Next Article in Journal
A Lookup Table-Based Method for Estimating Sea Surface Hemispherical Broadband Emissivity Values (8–13.5 μm)
Next Article in Special Issue
Detection of Oil near Shorelines during the Deepwater Horizon Oil Spill Using Synthetic Aperture Radar (SAR)
Previous Article in Journal
A Flexible, Generic Photogrammetric Approach to Zoom Lens Calibration
Previous Article in Special Issue
Marsh Loss Due to Cumulative Impacts of Hurricane Isaac and the Deepwater Horizon Oil Spill in Louisiana
Open AccessArticle

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

Graphical abstract

MDPI and ACS Style

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

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop