High-resolution soil moisture estimates using C- And L-band active passive observations and the TheX-MEX’15 dataset

Continuous monitoring of physical parameters such as soil moisture (SM) is crucial to improve food sustainability and risks mitigation. Because of the spatio-temporal variations in SM, satellite observations are an excellent tool to monitor its dynamic. Among different operational satellite missions, the NASA SMAP mission offers a unique opportunity to monitor SM worldwide thanks to its frequency band of operation (L-band). The main goal of this mission was the disaggregation of brightness temperature (T_B) at 36 km to 9km using backscatter images at 3 km. Although the SMAP mission was designed to collect simultaneously radar/radiometer observations, due to a failure in the radar in July 2015, only the radiometer continues working. Among different options to compensate the lack of information from the L-band radar, the exploitation of C-band active information with L-band passive observations to disaggregate T_B and produce SM at fine resolution has been proposed. Recently, the NASA SMAP team delivered a new SM product using this approach. However, this new product has not been validated over forested areas yet. In this work, we present the results of implementing a disaggregation algorithm based on the baseline SMAP downscaling approach over a tropical forest located in Southern Mexico, using information from the SMAP radiometer and Sentinel-1 images.