Principal Investigator Dara Entekhabi
Project Website http://watercycle.mit.edu/index_files/SMAP.htm
The project task is to develop and test satellite multi-pass estimation and retrieval models for surface soil moisture to support the forthcoming SMAP satellite mission. SMAP will use low frequency microwave sensors to map global fields of high-resolution radar backscatter and coarse-resolution but highly accurate radiobrightness simultaneously. An optimal soil moisture data product will have to merge low-resolution but high-accuracy radiometer data with high-resolution but low-sensitivity radar data to produce an intermediate resolution soil moisture data set. The approach will have to use time-series of radar backscatter change in the process. The project task is to develop and test a robust and simple algorithm to merge L-band radiometer retrievals and L-band radar observations to obtain high resolution (9 km) soil moisture estimates for the upcoming SMAP mission. The algorithm exploits the accuracy of radiometer retrievals and blends it to the fine scale spatial heterogeneity detected by radar measurements to produce a high resolution optimal soil moisture estimate at 9 km. The capability of the algorithm should be demonstrated with observing system simulation data (SMAP Algorithm Testbed) as well as airborne field experiment data. A key task is to find and use relationships between the radar and radiometer measurements as a function of vegetation cover.