基于遥感影像的植被指数研究方法述评

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摘要

随着遥感技术的发展,植被指数作为用来表征地表植被覆盖和生长状况的度量参数,已经在环境、生态、农业等领域有了广泛的应用。本文在分析植被指数形成机制及影响因子的基础上,对其具有一定技术突破的典型植被指数进行了归纳分类与比较分析,并评价了各自的优势和局限性。植被指数按遥感数据采集的平台可以分为航空植被指数和航天植被指数两大类,其中航天植被指数又可以分为基于波段简单线性组合的植被指数、消除影响因子的植被指数和针对高光谱遥感及热红外遥感的植被指数三类。最后就植被指数应用中存在的问题以及发展前景谈了一些看法:植被指数数目繁琐重复,急待规范条理化;植被指数应用领域不同,使用者时要慎重;植被指数影响因子很多,具体使用时应适时修正;植被指数公式繁琐阻碍其应用,应开发植被指数产品;遥感技术日新月异,积极研发新的植被指数。

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	罗亚
	徐建华
	岳文泽

关键词 ：遥感, 植被指数, 航空, 航天

Abstract：

With the development of remote sensing technology, vegetation indices(VI), which is a quantitative indicator for ivegetation canopy and growth conditions, has been widely applied in the fields such as environmental, ecological and agricultural studies. Different types of VI have been developed during last thirty years to enhance vegetation and minimize the effects of the factors. This paper reviews the formation mechanism and the factors of VI such as vegetation conditions, atmosphere, soil, sensor calibration, sensor viewing conditions. The VI with technical innovation are discussed and analyzed for the advantages and limitations. In general, the vegetation indices are classified into airborne and satelliate VI according to the sensor platform. The satelliate vegettion indices consist of three sorts of VI: simple linear combination of the spectral bands, eliminating the effects of the factors and aiming at hyperspectral remote sensing technology and thermal infrared multi-spectral remote sensing technology. Several issues in VI future development are also addressed: Firstly, Standardization and classification of different types of VI are necessary. Secondly, the applied fields of various VI are different so that the choice of VI should be careful. Thirdly, Because of many factors of affecting VI, modification should be made before application in practice. Also, the complex formula of VI prevent its application. Finally, new VI should be developed based on the advance of remote sensing technology.

Key words： Remote sensing Vegetation index Airborne Spaceflight

收稿日期: 2005-02-25

Q147

基金资助:国家自然科学基金项目(40371092)资助

引用本文:

罗亚, 徐建华, 岳文泽. 基于遥感影像的植被指数研究方法述评[J]. , 2005, 24(1): 75-79.
LUO Ya, XU Jian-Hua, YUE Wen-Ze. Research on vegetation indices based on the remote sensing images. , 2005, 24(1): 75-79.

链接本文:

http://www.ecolsci.com/CN/Y2005/V24/I1/75

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