Determining the dry boundary of the LST/FVC space for soil moisture monitoring: a semi-empirical method

Abstract

ABSTRACTLand surface temperature and fractional vegetation coverage (LST/FVC) space is a classical model for monitoring soil moisture (SMC) from optical/thermal remote sensing. However, its applications are critically constrained by the determination of the dry and wet boundaries. In this study, a semi-empirical method was provided for determining the dry boundary by introducing a parallel resistance following the Biome-BGC (BioGeochemical Cycles) model to determine the temperature endmembers on the dry boundary. The semi-empirical method was evaluated by comparing with typical theoretical calculation methods in calculating soil moisture index (SMI) based on the LST/FVC space. Public datasets from SMAPVEX12 (Soil Moisture Active Passive mission Validation Experiment 2012) experiment, MODIS (Moderate Resolution Imaging Spectroradiometer), and NLDAS-2 (North American Land Data Assimilation System) Forcing Dataset were utilized in the evaluation. Results demonstrated that the semi-empirical method has comparable performances with the theoretical methods in monitoring the spatial variation of SMC. The SMIs based on the semi-empirical and theoretical methods are significantly correlated at a high level of Pearson’s correlation coefficients (r) around 0.8–0.9 with p-value = 0.05. More importantly, this semi-empirical method requires fewer parameters and does not require a complex iteration calculating process as compared with previous theoretical methods.