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Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
ISBN: 978-0-7695-3507-4
pp: 1-5
The concentration of foliar photosynthetic pigments has considerable significance for vegetation – environment interactions, ecosystem functioning and its status. By decomposing canopy spectra with different mother wavelets, the study focused upon generating accurate predictions of photosynthetic pigment concentrations in Festuca arundinacea, despite wide variations in the range of other biochemical and biophysical factors that influence canopy reflectance. Compared with the traditional method, the outperformed resultant wavelet coefficients could be used to generate model based on transformed spectra, and the new model had the highest linear regression coefficient. Using the wavelet-selected variants and pigment concentration data, the developed regression model could rapidly predict the vegetation status and it’s photosynthetic pigment concentration. The results indicated that wavelet analysis held promise for the accurate determination of chlorophyll a and b and the carotenoids.
Chlorophyll, regression model, Wavelet Packet Decomposition (WPD)
Qian Yurong, Li Jianlong, Yang Feng, Gan Xiaoyu, Yang Qi, "Retrieval of Photosynthetic Pigment Concentration in Festuca arundinacea from Canopy-Scale Reflectance Spectra Using Wavelet Analysis", Computer Science and Information Engineering, World Congress on, vol. 04, no. , pp. 1-5, 2009, doi:10.1109/CSIE.2009.31
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