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J. Mar. Sci. Eng. 2019, 7(1), 12; https://doi.org/10.3390/jmse7010012

Bayesian Statistics of Wide-Band Radar Reflections for Oil Spill Detection on Rough Ocean Surface

1
Doctoral School of Sciences and Technologies, Lebanese University (LU), 1003 Beirut, Lebanon
2
Grenoble Electrical Engineering Laboratory, Grenoble Alpes University (UGA), 38031 Grenoble, France
3
National Council of Scientific Research (CNRS-L), Remote Sensing Research Center, 22411 Mansouriyeh, Lebanon
*
Author to whom correspondence should be addressed.
Received: 26 October 2018 / Accepted: 18 December 2018 / Published: 10 January 2019
(This article belongs to the Special Issue Marine Oil Spills 2018)
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Abstract

In this paper, we present a probabilistic approach which uses nadir-looking wide-band radar to detect oil spills on rough ocean surface. The proposed approach combines a single-layer scattering model with Bayesian statistics to evaluate the probability of detection of oil slicks, within a plausible range of thicknesses, on seawater. The difference between several derived detection algorithms is defined in terms of the number of frequencies used (within C-to-X-band ranges), as well as of the number of radar observations. Performance analysis of all three types of detectors (single-, dual- and tri-frequency) is done under different surface-roughness scenarios. Results show that the probability of detecting an oil slick with a given thickness is sensitive to the radar frequency. Multi-frequency detectors prove their ability to overcome the performance of the single- and dual-frequency detectors. Higher probability of detection is obtained when using multiple observations. The roughness of the ocean surface leads to a loss in the reflectivity values, and therefore decreases the performance of the detectors. A possible way to make use of the drone systems in the contingency planning is also presented. View Full-Text
Keywords: oil spill; remote sensing; reflection coefficient; electromagnetic roughness; multi-frequency detector; multiple observations; probability density function; probability of detection; contingency planning oil spill; remote sensing; reflection coefficient; electromagnetic roughness; multi-frequency detector; multiple observations; probability density function; probability of detection; contingency planning
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Hammoud, B.; Ndagijimana, F.; Faour, G.; Ayad, H.; Jomaah, J. Bayesian Statistics of Wide-Band Radar Reflections for Oil Spill Detection on Rough Ocean Surface. J. Mar. Sci. Eng. 2019, 7, 12.

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