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引用本文:

DOI:

10.11834/jrs.20132183

收稿日期:

2012-06-06

修改日期:

2012-10-27

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森林垂直结构参数遥感反演综述
1.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;2.中国科学院大学, 北京 100049
摘要:

随着遥感技术的发展,林业遥感从早期森林分类制图的定性研究,逐步发展到森林整体特性的遥感定量反演研究。目前利用遥感反演的森林叶面积指数、生物量、叶绿素浓度、碳储量等参数以描述森林生化理化特征、水平结构特征为主,而描述森林垂直结构的参数较少。本文针对不同高度处森林的叶面积密度和冠层垂直高度廓线参数,综述了遥感获取森林垂直结构参数的方法以及典型地表类型的垂直结构参数曲线,并总结了森林垂直结构参数提取方法中存在的问题,探讨未来研究方向。

Review of forest vertical structure parameter inversion based on remote sensing technology
Abstract:

Forest vertical structure is the most complex of all vegetation parameters which describes the vertical distributing characteristic of vegetation community. The forest vertical structure not only affects the contribution of vegetation components for canopy reflectance, but also constrains the extraction accuracy of forest characteristic parameters. It also has significance influences on land surface process. With the development of remote sensing technology, forestry remote sensing developed from early forest classification mapping to quantitative retrieval of forest characteristics parameters. At present, the forest parameters that retrieved from remote sensing data include leaf area index, forest biomass, concentrations of chlorophyll and carbon storage. These parameters mainly describe the forest biochemical characteristics and horizontal structures. There are few researches on the forest vertical parameters inversion. This paper firstly focuses on two parameters of Leaf Area Density (LAD) at different heights and vertical Canopy Height Profiles (CHP) which describes the forest vertical structure in remote sensing, and summarizes their extracting methods based on remote sensing technology. Secondly several vertical profiles of typical vegetation types are collected. Finally, issues in the forest vertical structure parameter extraction are discussed, and the new research directions in this area are suggested.

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