全球变化知识资源中心

Surface soil moisture (SSM) is one of the key parameters in the study of global climate change, water, and energy exchanges at both the land surface and atmospheric interface and drought and acidification measure. The temperature vegetation dryness index (TVDI) is an effective index from optical remote sensing imagery to monitor regional surface soil moisture status. Due to the disturbance of multiple factors, the coefficients of determination (R-2) of the dry and wet edge of the surface temperature - normalized difference vegetation index (-NDVI) feature space of the traditional TVDI method are quite low and unstable in karst area. Therefore, this article developed an improved -NDVI feature space by conducting elevation correction to the land surface temperature () to monitor soil moisture in the karst area of Guangxi, China. After digital elevation model (DEM) correction, the coefficients of determination of the wet edge were improved obviously. The drought distribution of Guangxi in spring and autumn of 2009 were analysed using the modified -NDVI space of the TVDI method (MTVDI) and verified by the in situ data. The results showed that the MTVDI can reasonably reflect the distribution of soil moisture in the study area, and the drought expression is in line with the in situ data and the actual situation.