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Multi-temporal remote sensing data can provide much more information that could be used to improve the accuracy of classification of vegetation types. However, it is always required to manually select a set of training samples by using conventional supervised classification methods, which is a time-consuming and costly task. In this paper, a new classification method based on spectral knowledge database...
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