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Flood is the most frequent disaster in the world, which can do harm to agriculture and threat to food security. Using kernel based supervised classifier to execute change detection for multi-temporal remote sensing data is a common method for flood disaster monitoring and assessment, and kernel Fisher's discrimination analysis (KFDA) is one of them. Choosing training sample by visual interpretation...
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