부산대학교 도서관

ESA BIOMASS will be the first spaceborne P-band SAR, and is designed to produce annual, near-global maps of forest biomass. Biomass-independent scene properties can be mitigated by interferometric pre-processing of the acquisitions, after which backscatter is inverted by a model to estimate biomass, relying on some external reference biomass. The model is simple enough to be invertible, while still representing the spatiotemporal variability of parameters in a global scenario. However, it requires a reliable, global reference biomass dataset, with enough coverage to reflect the variability of the chosen model. The global algorithm is also computationally efficient, so can be deployed in the ground segment. In this paper we briefly discuss the design of the global estimation algorithm for BIOMASS and propose a reference biomass dataset for the algorithm. Then, we discuss the robustness of the proposed algorithm using some reference biomass data for three different parameter variability setups.