Near Real-Time Soil Moisture in China Retrieved From CyGNSS Reflectivity

This work presents a novel scheme to retrieve soil moisture (SM) from the Cyclone Global Navigation Satellite System (CyGNSS) data, which is accomplished by using a bagged regression trees (BRT) algorithm with the inputs being the CyGNSS-derived products, the corresponding geolocation, and associated climate type. This algorithm is validated with the in situ hourly SM data acquired by Chinax2019;s automatic SM observation stations throughout the year 2018. High consistency between the retrieved SM results and the measured SM is achieved, with a correlation coefficient of 0.86 and a root-mean-square error of 0.05 cm(3)/cm(3). The results obtained in this work indicate that the proposed BRT-based method can effectively estimate SM from CyGNSS data in different scenarios of various station locations and climate types in a near real-time manner.