叶面积指数遥感反演研究进展与展望
收稿日期: 2013-07-04
修回日期: 2013-08-07
网络出版日期: 2013-09-29
基金资助
国家“973”计划项目(2010CB950701);气象行业科研专项(GYHY201106014);博士后面上基金项目(2012M510343)。
Current Status and Perspectives of Leaf Area Index Retrieval from Optical Remote Sensing Data
Received date: 2013-07-04
Revised date: 2013-08-07
Online published: 2013-09-29
叶面积指数表征叶片的疏密程度和冠层结构特征,体现植被光合、呼吸和蒸腾作用等生物物理过程的能力,是描述土壤-植被-大气之间物质和能量交换的关键参数。目前多种卫星传感器观测生成了多个区域和全球的叶面积指数标准产品。本文综述了基于光学遥感数据的叶面积指数反演进展:首先,介绍了叶面积指数的定义和在生态系统模拟中的作用;然后,阐述了基于光学遥感反演叶面积指数的基本原理;在此基础上,论述了基于植被指数经验关系和基于物理模型的两种主要遥感反演算法,讨论了2种算法的优点和存在的问题,并总结了现有的主要全球数据产品及其特点,论述了产品检验的方法和需要注意的问题;最后,总结了当前叶面积指数反演中存在的问题,并展望了其发展趋势和研究方向。
刘洋, 刘荣高, 陈镜明, 程晓, 郑光 . 叶面积指数遥感反演研究进展与展望[J]. 地球信息科学学报, 2013 , 15(5) : 734 -743 . DOI: 10.3724/SP.J.1047.2013.00734
Leaf area index (LAI) is a primary parameter for charactering leaf density and vegetation structure. Since it could represent the capability of vegetation for photosynthesis, respiration and transpiration, LAI is used as a critical parameter for modeling water, carbon and energy exchanges among soil, vegetation and the atmosphere. Several regional and global LAI datasets have been generated from satellite observations. This paper reviews current status of theoretical background, algorithms, products and evaluation of LAI from optical remote sensing data. First, the definition of LAI and its effects in ecosystem modeling are introduced. Then, the radiative transfer processes of photon in canopy are described briefly. Based on these processes, vegetation presents its own spectral response characteristics, which are related to biophysical and biochemical properties of leaves, canopy and soil background, making it possible to derive LAI from optical remote sensing data. Two main methods which establish the relationships between LAI and satellite observed spectral canopy reflectance are widely used for LAI retrieval from remote sensing data, including vegetation index-based empirical regression method and physical model-based method. These two methods are presented subsequently, and their advantages and disadvantages are also discussed. Several major global LAI remote sensing products are reviewed, such as MOD15, CYCLOPES, GLOBCARBON and GLOBMAP LAI. The methods for LAI products evaluation and validation are presented, and several problems in LAI evaluation are also discussed. Finally, several problems in LAI retrieval are concluded, and directions for future research of LAI retrieval are then suggested.
Key words： vegetation; leaf area index; remote sensing retrieval; products
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