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遥感技术与应用  2008, Vol. 23 Issue (2): 239-247    DOI: 10.11873/j.issn.1004-0323.2008.2.239
综述     
基于遥感植被生物量估算模型自变量相关性分析综述
徐小军1,杜华强1,周国模1,范文义2
(1.浙江林学院环境科技学院,浙江 临安 311300;
2.东北林业大学林学院,黑龙江 哈尔滨 150040)
Review on Correlation Analysis of Independent Variables in Estimation Models of Vegetation Biomass Based on Remote Sensing
XU Xiao-jun1,DU Hua-qiang1,ZHOU Guo-mo1,FAN Wen-yi2
(1.School of Environmental Sciences and Technology|Zhejiang Forestry College, 
Lin'an 311300,China|2.Forestry College of Northeast Forestry University,Harbin 150040,China|)
 全文: PDF(1093 KB)  
摘要:

应用遥感估算植被生物量越来越受到人们的关注。在利用遥感信息参数以及其它因子构建模型时,往往要挑选一些对生物量具有显著影响的因子作为自变量,因此自变量个数的确定、自变量的选择对估算模型的可靠性及精度影响很大。从单变量模型、多变量模型以及参数、非参数模型等几个方面论述了植被生物量估算遥感信息模型自变量相关性,并提出了一些建议,希望能对植被生物量估算模型自变量的选择提供参考价值。

关键词: 生物量自变量遥感模型相关性分析    
Abstract:

Applying remote sensing to estimate vegetation biomass has been paid more attention.When using the remote sensing information parameters and other parameters to construct models,researchers often need choose some parameters as independent variables which have obvious influence on biomass.Therefore,identifying the number of independent variables and choosing independent variables play an important role in the reliability and precision of estimation models.From single-variable models,multi\|variables models and nonparametric models,the article reviews on correlation analysis of independent variables in estimation models of vegetation biomass based on remote sensing,which offers some referenced value for choosing the independent variables in estimation models of vegetation biomass.

Key words: Biomass    Independent variable    Remote sensing    Model    Correlation analysis
收稿日期: 2007-12-06 出版日期: 2011-10-24
:  TP 79  
基金资助:

国家自然科学基金(30700638)、浙江科技厅优先主题项目“毛竹林吸收温室气体CO2关键技术应用与示范”和国家“863”专题课题(2006AA12Z104)共同资助。

作者简介: 徐小军(1984-),男,硕士研究生,主要从事遥感估测植被碳储量方面研究。E-mail:xuxiaojun3115371@163.com。
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引用本文:

徐小军,杜华强,周国模,范文义. 基于遥感植被生物量估算模型自变量相关性分析综述[J]. 遥感技术与应用, 2008, 23(2): 239-247.

XU Xiao-jun,DU Hua-qiang,ZHOU Guo-mo,FAN Wen-yi. Review on Correlation Analysis of Independent Variables in Estimation Models of Vegetation Biomass Based on Remote Sensing. Remote Sensing Technology and Application, 2008, 23(2): 239-247.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2008.2.239        http://www.rsta.ac.cn/CN/Y2008/V23/I2/239

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