Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors.
Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors.
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DOI：
10.3390/s90402719
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Moskal LM
中科院分区：
文献类型：
--
作者：
Zheng G;Moskal LM
准确、快速获取叶面积指数（LAI）的能力是基于过程的生态研究不可或缺的组成部分，有助于理解从叶子到景观的一系列空间尺度上的气体-植被交换现象。然而，由于 LAI 耗时且工作强度大，很难直接获取大范围的空间范围。光学和主动遥感技术的出现大大改善了这些努力。本文回顾了直接法和间接法 LAI 测量的定义和理论。然后，讨论了针对一系列遥感数据集特征的 LAI 反演方法。间接遥感方法分为被动遥感和主动遥感两类，又分为地面遥感、空中遥感和星载平台。由于遥感数据的空间分辨率多种多样以及生态建模的要求，讨论了LAI的缩放问题，并特别考虑了将测量外推到景观和区域水平。
The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels.
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影响因子：
6.2
作者：
CHEN, JM;BLACK, TA
通讯作者：
BLACK, TA
影响因子：
4.4
作者：
Chen, JM;Rich, PM;Plummer, S
通讯作者：
Plummer, S
影响因子：
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作者：
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通讯作者：
CAMPBELL, GS
影响因子：
6.4
作者：
Chen, JM;Chen, XY;Geng, XY
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影响因子：
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作者：
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通讯作者：
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