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当前位置: 首页 > 文章 > 高光谱遥感影像森林信息提取方法比较 中南林业科技大学学报 2013,33 (1) 75-79
Position: Home > Articles > Comparison among methods that extract forest information from hyper-spectral remote sensing image Journal of Central South University of Forestry & Technology 2013,33 (1) 75-79

高光谱遥感影像森林信息提取方法比较

作  者：
张雨;林辉;臧卓;严恩萍;东启亮
单  位：
中南林业科技大学林业遥感信息工程研究中心
关键词：
高光谱遥感;Hyperion数据;森林信息提取;黄丰桥林场
摘  要：
以湖南省株洲市攸县黄丰桥林场为研究对象,运用最小距离、马氏距离、最大似然、光谱角制图、光谱信息散度、神经网络、支持向量机7种分类方法对Hyperion高光谱数据进行森林信息提取。通过对信息提取结果进行比较分析得出:针对Hyperion影像信息提取的7种方法中,支持向量机、神经网络和马氏距离3种分类方法较适合森林信息的提取,总体精度分别为67.39%、66.30%、62.68%;最大似然法在针叶林信息提取中的效果较好,其精度为67.31%;支持向量机法最适合提取阔叶林信息,其精度为80.19%,远远高于其它6种分类方法;运用马氏距离和神经网络法提取竹林信息精度最高,分别达到了84.21%和81.58%。
译  名：
Comparison among methods that extract forest information from hyper-spectral remote sensing image
作  者：
ZHANG Yu,LIN Hui,ZANG Zhuo,YAN En-ping,DONG Qi-liang(Research Center of Forest Remote Sensing & Information Engineering,Central South University of Forestry & Technology,Changsha 410004,Hunan,China)
关键词：
hyperspectral remote sensing;Hyperion data;forest information extraction;Huangfengqiao forest farm
摘  要：
Taking Huangfengqiao forest farm as the studied object,which is located in Youxian county,Zhuzhou City,Hunan Province,the forest information was extracted from hyper-spectral remote sensing image by using 7 kinds of classification method such as minimum distance,Mahalanobis distance,maximum likelihood,spectral angle mapping,spectral information divergence,neural network,support vector machine.Comparing the results of information extraction shows that among 7 kinds of methods of Hyperion image information extraction,support vector machine,neural network and mahalanobis distance were more suitable for forest information extraction,with overall accuracy of 67.39%,66.30%,62.68% respectively.The effect of maximum likelihood method extracted the coniferous forest information was batter than other’s with an accuracy of 67.31%.The support vector machine was most suitable for extracting the information of broad-leaved forest,with an accuracy of 80.19%,the accuracy was much higher than the other six.Mahalanobis distance and neural network mthods were the two maximam ways to extract the bamboo forest information,with accuracy of 84.21% and 81.58% respectively.

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