Determination of all-sky surface soil moisture at fine spatial resolution synergistically using optical/thermal infrared and microwave measurements

Abstract

Soil moisture (SM) is highly involved in a number of fundamental agricultural activities and hydrological processes. Currently, most of the available microwave SM products are too coarse to be used in these relevant applications at regional or watershed scales, whereas optical/thermal infrared measurements are valid over clear-sky conditions only. The present study aims to provide a novel framework for the retrieval of all-sky surface SM at fine spatial resolution synergistically using optical/thermal infrared and microwave measurements. In this framework, SM for each clear-sky pixel is determined from a novel pixel-to-pixel scheme of land surface temperature-vegetation index (Ts-VI) trapezoid, whereas cloudy pixel SM is derived from coarse microwave-based product disaggregation where gridded meteorological measurements are provided as inputs. Mainland China is selected as the study area to obtain all-sky SM at the spatial resolution of 0.05° over the period from August to October in 2017. A preliminary comparison of the estimated all-sky SM with the China Meteorological Administration Land Data Assimilation System (CLDAS)-derived SM product at the same spatial resolution is conducted to assess the proposed approach. Results indicate that the two datasets show similar spatial patterns throughout mainland China. Moreover, the estimated SM over 300 random pixels correlates well with the CLDAS product, with RMSE ranging from 0.070 to 0.083 m3/m3 and a slight bias varying from −0.001 to 0.011 m3/m3 on six selected days. The present study therefore successfully provides a framework for the retrieval of all-sky SM content from currently available satellite products.