Overlapping plots

Why does it matter?

Each plot of land should be counted once. Overlaps inflate total area and apparent production capacity, which can let unverified volumes enter a compliant supply chain. They also point to land disputes relevant to the legality requirement.

How is it detected?

Overlap analysis compares every polygon with every other polygon in the dataset, and ideally across datasets from different buyers or programmes. Useful measures include:

• overlap area and percentage of each plot;
• whether overlaps are between the same farmer’s plots (often duplicates) or different farmers;
• clusters of plots overlapping many others.

How is it resolved?

• Duplicates from repeated registration are merged, which links to deduplication of farmer records.
• Boundary errors from GPS accuracy are corrected by snapping shared edges or re-mapping.
• Real disputes are documented and escalated.
• Suspected fraud is investigated before volumes from those plots are accepted.

Common pitfalls

• Checking overlaps only within one company’s data, when the same farmer supplies several buyers.
• Deleting one of two overlapping plots without investigation.
• Ignoring overlaps with protected areas and forest reserves.

Cross-dataset overlap detection is one of the pre-competitive checks in Farmer1st’s fraud detection service.