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

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.

Recent Advances in Oil-Spill Monitoring Using Drone-Based Radar Remote Sensing

“…Therefore, it is important to use more than one frequency to improve the detection or estimation. To see the effect of the relative permittivity of the oil on the reflectivity, Figure 3 studies the variation of this parameter evaluated at two frequencies: 4 and 12 GHz [69]. For the same frequency, the effect of the variation in the relative permittivity on the reflectivity value is dependent on the oil thickness.…”

Effects of chemical dispersant on the surface properties of kaolin and aggregation with spilled oil

“…Common oil spill responses are mostly applicable to the oating oil but ineffective for the sunken oil (IMO, 2012; Usher, 2009). Remarkably, the sunken oil cannot be easily monitored by typical visual observation or remote sensing techniques (Yu et al, 2021;Hammoud et al, 2019), posing challenges to the cleaning operations (Jacqueline, 2008).…”

Oil Spill Monitoring of Shipborne Radar Image Features Using SVM and Local Adaptive Threshold

“…For example, a recent oil spill disaster has continued to pollute many of Brazil's coastlines for months, with the catastrophe exhausting the resources of the government and communities [3,4]. Marine oil spills can diffuse extensively the sea surface within several hours, leading to very serious consequences [5]. Billions of dollars are spent preventing pollution, but risk cannot be completely eliminated [6].…”