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Estimating soil moisture using Temperature-Vegetation Dryness Index (TVDI) in the Huang-huai-hai (HHH) plain.

Authors :
Chen, Jian
Wang, Chunzhi
Jiang, Hong
Mao, Liuxi
Yu, Zhenrong
Source :
International Journal of Remote Sensing. 2/20/2011, Vol. 32 Issue 4, p1165-1177. 13p. 1 Diagram, 2 Charts, 2 Graphs, 3 Maps.
Publication Year :
2011

Abstract

Soil moisture is an important indicator to describe soil conditions, and can also provide information on crop water stress and yield estimation. The combination of vegetation index (VI) and land surface temperature (LST) can provide useful information on estimation soil moisture status at regional scale. In this paper, the Huang-huai-hai (HHH) plain, an important food production area in China was selected as the study area. The potential of Temperature-Vegetation Dryness Index (TVDI) from Moderate Resolution Imaging Spectroradiometer (MODIS) data in assessing soil moisture was investigated in this region. The 16-day composite MODIS Vegetation Index product (MOD13A2) and 8-day composite MODIS temperature product (MOD11A2) were used to calculate the TVDI. Correlation and regression analysis was carried out to relate the TVDI against in-situ soil moisture measurements data during the main growth stages of winter wheat/summer maize. The results show that a significantly negative relationship exists between the TVDI and in-situ measurements at different soil depths, but the relationship at 10-20 cm depth (R2 = 0.43) is the closest. The spatial and temporal patterns in the TVDI were also analysed. The temporal evolution of the retrieved soil moisture was consistent with crop phenological development, and the spatial distribution of retrieved soil moisture accorded with the distribution of precipitation during the whole crop growing seasons. The TVDI index was shown to be feasible for monitoring the surface soil moisture dynamically during the crop growing seasons in the HHH plain. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01431161
Volume :
32
Issue :
4
Database :
Academic Search Index
Journal :
International Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
59131904
Full Text :
https://doi.org/10.1080/01431160903527421