14 May 2018 Effect of chlorophyll concentration under different water situation and estimation model for Pinuse lliottii Engelm with hyperspectral data
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Abstract
Three treatments (normal soil water condition, CK; continual submergence condition, T1; and submergence and drought alternation condition, T2) are adopted. The reflectance spectra of Pinuse lliottii Engelm leaves, the red edge parameters and the corresponding chlorophyll content are measured, and the relationship between the red edge parameters and total chlorophyll concentration are analyzed. The results show that: (1) There are “blue shift” phenomena before 24d and “red shift” after 24d for the position of λred (Red edge position). The opposite phenomenon occurs for Dλred (Red edge amplitude). The Sred (Red edge area) appear “blue shift” for the case T1 and T2. (2)There is extremely significant correlation between chlorophyll content and red edge position, and there is significant correlation between chlorophyll content and red edge area, but the correlation between chlorophyll content and red edge amplitude is poor. The correlation coefficient between chlorophyll content and red edge position is 0.762. (3)The red edge position, kurtosis and skewness, which are computed by spectral curve at range 680-760nm of Pinuse lliottii Engelmare considered the input variables for artificial neural networks. The correlation coefficient is 0.928, and it obviously improves the accuracy of the estimation of the total chlorophyll concentration.
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Wenmin Li, Wenmin Li, Shuxia Li, Shuxia Li, } "Effect of chlorophyll concentration under different water situation and estimation model for Pinuse lliottii Engelm with hyperspectral data", Proc. SPIE 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics, 1065802 (14 May 2018); doi: 10.1117/12.2309322; https://doi.org/10.1117/12.2309322
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