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人工神经网络遥感分类方法研究现状及发展趋势探析
引用本文:修丽娜,刘湘南.人工神经网络遥感分类方法研究现状及发展趋势探析[J].遥感技术与应用,2003,18(5):339-345.
作者姓名:修丽娜  刘湘南
作者单位:(东北师范大学城市与环境科学学院,吉林 长春 130024)
基金项目:教育部高等学校骨干教师资助计划项目,霍英东教育基金会高等院校青年教师基金项目(71029),东北师范大学青年科学基金项目(111418)。
摘    要:从人工神经网络技术本身出发,概括了其在遥感分类中的研究现状,分析了人工神经网络遥感分类方法与其它分类方法相比具有的优势,介绍了人工神经网络遥感分类的一些主要应用,并进一步对人工神经网络遥感分类方法的发展趋势进行了展望。

关 键 词:人工神经网络  遥感影像  分类  
文章编号:1004-0323(2003)05-0339-07
修稿时间:2003年5月8日

Current Status and Future Direction of the Study on Artificial Neural Network Classification Processing in Remote Sensing
XIU Li-na,LIU Xiang-nan.Current Status and Future Direction of the Study on Artificial Neural Network Classification Processing in Remote Sensing[J].Remote Sensing Technology and Application,2003,18(5):339-345.
Authors:XIU Li-na  LIU Xiang-nan
Affiliation:(College of Urban and Environmental Sciences,Northeast Normal University,Changchun130024,China)
Abstract:This paper generalized all-roundly the current study status of artificial neural network in remote sensing image classification and introduced its major application to remote sensing images classification abroad and home. For example, vegetation information extraction in remote sensing images using artificial neural network method, snowfall and rainfall information extraction in SAR images, information content extraction in mixed pixel or its decomposition by the study of multi-information content and uncertainty of object property in sample data. Compared with other classification methods, this paper also pointed out the advantage of artificial neural network method in remotely sensed images classification and made prospects for its future development trend, including the integration of ANN and expert system, the combination of ANN and traditional analysis method, the fusion of ANN and geographical knowledge, the integration of ANN and image fusion technology, and so on. Finally it is summarized that the artificial neural network method is an useful and effective means in remote sensing images classification. Though the study and application of artificial neural network method in remote sensing image classification is still in the beginning stage, the compositive analysis ability of artificial neural network models provided credible new approach for the analysis and classification of remote sensing images and other multi-source data.
Keywords:Artificial neural network  Remote sensing images  Classification
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