叶肉结构对叶片光谱及生化组分定量反演的影响

doi:10.7523/j.issn.2095-6134.2005.5.009

中国科学院大学学报 ›› 2005, Vol. 22 ›› Issue (5): 589-595.DOI: 10.7523/j.issn.2095-6134.2005.5.009

叶肉结构对叶片光谱及生化组分定量反演的影响

施润和^1,2, 庄大方¹, 牛铮³, 王汶³

1. 中国科学院地理科学与资源研究所, 北京100101;
2 中国科学院研究生院, 北京100049;
3 中国科学院遥感应用研究所遥感科学国家重点实验室, 北京100101

收稿日期:2004-07-26 修回日期:2004-11-19 发布日期:2005-09-15
基金资助:
国家973项目(2002CB412507);国家863项目(2003AA131170);国家自然科学基金项目(40271086)资助

Influence of Mesophyll Structure on Leaf Spectra and Biochemical Inversion

SHI Run-He^1,2, ZHUANG Da-Fang¹, NIU Zheng³, WANG Wen³

1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
2. Graduate School of the Chinese Academy of Sciences, Beijing 100049, China;
3. LRSS, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China

Received:2004-07-26 Revised:2004-11-19 Published:2005-09-15

摘要/Abstract

摘要：

深入研究了PROSPECT模型中叶肉结构参数N对叶片反射和透射光谱的影响,利用迭代法使全波段代价函数达到最小来计算LOPEX93数据集中样品的最优N值,对在最优N值下的模拟光谱与实测光谱进行比较,并对N在不同取值情况下,叶绿素与水分的反演进行了研究.研究认为:(1)N对整个光谱波段产生影响,并随N的增大而减小;(2)构造全波段代价函数,利用迭代法得到的最优N值可以很好地模拟实际光谱;(3)在高估N值情况下的叶绿素和水分反演精度明显高于低估N值的情况;(4)水分反演的效果明显优于叶绿素反演的效果,原因与代价函数的选取有关.

关键词: PROSPECT模型, 叶肉结构, 高光谱, 定量反演, 代价函数

Abstract:

This paper presents an in2depth analysis on the influence of mesophyll structure parameter N in PROSPECT model on leaf reflectance and transmittance spectra. Optimal N values of samples in LOPEX93 data set are calculated by minimizing a whole2band cost function using the iterative method. Simulated spectra under calculated optimal N values are compared with measured ones. Further,inversions of chlorophyll and water content under different N values are performed. Results show that : (1) the influence of N involves the whole2band spectra from visible to near infrared,and the influence decreases with its values ; (2) simulated spectra with optimal N, which is calculated by minimizing a whole2band cost function using the iterative method,match very well with measured spectra ; (3) the inversion accuracy of chlorophyll and water content by using overestimated N is better than that by using underestimated N ; (4) the inversion accuracy of water content is significantly better than that of chlorophyll partially due to the selection of cost function.

Key words: PROSPECT model, mesophyll structure, hyperspectra, quantitative inversion, cost function

中图分类号:

Q94.333
TP79

施润和, 庄大方, 牛铮, 王汶. 叶肉结构对叶片光谱及生化组分定量反演的影响[J]. 中国科学院大学学报, 2005, 22(5): 589-595.

SHI Run-He, ZHUANG Da-Fang, NIU Zheng, WANG Wen. Influence of Mesophyll Structure on Leaf Spectra and Biochemical Inversion[J]. , 2005, 22(5): 589-595.

参考文献

[1] Pu RL,Gong P.Hyperspectral Remote Sensing and its Applications.Beijing :Higher Education Press,2000 (in Chinese)

[2] Elvidge CD.Visible and near infrared reflectance characteristics of dry plant materials.International Journal of Remote Sensing,1990,11 :1775～1795

[3] Curran PJ.Remote sensing of foliar chemistry.Remote Sensing of Environment,1989,30 : 271～278

[4] Hosgood B,Jacquemoud S,Andreoli G,et al.Leaf optical properties experiment 93 (LOPEX93) report EUR2160952EN.In :EuropeanCommission,Joint Research Centre,Institute for Remote Sensing Applications,Ispra,Italy,1995

[5] Accelerated Canopy Chemistry Program (ACCP).http :PPwww2eosdis.ornl.govPdaacpagesPaccp.html,1994

[6] Niu Z,Chen YH,Sui HZ,et al.Mechanism analysis of leaf biochemical concentration by high spectral remote sensing.Journal of Remote Sensing,2000,4 (1) :46～50 (in Chinese with English abstract)

[7] Ruan WL,Niu Z.Comparison of retrieving plant biochemical components with statistical and physical models.Journal of the Graduate School of theChinese Academy of Sciences,2004,21 (1) :78～83 (in Chinese with English abstract)

[8] Yoder BJ,Pettigrew2Crosby RE.Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400～2500 nm) at leaf and canopy scales.Remote Sensing of Environment,1995,53 :199～211

[9] Jacquemoud S,Baret F.PROSPECT: a model of leaf optical properties spectra.Remote Sensing of Environment,1990,34 :75～91

[10] Jacquemoud S,Ustin SL,Verdebout J,et al.Estimating leaf biochemistry using the PROSPECT leaf optical properties model.Remote Sensing of Environment,1996,56 :194～202

[11] Yan CY,Jiang GM,Wang C,et al.Theoretical simulation of single leaf’s optical characteristics.Journal of Remote Sensing,2003,7 (2) :81～85(in Chinese with English abstract)

[12] Shi RH,Niu Z,Zhuang DF.Research on the effects of leaf biochemical concentrations on leaf spectra.Journal of Remote Sensing,2005,9 (1) :1～7 (in Chinese with English abstract)

[13] Kokaly RF,Clark RN.Spectroscopic determination of leaf biochemistry using band2depth analysis of absorption features and stepwise multiple linear regression.Remote Sensing of Environment,1999,67 :267～287

[1] 浦瑞良,宫　鹏.高光谱遥感及其应用.北京:高等教育出版社.2000

[6] 牛　铮,陈永华,隋洪智,等.叶片化学组分成像光谱遥感探测机理分析.遥感学报,2000,4 (2) : 125～130

[7] 阮伟利,牛　铮.利用统计和物理模型反演植物生化组分的比较.中国科学院研究生院学报,2004,21 (1) : 78～83

[11] 颜春燕,蒋耿明,王　成,等.植被单叶光谱特性的理论模拟.遥感学报,2003,7 (2) :81～85

[12] 施润和,牛　铮,庄大方.叶片生化组分浓度对单叶光谱影响研究.遥感学报,2005,9 (1) :1～7

叶肉结构对叶片光谱及生化组分定量反演的影响

Influence of Mesophyll Structure on Leaf Spectra and Biochemical Inversion

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