4.7 Article

Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2018.2797536

关键词

Classification; co-occurrence texture; flooding; fuzzy systems; synthetic aperture radar (SAR)

资金

  1. POR Campania FSE Sviluppo di metodologie e tecniche per applicazioni di telerilevamento al monitoraggio ferroviario

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We present a new methodology for rapid flood mapping exploiting Sentinel-1 synthetic aperture radar data. In particular, we propose the usage of ground range detected (GRD) images, i.e., preprocessed products made available by the European Space Agency, which can be quickly treated for information extraction through simple and poorly demanding algorithms. The proposed framework is based on two processing levels providing event maps with increasing resolution. The first level exploits classic co-occurrence texture measures combined with amplitude information in a fuzzy classification system avoiding the critical step of thresholding. The second level consists of a change-detection approach applied to the full resolution GRD product. The discussion is supported by several experiments demonstrating the potentiality of the proposed methodology, which is particularly oriented toward the end-user community.

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