Xiao, Lujie; Feng, Meichen; Yang, Wude; Ding, Guangwei (2015). Estimation of Water Content in Winter Wheat (Triticum aestivum L.) and Soil Based on Remote Sensing Data-Vegetation Index. COMMUNICATIONS IN SOIL SCIENCE AND PLANT ANALYSIS, 46(14), 1827-1839.

Abstract
In this study, a suitable and near-real-time water status monitoring approach for winter wheat before harvest was developed with remotely sensed satellite data. Seven vegetation indices were extracted as remote-sensing parameters by making full use of the land surface reflection and land surface temperature transmitted by moderate resolution imaging spectroradiometer (MODIS) data. The correlation of each vegetation index and measured values of winter wheat and soil water contents in different crop growth periods was established. The simulation models, combining vegetation index, soil water content (SWC), and plant water content (PWC) in different winter wheat growth periods, were constructed to predict water content by using remote-sensing data. We found that the correlations between the difference vegetation index (DVI) and the perpendicular vegetation index (PVI) in the beginning of the stem elongation period with SWC were highly significant (P<0.01); the correlation between the global environmental monitoring index (GEMI) in the ear emergency period and SWC was highly significant (P<0.01). Furthermore, the correlation between the PVI in maturing period and SWC was highly significant (P<0.01). Data of different coefficients of vegetation indices and PWC in different winter wheat growth periods illustrated that correlation between the DVI in the beginning of stem elongation period and PWC was highly significant (P<0.01), while the correlation between the PVI in the maturing period and PWC was highly significant. Our results indicated that spatial and temporal vegetation indices were closely related to soil moisture and winter wheat water content in Wenxi County, Shanxi Province (P. R. China). The vegetation index is conceptually and computationally straightforward and may be used in prediction of environmental hydrological status.

DOI:
10.1080/00103624.2015.1059844

ISSN:
24-Oct