Publications

Sun, H; Cai, CC; Liu, HX; Yang, B (2019). Microwave and Meteorological Fusion: A method of Spatial Downscaling of Remotely Sensed Soil Moisture. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 12(4), 1107-1119.

Abstract
Downscaling of microwave remotely sensed that soil moisture content (SMC) is an efficient way to obtain spatial continuous SMC at a finer resolution. However, the classical optical/thermal and microwave fusion, and the active and passive microwave fusion cannot work under all-weather conditions because of contamination of clouds or the lack of suitable radar data source. In this study, a microwave and meteorological fusion (MMF) is provided. The MMF method is based on a complementary relationship hypothesis assuming SMC is reflected in the adjacent surface atmospheric moisture under midday conditions. By this method, daily passive SMC products from Soil Moisture Active Passive (SMAP) mission with 36-km resolution were disaggregated using a daily gridded meteorological data with nominal 4-km resolution. The original and downscaled SMCs were evaluated by comparing with in situ SMC obtained from three core validation sites and three sparse networks. The experiment was conducted in the central part of the U.S. from April 2015 to June 2018. Results demonstrated that the downscaled SMC maintained the dynamic range of original SMC product and energy was conserved. Furthermore, the downscaled SMC showed good agreement with and slightly outperformed the original SMC as compared with in situ SMC. The downscaling method is shown to capture higher resolution SMC spatial variability while preserving the quality of original SMC. However, because of the complexity of soil moisture-atmosphere interactions, the actual contributing domain of downscaled SMC may be greater than 4 km. The MMF method is suggested as a supplementary for all-weather downscaling coarse-resolution SMC.

DOI:
10.1109/JSTARS.2019.2901921

ISSN:
1939-1404