This is a small example project for the 3D Powerline Vegetation Risk Analysis video.


Being able to detect Risk areas around power lines in an automated way is a game changer for energy network operators. This Rule Set provides a solution to extract these Risk areas in an automated, accurate and less time consuming way than traditional manual assessment. The idea of this project was to develop a rule set which classifies points of a point cloud into different Risk areas based on the 3D distance to a power line. The whole workflow within eCognition is automated, meaning you only need a point cloud as input and the Rule Set takes care of creating the deliverables, in this case a classified point cloud with Risk classes and the power line detected.

Download Data and Tutorial

Download eCognition Trial version here

Input Data

Unclassified Lidar *.las Point cloud


Classified point cloud into:

  • Powerline
  • Ground
  • Vegetation
    • Risk01 - Pro-Active Fault Clearance - PC#16
    • Risk02 - Branch Removal - PC#17
    • Risk03 - Underlying Vegetation - PC#18
    • Risk04 - Neighboring Forest - PC#19
  • Other vegetation


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