Bayesian identification of oil spill source parameters from image contours
KAUST DepartmentEarth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Embargo End Date2023-06-04
Permanent link to this recordhttp://hdl.handle.net/10754/669383
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AbstractOil spills at sea pose a serious threat to coastal environments. Identifying oil pollution sources could help to investigate unreported spills, and satellite imagery can be an effective tool for this purpose. We present a Bayesian approach to estimate the source parameters of a spill from contours of oil slicks detected by remotely sensed images. Five parameters of interest are estimated: the 2D coordinates of the source of release, the time and duration of the spill, and the quantity of oil released. Two synthetic experiments of a spill released from a fixed point source are investigated, where a contour is fully observed in the first case, while two contours are partially observed at two different times in the second. In both experiments, the proposed method is able to provide good estimates of the parameters along with a level of confidence reflected by the uncertainties within.
CitationEl Mohtar, S., Ait-El-Fquih, B., Knio, O., Lakkis, I., & Hoteit, I. (2021). Bayesian identification of oil spill source parameters from image contours. Marine Pollution Bulletin, 169, 112514. doi:10.1016/j.marpolbul.2021.112514
SponsorsWe thank Prof. Håvard Rue for suggestions related to MCMC. We also thank Dr. Yanhui Zhang for helpful discussions related to the Hausdorff distance. Research reported in this publication was supported by the Office of Sponsored Research (OSR) at King Abdullah University of Science and Technology (KAUST) under Award No. OSR-CRG2018-3711 and under the Virtual Red Sea Initiative (Grant #REP/1/3268-01-01).
JournalMarine Pollution Bulletin