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Wide Area Mapping

Geospatial AI model for automatic classification of LiDAR point clouds

As part of Flai, we offer pre-trained AI models for common categories and problems, such as wide-area mapping projects, power lines mapping, infrastructure mapping, mobile mapping or others.


All models can be easily extended and retrained (AI learning point) for your specific needs by yourself or by our experts.


The geospatial AI (geoAI) model contains the following categories:

  • ground,

  • vegetation (low, mid, high),

  • buildings,

  • low isolated noise,

  • high isolated noise,

  • water,

  • bridges,

  • powerline wires - separated low and high voltage,

  • powerline towers - separated low and high voltage,

  • railroad wires

  • railroad towers

  • building facades,

  • vehicles,

  • linear walls,

  • objects on building roofs,

  • points below the ground,

  • other man-made structures.



Luka Kocijančič, Project manager at Flycom Technologies shared the following insights regarding Flai's wide area mapping:

​With use of Flai's state-of-the-art AI for automatic classification of LiDAR point clouds we have reduced cost and complexity of data processing.

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