Point cloud classification

Automatic classification of LiDAR point clouds

Perform semantic segmentation (classification) of LiDAR point clouds using AI models.


You can choose between three pre-trained AI models derived from semantic segmentation datasets that are continuously labelled by a team of experts in the geospatial and forestry domain.

Depending on the selected geospatial AI (geoAI) model, the following categories are available:

  • Ground,

  • vegetation (low, mid, high),

  • buildings,

  • bridges,

  • other man made objects,

  • low points,

  • noise,

  • water.

  • powerlines (coming soon),

  • powerline towers (coming soon),

  • facades (coming soon),

  • roofs (coming soon),

  • roof objects (coming soon).


The following classes can be extracted using the forestry AI model:

  • Ground,

  • tree stems,

  • canopies,

  • deadwood,

  • understory.

If you notice areas where the AI model does not perform optimally, use Tools for manual annotation directly on Flai's cloud based machine learning platform.

Annotation-as-a-service is available if you would like us to do data labelling and annotation services to improve the quality and applicability of the AI model.

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