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Remote Sens. 2017, 9(3), 230;

Fast Detection of Oil Spills and Ships Using SAR Images

Consorzio Nazionale Interuniversitario delle Telecomunicazioni (CNIT)-National Laboratory of Radar and Surveillance Systems (RaSS), 56124 Pisa, Italy
Department of Information Engineering, University of Pisa, 56126 Pisa, Italy
Author to whom correspondence should be addressed.
Academic Editors: Ira Leifer, Elijah Ramsey, Bill Lehr, Xiaofeng Li and Prasad S. Thenkabail
Received: 29 October 2016 / Revised: 21 February 2017 / Accepted: 1 March 2017 / Published: 6 March 2017


In this paper, we show the capabilities of a new maritime control system based on the processing of COSMO-SkyMed Synthetic Aperture Radar (SAR) images. This system aims at fast detection of ships that may be responsible for illegal oil dumping. In particular, a novel detection algorithm based on the joint use of the significance parameter, wavelet correlator and a two-dimensional Constant False Alarm Rate (2D-CFAR) is designed. Results show the effectiveness of such algorithms, which can be used by the maritime authorities to have a faster although still reliable response. The proposed algorithm, together with the short revisit time of the COSMO-SkyMed constellation, can help with tracking the scenario evolution from one acquisition to the next. View Full-Text
Keywords: oil spill; CFAR; ship detection; fast; early warning; maritime surveillance oil spill; CFAR; ship detection; fast; early warning; maritime surveillance

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Lupidi, A.; Staglianò, D.; Martorella, M.; Berizzi, F. Fast Detection of Oil Spills and Ships Using SAR Images. Remote Sens. 2017, 9, 230.

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