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    Bayesian identification of oil spill source parameters from image contours

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    Name:
    MPB-D-20-01662.pdf
    Size:
    17.44Mb
    Format:
    PDF
    Description:
    Accepted manuscript
    Embargo End Date:
    2023-06-04
    Download
    Type
    Article
    Authors
    El Mohtar, Samah
    Ait-El-Fquih, Boujemaa
    Knio, Omar
    Lakkis, Issam
    Hoteit, Ibrahim cc
    KAUST Department
    Earth Fluid Modeling and Prediction Group
    Earth Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    KAUST Grant Number
    OSR-CRG2018-3711
    REP/1/3268-01-01
    Date
    2021-06-04
    Online Publication Date
    2021-06-04
    Print Publication Date
    2021-08
    Embargo End Date
    2023-06-04
    Submitted Date
    2020-09-07
    Permanent link to this record
    http://hdl.handle.net/10754/669383
    
    Metadata
    Show full item record
    Abstract
    Oil 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.
    Citation
    El 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
    Sponsors
    We 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).
    Publisher
    Elsevier BV
    Journal
    Marine Pollution Bulletin
    DOI
    10.1016/j.marpolbul.2021.112514
    Additional Links
    https://linkinghub.elsevier.com/retrieve/pii/S0025326X21005488
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.marpolbul.2021.112514
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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