Abstract
Soil water content (SWC) is a crucial variable in the thermal infrared research and is the major control for land surface hydrological processes at the watershed scale. Estimating the surface SWC from remotely sensed data using the triangle method proposed by Price has been demonstrated in previous studies. In this study, a new soil moisture index (Temperature Rising Rate Vegetation Dryness Index—TRRVDI) is proposed based on a triangle constructed using the mid-morning land surface temperature (LST) rising rate and the vegetation index to estimate the regional SWC. The temperature at the dry edge of the triangle is determined by the surface energy balance principle. The temperature at the wet edge is assumed to be equal to the air temperature. The mid-morning land surface temperature rising rate is calculated using Meteosat Second Generation—Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) LST products over 4 cloud-free days (day of year: 206, 211, 212, 242) in 2007. The developed TRRVDI is validated by in situ measurements from 19 meteorological stations in Spain. The results indicate that the coefficient of determination (R2) between the TRRVDI derived using the theoretical limiting edges and the in situ SWC measurements is greater than that derived using the observed limiting edges. The R2 values are 0.46 and 0.32; respectively (p < 0.05). Additionally, the TRRVDI is much better than the soil moisture index that was developed using one-time LST and fractional vegetation cover (FVC) with the theoretically determined limiting edges.
Highlights
Soil water content (SWC) is an important parameter in the study of hydrology, meteorology, agriculture management and global climate change [1,2,3,4,5,6,7,8,9]
The results demonstrated that TDX can be used to monitor soil moisture variation and that it is suitable for monitoring the regional surface soil moisture and temporal variation [46]
Surface soil water content is of great importance in closing hydrologic budgets, assessing soil plant water interactions and studying climate change
Summary
Soil water content (SWC) is an important parameter in the study of hydrology, meteorology, agriculture management and global climate change [1,2,3,4,5,6,7,8,9]. It influences energy partitioning between sensible and latent heat fluxes, and the exchange of water and energy fluxes between the land surface and the atmosphere [9]. Microwave remote sensing estimates the SWC using a passive radiometer or the relationship between the SWC and the backscattering coefficients from radar [24,25,26,27,28]
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