Conference Agenda

Satellite imagery acquired in the last decade have substantially improved the knowledge of the spatial distribution of aboveground biomass (AGB) worldwide. Wall-to-wall maps of AGB impact downstream activities related to climate and vegetation modelling, national inventories and policy making. The start of operations of the BIOMASS satellite provides a novel data stream that in principle shall further improve the estimation of AGB from space. At the early stage of the mission, data from the Cal/Val phase are relevant to understand the contribution of BIOMASS to the quantification of AGB from space. Here, we intend to relate the Cal/Val datasets released by ESA to the set of predictors used by the Climate Change Initiative (CCI) Biomass retrieval algorithm, i.e., multi-temporal Sentinel-1 and ALOS-2 PALSAR-2 radar backscatter images and canopy height from the ICESat-2 LiDAR mission. Our scope is to assess similarities and differences between these data streams and understand the signatures the BIOMASS data. Ultimately, our goal is to assess how BIOMASS data can contribute to large-scale estimates of AGB within the context of the CCI Biomass framework. This work relies on the database of satellite observations gathered in CCI Biomass, which is updated regularly with the newest observations. A second objective of our study is to relate the BIOMASS data to CCI Biomass estimates of AGB. This is a purely explorative approach aimed at flagging potential caveats of the CCI Biomass dataset (e.g., due to lack of sensitivity of the C- and L-band predictors to biomass) and the BIOMASS data (e.g., due to ionosphere, geolocation accuracy, pre-processing etc.). This work is undertaken as part of ESA’s CCI Biomass project and EU’s NextGenCarbon project.