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Multi-temporal SAR Images Classification Using Case-based Reasoning for Application of Land Use and Land Cover Change |
CHEN Fu-long1,2,3, WANG Chao1,3, ZHANG Hong3
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(1.State Key Laboratory of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing100101,China;2.Graduate University of the Chinese Academy of Sciences,Beijing100101; 3.China Remote Sensing Satellite Ground Station,Chinese Academy of Sciences,Beijing100086,China) |
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Abstract In this paper, we investigate a case-based reasoning (CBR) method for the classification of multi-temporal SAR images with the aid of ancillary information. Our scheme for the problem of multi-temporal SAR images classification comprises four main steps, including SAR image processing, construction of case library, case-based classification and post-classification processing. During the construction of case library, we employ a spatial-temporal analysis technique to remove fake cases, which can guarantee cases with high credibility. In the implementation of case-based classification, we propose a stratified similarity assessment and use it for the case-based matching. After that, we investigate an object-oriented post-classification method which takes the shape of land use region into account, as a result, it leads to a more meaningful classification, and the regenerate land use image or map can be easier compared and combined with usual GIS data. A series of multi-temporal SAR images for 2000 and
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Received: 15 November 2006
Published: 25 November 2011
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