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遥感技术与应用  2019, Vol. 34 Issue (1): 155-165    DOI: 10.11873/j.issn.1004-0323.2019.1.0155
模型与反演     
全球典型植被叶片光谱特征及其对LAI反演的影响分析
刘洁1,李静2,柳钦火1,2,何彬彬1,于文涛2
(1.电子科技大学资源与环境学院,四川 成都 611731;
2.中国科学院遥感与数字地球研究所遥感科学国家重点实验室,北京 100101)
 
GlobalLeaf Spectral Characteristics of Typical Vegetation and It’s Impacts on LAI Inversion
Liu Jie1,Li Jing2,Liu Qinhuo1,2,He Bingbing1,Yu  Wentao2
(1.School of Resources and Environment,University of Electronic Science and Technologyof China,Chengdu 611731,China;
2.State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100101,China)
 
 全文: PDF(2430 KB)  
摘要: 在全球范围长时间序列LAI遥感产品反演算法中,植被冠层反射率模型仅使用少量叶片光谱特征代表全球植被全年的典型植被光谱特征,叶片光谱的不确定性导致LAI遥感产品存在一定的误差。目前全球已经构建了多个典型植被叶片波谱数据集,这些数据集包含多个植被物种、不同空间地域及多时相叶片光谱数据,为定量分析叶片光谱特征提供了数据支持。主要利用LOPEX’93、ANGERS’03、中国典型地物波谱数据库和野外实测的叶片光谱数据,以黄边参数、红边参数和叶片光谱指数作为分析指标,探讨不同植被物种、不同气候区和不同物候期的叶片光谱特征差异,及其对植被冠层反射率、LAI反演的影响,为发展考虑现实叶片光谱差异的LAI反演算法提供研究基础。结果表明:植被叶片光谱存在多样性,叶片光谱特征差异主要影响MODIS传感器近红外波段和绿波段反射率值,其中,绿波段反射率值对叶片光谱变化最为敏感;在LAI反演算法中,如果只考虑植被类型而不考虑物种叶片光谱差异,可能会给LAI反演带来大于3的误差。
  
关键词: 叶片光谱特征LOPEX’93ANGERS’03中国典型地物波谱库叶面积指数    
Abstract: Long time series LAI remote sensing inversion algorithms use only a few leaves spectra to represent the global leaf spectral characteristics throughout the year.while due to the variation of leaf spectra,it may introduce uncertainties to LAI remote sensing products.An amount of spectrum databases containing leaf spectrum of different vegetation species,geographical locations and time phase and corresponding biochemical parameters have been constructed to provide support for the analysis of spectral characteristics of leaves.This paper mainly uses the leaf spectral database LOPEX’93,ANGERS’03,Spectral library of typical ground objects in China and field experimental data to analyze the effects of spectral characteristics of different plant species and different climate zones on MODIS reflectance of specific channels and further to provide prior information for the development of LAI inversion algorithms with consideration of leaf spetra differences.The result suggests that:There exists diversity in vegetation leaf spectra.The spectral differences mainly affect the reflectance in red and green band (green band is most sensitive to leaf spectra variation).Only considering vegetation types without taking leaf spectral variation into account may induce error over 3 in remote sensing LAI inversion algorithms.
Key words: Leaf optical characteristics    LOPEX’93    ANGERS’03    Spectral library of typical ground objects in China    Leaf area index
收稿日期: 2018-03-03 出版日期: 2019-04-02
ZTFLH:  TP237  
基金资助:

高分项目“GF-6卫星宽幅相机影像植被参数定量反演技术项目”(30Y20A03-9003017/18)。

作者简介: 刘洁(1991-),女,湖南邵阳人,硕士研究生,主要从事叶片组分光学特征方面的研究。E-mail:781159111@qq.com。
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引用本文:

刘洁, 李静, 柳钦火, 何彬彬, 于文涛. 全球典型植被叶片光谱特征及其对LAI反演的影响分析[J]. 遥感技术与应用, 2019, 34(1): 155-165.

Liu Jie, Li Jing, Liu Qinhuo, He Bingbing, Yu Wentao. GlobalLeaf Spectral Characteristics of Typical Vegetation and It’s Impacts on LAI Inversion. Remote Sensing Technology and Application, 2019, 34(1): 155-165.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.1.0155        http://www.rsta.ac.cn/CN/Y2019/V34/I1/155

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