Remote detection of bare soil moisture using a surface-temperature-based soil evaporation transfer coefficient

An approach for estimating soil moisture is presented and tested by using surface-temperature-based soil evaporation transfer coefficient (h_a), a coefficient recently proposed through the equation h_a = (T_s − T_a)/(T_sd − T_a), where T_s, T_sd, and T_a are land surface temperature (LST), reference soil (dry soil without evaporation) surface temperature, and air temperature respectively. Our analysis and controllable experiment indicated that h_a closely related to soil moisture, and therefore, a relationship between field soil moisture and h_a could be developed for soil moisture estimation. Field experiments were carried out to test the relationship between h_a and soil moisture. Time series Aqua-MODIS images were acquired between 11 Sep. 2006 and 1 Nov. 2007. Then, MODIS derived h_a and simultaneous measured soil moisture for different soil depths were used to establish the relations between the two variables. Results showed that there was a logarithmic relationship between soil moisture and h_a (P < 0.01). These logarithmic models were further validated by introducing another ground-truth data gathered from 46 meteorological stations in Hebei Province. Good agreement was observed between the measured and estimated soil moisture with RMSE of 0.0374 cm³/cm³ and 0.0503 cm³/cm³ for surface energy balance method at two soil depths (10 cm and 20 cm), with RMSE of 0.0467 cm³/cm³ and 0.0581 cm³/cm³ for maximum temperature method at two soil depths. For vegetated surfaces, the ratio of h_a and NDVI suggested to be considered. The proposed approach has a great potential for soil moisture and drought evaluation by remote sensing.