🌲 Forest and trees v.2026-09-10 — tree crown benchmark

This page details the validation of tree crown polygons produced by the 🌲 Forest and trees v.2026-09-10 model on 7 areas of interest (AOI), compared against the previous version v.2026-07-03. For each AOI the two crown-mask results are shown side by side; click any image to open it full size, and use the ← / → arrow keys to browse between them.

Metrics are area-based on the crown masks: IoU is the intersection-over-union of the predicted and ground-truth crown masks, and F1 / Precision / Recall are computed on the overlapping mask area. Crowns is the number of detected crown polygons; the ground-truth crown count and the relative count error are reported below each AOI (see also the Tree count accuracy table on the model page). Evaluation run: 2026-10-01.

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Mask colour legend: v.2026-09-10 · v.2026-07-03

Italy — Crotone

Model	IoU	F1	Precision	Recall	Crowns
v.2026-09-10	0.842	0.914	0.930	0.898	254
v.2026-07-03	0.825	0.904	0.925	0.884	254

v.2026-09-10

v.2026-07-03

Argentina — La Banda

Model	IoU	F1	Precision	Recall	Crowns
v.2026-09-10	0.624	0.769	0.700	0.852	111
v.2026-07-03	0.575	0.730	0.691	0.774	83

v.2026-09-10

v.2026-07-03

Spain — Rus

Model	IoU	F1	Precision	Recall	Crowns
v.2026-09-10	0.689	0.816	0.759	0.883	239
v.2026-07-03	0.567	0.723	0.671	0.785	249

v.2026-09-10

v.2026-07-03

Philippines — Balanga

Model	IoU	F1	Precision	Recall	Crowns
v.2026-09-10	0.780	0.876	0.849	0.904	309
v.2026-07-03	0.782	0.878	0.860	0.896	220

v.2026-09-10

v.2026-07-03

Spain — Cuenca

Model	IoU	F1	Precision	Recall	Crowns
v.2026-09-10	0.732	0.846	0.875	0.818	433
v.2026-07-03	0.728	0.842	0.868	0.818	409

v.2026-09-10

v.2026-07-03

Spain — Velilla de San Antonio

Model	IoU	F1	Precision	Recall	Crowns
v.2026-09-10	0.694	0.819	0.855	0.786	1,134
v.2026-07-03	0.667	0.800	0.831	0.771	1,070

v.2026-09-10

v.2026-07-03

Spain — Madrid

Model	IoU	F1	Precision	Recall	Crowns
v.2026-09-10	0.823	0.903	0.907	0.899	398
v.2026-07-03	0.801	0.889	0.879	0.900	368

v.2026-09-10

v.2026-07-03

Summary

For tree crown polygons, v.2026-09-10 improves on v.2026-07-03 across the 7 AOIs: mean area-based F1 rises from 0.824 to 0.849 and IoU from 0.706 to 0.741, with gains in both precision (0.818 → 0.839) and recall (0.833 → 0.863). It leads on F1 in 6 of the 7 AOIs and is on par at Balanga (0.876 vs 0.878).

On tree count accuracy the picture is mixed. We will provide more evidence on the later benchmarks based on results against the validated mapping surveys.