All work
Machine Learning Engineer
ArborMeta
Byron Bay, NSW · 2025 – present
The geospatial ML platform behind Australian carbon-credit policy advice.
Carbon and ecology data was scattered across field surveys and raw LiDAR. None of it sat in one place a policymaker could actually look at, and none of it answered the question that matters: how much carbon, and is it growing?
- Canopy-height and above-ground-carbon models from paired LiDAR captures, with growth quantified between flights parcel by parcel
- Live fire-spread and ember mapping driven by wind fields
- A multi-LOD PMTiles pipeline that keeps continental-scale datasets fast at every zoom level
- A PostGIS spatial backend, with parsers that pull Fulcrum field surveys straight into the platform
- A map viewer that renders live survey data over satellite imagery
- Used to advise federal and state government on carbon credit rules
- Canopy growth and carbon change measured between repeat LiDAR captures, the numbers under the policy
- Field data from four countries, readable in one live interface
Stack
FastAPIPostGISMapLibre GL JSPMTilesALS / LiDARDockerReact