Aim
Estimating the current spatial variation of biomass in the Amazon rain forest is a challenge and remains a source of substantial uncertainty in the assessment of the global carbon cycle. Precise estimates need to consider small-scale variations of forest structures resulting from local disturbances, on the one hand, and require large-scale information on the state of the forest that can be detected by remote sensing, on the other hand. In this study, we introduce a novel method that links a forest gap model and a canopy height map to derive the biomass distribution of the Amazon rain forest.