Improved spatial resolution in soil moisture retrieval at arid mining area using apparent thermal inertia
(1. State Key Laboratory for GeoMechanics and Deep Underground Engineering,
China University of Mining and Technology, Xuzhou 221116, China;
2. Department of Civil Engineering, University of North Carolina at Charlotte, Charlotte, 28223, USA;
3. School of Environment Sciences and Spatial Informatics,
China University of Mining and Technology, Xuzhou 221116, China)
China University of Mining and Technology, Xuzhou 221116, China;
2. Department of Civil Engineering, University of North Carolina at Charlotte, Charlotte, 28223, USA;
3. School of Environment Sciences and Spatial Informatics,
China University of Mining and Technology, Xuzhou 221116, China)
Abstract: A surface soil moisture model with improved spatial resolution was developed using remotely sensed apparent thermal inertia (ATI). The model integrates the surface temperature derived from TM/ETM+ image and the mean surface temperature from MODIS images to improve the spatial resolution of soil temperature difference based on the heat conduction equation, which is necessary to calculate the ATI. Consequently, the spatial resolution of ATI and SMC can be enhanced from 1 km to 120 m (TM) or 60 m (ETM+). Moreover, the enhanced ATI has a much stronger correlation coefficient (R2) with SMC (0.789) than the surface reflectance (0.108) or the ATI derived only from MODIS images (0.264). Based on the regression statistics of the field SMC measurement and enhanced ATI, a linear regression model with an RMS error of 1.90% was found.
Key words: soil water content; soil temperature difference; thermal inertia; remote sensing; spatial resolution