Publications

Zhang Feng; Zhang Li-Wen; Shi Jing-Jing; Huang Jing-Feng (2014). Soil Moisture Monitoring Based on Land Surface Temperature-Vegetation Index Space Derived from MODIS Data. PEDOSPHERE, 24(4), 450-460.

Abstract
Soil moisture has been considered as one of the main indicators that are widely used in the fields of hydrology, climate, ecology and others. The land surface temperature-vegetation index (LST-VI) space has comprehensive information of the sensor from the visible to thermal infrared band and can well reflect the regional soil moisture conditions. In this study, 9 pairs of moderate-resolution imaging spectroradiometer (MODIS) products (MODO9A1 and MOD11A2), covering 5 provinces in Southwest China, were chosen to construct the LST-VI space, and then the spatial distribution of soil moisture in 5 provinces of Southwest China was monitored by the temperature vegetation dryness index (TVDI). Three LST-VI spaces were constructed by normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and modified soil-adjusted vegetation index (MSAVI), respectively. The correlations between the soil moisture data from 98 sites and the 3 TVDIs calculated by LST-NDVI, LST-EVI and LST-MSAVI, respectively, were analyzed. The results showed that TVDI was a useful parameter for soil surface moisture conditions. The TVDI calculated from the LST-EVI space (TVDIE) revealed a better correlation with soil moisture than those calculated from the LST-NDVI and LST-MSAVI spaces. From the different stages of the TVDIE space, it is concluded that TVDIE can effectively show the temporal and spatial differences of soil moisture, and is an effective approach to monitor soil moisture condition.

DOI:

ISSN:
1002-0160; 2210-5107