A New Leap in Vegetation Optical Depth and Soil Moisture Mapping from Space
Feb 26, 2024
Scientists from the Aerospace Information Research Institute (AIR) with the Chinese Academy of Sciences CAS) have developed a novel technique that leverages the Soil Moisture Active Passive mission data to extract crucial information about soil moisture (SM) and vegetation optical depth (VOD) with unprecedented accuracy.
The study, detailed in the Remote Sensing of Environment, propels the multi-channel collaborative algorithm (MCCA) by introducing a self-calibrating framework to fine-tune algorithm parameters. Information theory metrics are employed to determine the appropriate values for surface roughness and effective scattering albedo. The developed MCCA eliminates the dependency on auxiliary data, making it a more efficient retrieval process.
The study validated the new method in detail against in-situ observations from extensive soil moisture networks, demonstrating its superior accuracy in measuring soil moisture levels, with the unbiased root mean square error about 0.055 m3/m3 and a high overall Pearson's correlation coefficient of 0.744.
Furthermore, the MCCA retrievals show a slight polarization difference of vegetation effects at the satellite scale through polarization-dependent VOD measurements, a step forward not achievable with previous methodologies. Both H-pol and V-pol VOD exhibit a strong linear relationship with above-ground biomass and canopy height, with the polarization difference primarily observed in densely vegetated and arid areas.
The corresponding dataset was published on the National Tibetan Plateau Data Center. This research, alongside a prior study focusing on a two-decade dataset of SM and polarization-dependent VOD from AMSR-E/2 measurements, scientists from AIR have delivered long-term SM and VOD datasets across L, C, X, Ku bands, providing valuable insights into water exchanges at the land-atmosphere interface through microwave radiometry.
For further information, please contact ZHAO Tianjie at zhaotj@aircas.ac.cn.
News & Events