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Land Use Classification Based on Remote Sensing Images and Weighted Clustering Method

机译:基于遥感影像和加权聚类法的土地利用分类

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Quite a few methods have been applied in the remote sensing images processing. Among which the fuzzy clustering method is effective to land use classification. This paper analyzes some of the shortages in basic principles of the fuzzy clustering methods caused by the massive redundant information in multispectral images, and supplies an updated weighted clustering method, which considers the weights of different spectrums according to their effective information capacities. In examination we take the TM images of pan of Beijing city as an example to carry out land use classification. The results of ISODATA clustering method, common fuzzy K-mean clustering method and weighted clustering method are compared.
机译:在遥感图像处理中已经应用了许多方法。其中模糊聚类法对土地利用分类有效。本文分析了由多光谱图像中大量冗余信息引起的模糊聚类方法基本原理的不足,并提供了一种更新的加权聚类方法,该方法根据不同频谱的有效信息容量来考虑其权重。在检验中,我们以北京市平底锅的TM图像为例进行土地利用分类。比较了ISODATA聚类方法,常用模糊K均值聚类方法和加权聚类方法的结果。

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