植物叶片多种色素高光谱遥感机理与模型研究

项目名称： 植物叶片多种色素高光谱遥感机理与模型研究

项目编号： No.41471277

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 天文学、地球科学

项目作者： 黄敬峰

作者单位： 浙江大学

项目金额： 89万元

中文摘要： 由于植物叶片中的色素（叶绿素a和b、β-胡萝卜素、叶黄素和花青素）含量与植物的光合作用、营养状况和环境变化有关，因此，开展植物多色素高光谱遥感机理和模型研究，是植被高光谱遥感的基础工作。本研究利用高效液相色谱仪精确测定叶片各种色素含量，针对叶片中色素吸收波段谱带交叠现象，将化学计量学中的光谱分峰技术引入到植物色素高光谱遥感，量化各种色素在叶片光谱上的重叠和遮蔽特征，获得能反映单一色素的光谱，再采用神经网络方法建立叶片多色素含量高光谱遥感估算模型；将PROSPECT-5模型中的叶绿素、类胡萝卜素含量输入项改为叶绿素a和b、β-胡萝卜素、叶黄素和花青素含量，通过最小代价函数迭代确定模型参数，建立能反映叶绿素a和b、β-胡萝卜素、叶黄素和花青素含量变化的PROSPECT模型，并进行模型的敏感性分析和精度验证；最后，利用改进的PROSPECT模型进行叶片多色素定量遥感反演。

中文关键词： 植被生物化学参数；植被生物物理参数；高光谱遥感；光谱分峰技术；PROSPECT模型

英文摘要： The studies on the quantitative inversion of leaf pigments, including chlorophyll a, chlorophyll b, beta-carotene, xanthophyll and anthocyanins, using hyperspectral remote sensing technology are the basis of vegetation hyperspectral remote sensing because the pigments content are the indicators of photosynthesis, nutritional status and environmental change. Among studies on content estimation of foliar pigment in the literature reviewed, the estimation of total chlorophyll content is highly performed, and only a few articles were found for the estimation of chlorophyll a or chrolophyll b content.To our knowledge, few studies have tried to relate the beta-carotene content, xanthophyll content and anthocyanins content to the leaf hyperspectral parameters.This is because that the precise measurement of chlorophyll a, chlorophyll b, beta-carotene, xanthophyll and anthocyanins is difficult using spectrophotometer and the overlap phenomina in the leaf spectra of the different pigments. The aim of our work include: 1. According to the pigment varieties and content of plant leaves in different growth stage, Loropetalum Chinense, Acer saccharum Marsh, Elaeocarpus Sylvestris are selected as tested plants preliminarily. Leaves with different pigment content are collected as the experimental material in different growth stage. The reflectance spectra of leaves are measured immediately. The content of chlorophyll a, chlorophyll b, beta-carotene, xanthophyll and anthocyanins will be measured precisely using High Performance Liquid Chromatography. Other parameters such as water content, dry matter, cellulose content, lignin content will be measured at the same time. 2. Spectral peak separation technology which is widely used in Chemometrics will be introduced to data processing of leaf spectra in order to separate the influnce of chlorophyll a, chlorophyll b, beta-carotene, xanthophyll and anthocyanins on leaf spectra, to quantify the overlapping and sheltering characteristics of various pigment on the leaf spectra, and to obtain a spectrum which can reflect the characteristics of a individual pigment, and then to establish estimation models of pigment content using neural network with hyperspectral data. 3.The PROSPECT-5 model will be modified by introduce the input parameters including the content of chlorophyll a, the content of chlorophyll b, the content of β-carotene, the content of xanthophylls, and the content of anthocyanins. The parameters of pigment specific absorption coefficients, leaf structure parameter and leaf refractive index will be obtained by iterating based on the minimum cost function in the range of 400nm-800nm using the leaf reflectance spectra and the corresponding pigment content. After sensitivity and accuracy analysis were performed on modified PROSPECT model,the pigment content, including chlorophyll a, chlorophyll b, β-carotene, xanthophylls, and anthocyanins, can be inversed quantitatively.

英文关键词： biochemical parameters of vegetation;biophysical parameters of vegetation;hyperspectral remote sensing;spectral peak separation technology;PROSPECT model