A reflectance spectra model of heavy metal stressed leaves: advances in the PROSPECT model adding specific absorption coefficients of heavy metal ion

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Qu, Yonghua^1 ; Zhu, Yeqing^1 ; Ge, Xiaoli^2

State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University, Chinese Academy of Sciences, Beijing, 100875, China^1

China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing, 100083, China^2

关键词: Biochemical components;    Correlation coefficient;    In-laboratory experiments;    Laboratory experiments;    Pigment concentration;    Radiative transfer model;    Scanning electron microscopy image;    Specific absorption coefficients;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012041/pdf
DOI  :  10.1088/1755-1315/17/1/012041

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

This article aims to investigate the reflectance model of heavy metal copper stressed crop. Forty-six groups of copper-treated leaves were measured during a laboratory experiment in order to obtain the leaf biochemical component information and its corresponding scanning electron microscopy image. Then a new reflectance spectral model was developed on the basis of the classical broadleaf radiative transfer model-PROSPECT. Comparing with the PROSPECT model, new models mainly consider adding specific absorption coefficient of copper ion. The scattering process is described by a refractive index (n) and a leaf structure parameter (N). Absorption is modeled using pigment concentration, water content, dry matter content, copper ion contamination and the corresponding specific spectral absorption coefficients (Kab, Kw, Kd, KCu). Thus, reflectance spectral modeling is an inversion procedure to calculate the above 6 parameters accurately. To validate the model 16 leaves were tested in laboratory experiment. This experiment showed that the inversion values of KCuhad very strong agreement with the published absorption spectra of Cupric Chloride. The linear regression analysis between simulated and measured reflectance provides a correlation coefficient of 0.93 and a root mean squares of 0.067.