This layer classifies forest canopy dynamics between 2000 and 2025 into a 7-class stable/loss/gain scheme crossed with canopy height bins, at 30 m resolution. It is the extended-epoch variant that approximates the GLCLUC scheme by combining Hansen Global Forest Change v1.13 (University of Maryland / GLAD) loss and tree-cover bands with the 2020 ETH Global Canopy Height snapshot (Lang et al., 2023). Green tones mark stable canopy (in three height bins), pink tones mark height loss, and purple tones mark height gain; unforested and no-data pixels are masked.
The layer reproduces the 7-class GLCLUC stable/loss/gain classification over an extended time window (2000-2025) for which no pre-baked product exists (the upstream GLCLUC v1 product only covers 2000-2020). It fuses the Hansen Global Forest Change v1.13 multi-band asset (tree cover 2000, loss, gain, data mask) with the 2020 ETH Global Canopy Height snapshot to assign each forested pixel a class combining its change status and its canopy height bin.
| Code | Provider | Resolution | Year |
|---|---|---|---|
| UMD/hansen/global_forest_change_2025_v1_13 | University of Maryland / GLAD | 30 m | 2000-2025 |
| ETH Global Canopy Height (Lang et al.) | ETH Zürich | 10 m (aggregated to 30 m) | 2020 |
The ETH canopy height (native 10 m) is aggregated to the Hansen 30 m Web Mercator grid via reduceResolution (mean). Each pixel is then classified per-pixel into stable, loss or gain from the Hansen loss and tree-cover bands, and split by canopy-height bin (5-10 m, 10-20 m, 20+ m for stable; 5-10 m and 10+ m for loss and gain), yielding the 7 classes plus a masked no-forest/no-data value. Because the height snapshot is dated 2020, canopy height at loss time is accurate for recent losses and approximate for earlier ones.