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.
Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images / Amitrano, Donato; Di Martino, Gerardo; Iodice, Antonio; Riccio, Daniele; Ruello, Giuseppe. - In: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING. - ISSN 0196-2892. - 56:6(2018), pp. 3290-3299. [10.1109/TGRS.2018.2797536]
Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images
Amitrano, Donato;Di Martino, Gerardo;Iodice, Antonio;Riccio, Daniele;Ruello, Giuseppe
2018
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.