
Moisture content is an important indicator for crop water stress condition, timely and effective monitoring crop water content is of great significance for evaluate crop water deficit balance and guide agriculture irrigation. In order to improve the saturated problems of different forms of typical NDWI (Normalized Different Water Index), we tried to introduce EVI (Enhanced Vegetation Index) to build new vegetation water indices (NDWI#) to estimate crop water content. Firstly, PROSAIL model was used to study the saturation sensitivity of NDWI, and NDWI# to canopy water content and LAI (Leaf Area Index). Then, the estimated model and verified model were estimated using the spectral data and moisture data in the field. The result showed that the new indices have significant relationships with canopy water content. In particular, by implementing modified standardized for NDWI1450, NDWI1940, NDWI2500. The result indicated that newly developed indices with visible-infrared and shortwave infrared spectral feature may have greater advantage for estimation winter canopy water content.
Plant Leaves, Spectrum Analysis, Water, Models, Theoretical, Triticum
Plant Leaves, Spectrum Analysis, Water, Models, Theoretical, Triticum
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