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Estimating winter wheat plant water content using red edge parameters

Remote sensing of plant water content is difficult because the absorption band sensitive to foliar liquid water is also sensitive to the atmospheric vapour. A method using non-water-absorption spectral parameters to evaluate plant water content (PWC) would be valuable. In our experiment, canopy spec...

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Bibliographic Details
Published in:International journal of remote sensing 2004-09, Vol.25 (17), p.3331-3342
Main Authors: Liu, Liangyun, Wang, Jihua, Huang, Wenjiang, Zhao, Chunjiang, Zhang, Bing, Tong, Qingxi
Format: Article
Language:English
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Summary:Remote sensing of plant water content is difficult because the absorption band sensitive to foliar liquid water is also sensitive to the atmospheric vapour. A method using non-water-absorption spectral parameters to evaluate plant water content (PWC) would be valuable. In our experiment, canopy spectra of 48 winter wheat treatments with different varieties, different fertilization and irrigation levels were measured by an ASD FieldSpec FR spectrometer in six different growth stages from erecting stage to milking stage, and the PWCs of the related wheat plant samples were also measured. Significant positive coefficients of correlation were observed between PWC and spectral reflectance in 740-930 nm region in all of the six different growth stages, which indicates that the NIR spectral reflectance increases due to the effect of PWC on the leaf internal structure. This mechanism also affects the red edge spectrum in 680-740 nm region. The spectral reflectance increases more rapidly and the red edge becomes steeper if PWC is higher. The coefficients of correlation between PWC and red edge width, derived from the inverted-Gaussian model, are significant at the 0·999 confidence-level, which is more reliable than WI and NDWI, and the statistical models for PWC based on red edge width were set up in all the six different growth stages. In addition, LAI and canopy chlorophyll density (CCD) are also related to red edge parameter, such as red edge position and red edge width. It seems that PWC plays a more important role in red edge width than LAI and CCD due to the effect of PWC on the leaf internal structure, and that CCD plays a more important role in red edge position than LAI and PWC.
ISSN:0143-1161
1366-5901
DOI:10.1080/01431160310001654365