Point cloud classification

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.