|Paper title||An evaluation of the synergy of satellite passive and active microwave observations between 1.4 and 36 GHz, for vegetation characterization over the Tropics|
|Form of presentation||Poster|
Passive microwave observations from 1.4 to 36 GHz already showed sensitivity to vegetation parameters, primarily through the calculations of the Vegetation Optical Depth (VOD) at individual window frequencies, separately. Here we evaluate the synergy of this frequency range for vegetation characterization over Tropical forest, through the estimation of two vegetation parameters, its foliage and the photosynthesis activity as described by the Normalized Difference Vegetation Index (NDVI), and its woody components and carbon stock as described by the Above Ground Carbon (AGC), using different combinations of channels in the considered frequency range. Neural network retrievals are trained on these two vegetation parameters (NDVI and AGC), for several microwave channel combinations, including the future Copernicus Imaging Microwave Radiometer (CIMR) that will observe simultaneously in window channels from 1.4 to 36 GHz, for the first time. This methodology avoids the use of any assumptions in the complex interaction between the surface (vegetation and soil) and the radiation, as well as any ancillary observations, to propose a genuine and objective evaluation of the information content of the passive microwave frequencies for vegetation characterization. Our analysis quantifies the synergy of the microwave frequencies from 1.4 to 36 GHz. For the retrieval of NDVI, the coefficient of determination R2 between retrieved and true NDVI reaches 0.84 when using the full 1.4 to 36 GHz range as will be measured by CIMR, with a retrieval error of 0.07. For the retrieval of AGC, the coefficient of determination R2 reaches 0.82 with CIMR, with an error of 21 Mg/ha. This study also confirmed that 1.4 GHz observations have the highest sensitivity to AGC, as compared to other frequencies up to 36 GHz, at least under tropical environments.
CIMR will provide valuable ecological indicators to enhance our present global vegetation understanding. Considering both vegetation aspects together (foliage photosynthesis activity and carbon stocks) offers a more robust and consistent characterization and assessment of long-term vegetation dynamics at large scale. CIMR will operate in synergy with MetOp-SG that carries the ASCAT scatterometer at 5.2 GHz. The complementarity between CIMR and the active microwave observations from ASCAT will also be evaluated, over Tropical forests, for vegetation characterization.