基于冠层尺度的枣树色素含量的高光谱估算模型  

Estimation Models for Jujube Leaf Pigment Concentration with Hyperspectrum Data at Canopy Scale

作　　者：柳维扬[1] 彭杰[1] 窦中江[2] 陈兵[2] 王家强[1] 向红英[1] 代希君 王琼[2] 牛建龙[1] LIU Wei-yang PENG Jie DOU Zhong-jiang CHEN Bing WANG Jia-qiang XIANG Hong-ying DAI Xi-jun WANG Qiong NIU Jian-long(College of Plant Science, Tarim University, Alar 843300, China Xinjiang Academy Agricultural and Reclamation Science, Shihezi 832000, China College of Mechanical and Electrical Engineering, Tarim University, Alar 843300, China)

机构地区：[1]塔里木大学植物科学学院,新疆阿拉尔843300 [2]新疆农垦科学院,新疆石河子832000 [3]塔里木大学机械电器化工程学院,新疆阿拉尔843300

出　　处：《光谱学与光谱分析》2017年第1期156-161,共6页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(11564032;41161068);新疆兵团工业科技计划项目(2014BA019)资助

摘　　要：植物冠层色素含量与氮素含量具有高度的相关性,是农业遥感中的关键研究因素。本研究的主要目的是:(1)对比偏最小二乘回归和支持向量机两种建模方法对枣树冠层色素的预测精度;(2)构建基于高光谱数据的枣树冠层色素含量定量反演模型,为枣树冠层色素含量的快速、无损、廉价、环保的测定提供一定的理论依据和技术支持。相关性分析结果表明,枣树冠层色素与高光谱数据之间具有较好的相关性,但叶绿素、叶绿素a要优于叶绿素b和类胡萝卜素。独立样本对模型的预测性能检验结果表明,偏最小二乘回归和支持向量机均能有效的估算枣树色素含量,但不同色素的偏最小二乘回归模型和支持向量机模型的预测精度存在一定的差异,叶绿素和类胡萝卜素的支持向量机模型的预测精度要高于偏最小二乘回归模型,而叶绿素a和叶绿素b则相反。比较不同色素的最佳反演模型的预测精度表明,叶绿素、叶绿素a和类胡萝卜素的预测精度要优于叶绿素b,前三者的决定系数大于0.8,残余预测误差高于2.0,平均相对误差低于13%,而叶绿素b的对应值分别为0.60%,20.79%和1.79%。Plant canopy pigment concentration is a critical variable for agricultural remote sensing due to its close relationship to leaf nitrogen content.The aims of this study were to：（1）compare the prediction performances on chlorophyll,chlorophyll-a and b,and carotenoid concentration in jujube leaf at canopy scale between partial least squares regression（PLSR）and support vector machine（SVM）,（2）develop quantitative models to estimate pigment concentration in jujube canopy using hyperspectral data and provide theoretical and technical support for rapidly,non-destructive,less expensive and eco-friendly measuring the concentration.Results from correlation analysis showed that jujube canopy pigment concentration correlated strongly with hyperspectral data.What’s more,the hyperspectral data was better correlated by chlorophyll and chlorophyll-a than chlorophyll-b and carotenoid.Results of independent samples tested in predicting performance indicated that both of the PLSR and SVM models could effectively estimate pigment concentration,however,with different prediction precisions.Additionally,the precision of SVM outperformed PLSR for predicting chlorophyll and carotenoid.Whereas chlorophyll-a and chlorophyll-b were better predicted using PLSR than SVM.Compared among all the pigments’ prediction precisions with corresponding optimal inversion models showed that prediction precisions on chlorophyll,chlorophyll-a and carotenoid were superior to chlorophyll-b.The determination coefficients and residual prediction deviation from predicting chlorophyll,chlorophyll-a and carotenoid were higher than 0.8and 2.0,respectively,while the mean relative error values were lower than 13%.And the corresponding values from predicting chlorophyll-b were 0.60%,20.79% and 1.79% respectively.

关 键 词：枣树 色素 冠层尺度 可见光近红外光谱 定量反演模型 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]