Fields of The World Global — predicted field boundaries
Machine-learning-predicted field boundaries for 241 countries — the Global edition (India ~20%, Africa ~40% of coverage). Distinct from the curated Benchmark edition.
What this is
FTW publishes two distinct datasets — don't conflate them. The Benchmark edition is ~1.63M curated, human-verified polygons (Europe-heavy, used for model training). The Global edition is ML-predicted field boundaries across 241 countries: India (~20% of coverage), Africa (~40%), and the rest of the world. The Global dataset is what UFFDA serves via PMTiles. Record count: FTW's own documentation reports roughly 8.2 billion rows total across all prediction labels in the Global release; how many of those are field polygons specifically (versus other label types) hasn't been independently confirmed. UFFDA points its map at the published per-year PMTiles (2024 and 2025 epochs), no re-tiling required.
Why we surface it
FTW is what brings the rest of the world into UFFDA's map. Once a place has field boundaries, every layer with global coverage — soil, weather, imagery — has fields to join against.
What you can do with it
Shown for commercial use. Personal, research, and nonprofit use is often more permissive — switch the verdict lens on the catalog.
- Internal / individual use
- Free to use for any purpose, including commercial and AI training. Nothing's triggered until you share it.
- Redistribute the data
- Fine to use and redistribute, including commercially. One string attached: credit the original source wherever it shows up.
- Republish a derivative
- Build on it and republish freely, commercial or not. You must credit the original source in what you ship.
- Build into a private product
- Fine to build into a closed or commercial product. Attribution is still owed wherever the data is actually exposed to users.
This decoder is a starting point, not legal advice. For commercial deployment, run the actual license terms past someone who reads them for a living.
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