Chlorophyll Concentration Estimation Model Based on Canopy Spectra of Spartina Anglica
【摘要】：Spartina Anglica has been widely used to protect tidal flat and clarify water quality, and studying its spectral reflectance characteristics would be helpful to understand its nutritional status, which usually help to improve and promote the halophyte's cultivation and protection. A total of 8 sample sites in the tidal flat, Lianyungang, had been selected to test their canopy reflectance spectra of Spartina anglica by using ASD FieldSpec HandHeld spectrometer, and the concentration of chlorophyll a, b of each sample's leaves, stems and the mixture of leaves and stems were extracted by acetone method in laboratory. Thereafter the correlation was analyzed between the corresponding chlorophyll concentration and spectral reflectance parameters, namely red edge position (REP), red edge slope, red edge area, yellow edge, blue edge, leaf chlorophyll index(LCI) and water index(WI), and the univariate and multivariate estimation models of chlorophyll concentration were also established based on the spectral reflectance variables with high correlation coefficients. The results showed that the chlorophyll concentration only for leaves had a relatively high correlation with REP, LCI and the reflectance peak ranging from 550nm to 560nm, and their largest correlation coefficients reached 0.75, 0.808 and 0.717 respectively. Relatively high accuracy estimation models, with R2 being 0566 and 0.542,for leaf chlorophyll a, b concentration were obtained based on the spectral reflectance variable of red edge slope by applying inverse method, while much higher accuracy estimation models, with R2 being 0.779 and 0.841,could also be got based on LCI when cubic function method were used. Chlorophyll a concentration estimation model was created based on multivariable parameters by using multiple linear regression method and its R2 was up to 0.899. The research would provide important reference data with further discuss special distribution map of salt marsh vegetation. Hence, it has important theoretical value.