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

• Published in: International journal of applied earth observation and geoinformation Vol. 12; no. 5; pp. 351 - 358
• Main Authors: Zhao, Shaohua, Yang, Yonghui, Qiu, Guoyu, Qin, Qiming, Yao, Yunjun, Xiong, Yujiu, Li, Chunqiang
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 01.10.2010; Elsevier
• Subjects: Applied geophysics; Earth sciences; Earth, ocean, space; Energy balance equation; Exact sciences and technology; Internal geophysics; MODIS; Regional maximum temperature; Remote sensing; Far East; Asia; China; Hebei China; Energy balance equation; Regional maximum temperature; Remote sensing; MODIS; experimental studies; models; ground truth; detection; soil moisture; remote sensing; energy balance; air; bare soils; depth; drought; surface temperature; evaporation
• ISSN: 1569-8432; 1872-826X
• DOI: 10.1016/j.jag.2010.04.007

An approach for estimating soil moisture is presented and tested by using surface-temperature-based soil evaporation transfer coefficient (ha), a coefficient recently proposed through the equation ha=(Ts−Ta)/(Tsd−Ta), where Ts, Tsd, and Ta are land surface temperature (LST), reference soil (dry soil without evaporation) surface temperature, and air temperature respectively. Our analysis and controllable experiment indicated that ha closely related to soil moisture, and therefore, a relationship between field soil moisture and ha could be developed for soil moisture estimation. Field experiments were carried out to test the relationship between ha and soil moisture. Time series Aqua-MODIS images were acquired between 11 Sep. 2006 and 1 Nov. 2007. Then, MODIS derived ha 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 ha (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 0.0374cm3/cm3 and 0.0503cm3/cm3 for surface energy balance method at two soil depths (10cm and 20cm), with RMSE of 0.0467cm3/cm3 and 0.0581cm3/cm3 for maximum temperature method at two soil depths. For vegetated surfaces, the ratio of ha and NDVI suggested to be considered. The proposed approach has a great potential for soil moisture and drought evaluation by remote sensing.