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Biodiversity Credit Mapping

Drone LiDAR & multispectral · Detectron2 / Mask-RCNN · scikit-learn

Biodiversity credit schemes need defensible, per-tree measurements across large sites. Manual field counts could not keep up, so I turned to drone data.

I segmented drone point clouds and multispectral orthomosaics with Detectron2 / Mask-RCNN to isolate individual trees, then modelled tree properties and surface/canopy structure with scikit-learn.

  • Delivered individual-tree delineation instead of coarse plot estimates.
  • Linked canopy models to biodiversity indicators for credit accounting.

Developed while helping a large NGO in Australia with their Australian Carbon Credit Unit (ACCU) work.

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