1. AN ASSESSMENT OF SURFACE SOIL MOISTURE BASED ON IN SITU OBSERVATIONS AND LANDSAT 8 REMOTE SENSING DATA.
- Author
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Chunya Ma, Jinglei Wang, Zhen Chen, Zhifang Chen, ZhanDong Liu, and Xiuqiao Huang
- Abstract
In this study, we derived regional soil moisture (SM) using the latest Landsat 8 image and in situ soil moisture observations at the People's Victory Irrigation District, China. Landsat 8 image was used to construct the temperature-vegetation-dryness-index (TVDI), which integrates the vegetation index (VI) and land surface temperature (LST) to reflect the regional soil moisture conditions. The normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and modified soil adjusted vegetation index (MSAVI) were used in this study to construct the LST-VI feature space. The correlations between the in situ soil moisture observations and the three TVDIs calculated via the LST-NDVI, LSTEVI, and LST-MSAVI were analyzed. The results indicated that the three TVDIs had a negative correlation with the soil moisture. Then the effective depth of the surface soil moisture was analyzed and found that the soil moisture at a depth of 0-200 mm had a stronger correlation with the TVDIs than the other depths. Finally, the retrieval models were verified by using the remote sensing and in situ soil moisture data on another day. [ABSTRACT FROM AUTHOR]
- Published
- 2018