Collection of tutorials that I wrote to open source the knowledge of processing LiDAR data using Python. The notebooks run on Google Colab, online free IDE with powerful computing resource by Google.

Contents (and planned):

  • Tutorial 01 Read point cloud data, clip with polygon, and visualize
  • Tutorial 02 Create DSM, DTM, and CHM map
  • Tutorial 03 Create aerial photo from point cloud
  • Tutorial 04 Individual tree identification (planned)

PDAL (Point Data Abstraction Library) is a powerful package for complex processing of LiDAR point cloud data in JSON pipeline. I have simplified the workflows so that it is easy to use.

Data used for these tutorials are open-source, such as:

  • Borneo forest LiDAR data acquired by NASA Oak Ridge National Laboratory (ORNL). --> Link <--
  • Autzen stadium released by --> Link <--

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Python notebooks for LiDAR data processing

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