

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.