This study aims at developing appropriate methods for soil water stress detection in arid regions in Ugan-Kuqa River Delta Oasis by the images of Landsat 8. To do this, we use NDVI combined with Vegetation Water Index (VWIs) and surface temperature (Ts) to construct Vegetation Dryness Index (VDI) and Temperature Vegetation Drought Index (TVDI) respectively. At the same time, a modified approach towards the TVDI incorporating air temperature (Ta) and a DEM to develop the improved Temperature Vegetation Drought Index (iTVDI), which taking into account the impact of topography and cover types. The three algorithms were applied to retrieve the spatial and temporal distribution of water stress. Then, the same period field surface soil moisture data were used for verification and evaluation. The results show that the three algorithms to some extent, all can objectively reflect the dryness characteristics and all have negative correlation of soil moisture. While iTVDI has best correlation, TVDI followed, VDI has minimum correlation. In addition, all R2 values in April were lower than values in August, it is concluded that compared with growing season, the three algorithms were more suitable for the grown season water stress/drought detection.
Wang Jiao
,
Ding Jianli
,
Yuan Ze
,
Chen Wenqian
,
Li Xiang
,
Huang Shuai
. Improvement and Comparison of Soil moisture Monitoring Algorithm in Oasis Based on Ts-NDVI Feature Space[J]. Journal of Desert Research, 2016
, 36(6)
: 1606
-1612
.
DOI: 10.7522/j.issn.1000-694X.2015.00165
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