GAMMA REMOTE SENSING AG (CH)
Characterization of forest biogeochemical cycles is of paramount importance in Earth system science to understand contemporaneous dynamics and for expanding global land models in order to predict future trends of vegetation and climate. Thanks to the increasing amount of spaceborne observations of land and ocean surfaces, data-driven models are revealing intriguing trends and mechanisms and model evaluation exercises are reaching global insights into temporal dynamics, which would not be achievable otherwise. The global characterization and the accurate knowledge of terrestrial carbon pools have been acknowledged as a fundamental variable for driving research in the terrestrial component of Earth system models. Traditionally, carbon pools are best estimated from measurements of forest inventories. However, these estimates are sparse in time and sometimes only locally relevant. There is therefore a strong requirement for data collection approaches that expand these spatial-temporal representativeness limits. However to date, despite the long term records of observations from space, only one dataset of biomass extended over multiple years so far – a 10 year passive microwave data. This project is developing a more comprenensive approach to the inforamtion gap by combining SAR and scatterometer data collected since the early 1990s to estiamte biomass properties. As the spatial resolution of both sensors is consistent with the range of length scales typcially used within ecosystem models it is expected that this development will provide a unique contribution to improving ecosystem modelling and assessment.