Sub-pixel mapping of annual tree and standing deadwood cover from Sentinel-2 time series across the globe

Clemens Mosig , Teja Kattenborn, David Montero Loaiza, Janusch Vanja-Jehle, John Brandt, Nathan Jacobs, Subash Khanal, Eric Xing, Martin Schwartz, Helene C. Muller-Landau, Mirela Beloiu, Aurora Bozzini, Yan Cheng, Keenan Ganz , Björn Grüning, Henrik Hartmann, Jan Hempel, Stéphanie Horion, Samuli Junttila, Kirill Korznikov, Guido Kraemer, Milena Mönks, Davide Nardi, Paul Neumeier, Jonathan Schmid, Salim Soltani, Marie Therese-Schmehl, Josh Veitch-Michaelis, Miguel Mahecha

Elevated forest disturbances and excess tree mortality are increasingly reported worldwide. Yet existing assessments are either based on patchy terrestrial observations or on large-scale satellite products, which are limited in resolution to pixel-level, binary tree loss detection. This leaves a blind spot on fine-scale disturbances where only a few trees are declining in an otherwise intact canopy. Here, we develop and validate a model that annually retrieves sub-pixel fractional cover of standing deadwood and trees from rolling four-year windows of Sentinel-2 time series. Fractional cover is the proportion of each pixel covered by dead or live tree crowns. To obtain globally distributed sub-pixel reference labels, we leveraged the crowd-sourced archive deadtrees.earth of centimeter-scale drone orthophotos with two globally calibrated semantic segmentation models to derive tree and standing deadwood masks, yielding 11.1 million labeled Sentinel-2 pixels. Spatial block cross-validation yields Pearson’s r = 0.64–0.68 for tree cover across biomes, and Pearson’s r = 0.24–0.51 for standing deadwood cover. Evaluated on identical cells, our fractional tree cover agrees more closely with the drone reference than the Global 30 m Landsat Tree Canopy Cover and Copernicus Tree Cover Density products (weighted r = 0.73 versus 0.40 at 30 m, and 0.68 versus 0.38 at 10 m). Our method provides the missing link between fine-scale ground observations and low-resolution remote sensing products, allowing more realistic estimates of global trends in forest disturbance and tree mortality.