Bayesian identification of oil spill source parameters from image contours

Samah El Mohtar; Boujemaa Ait-El-Fquih; Omar Knio; Issam Lakkis; Ibrahim Hoteit

doi:10.1016/j.marpolbul.2021.112514

Bayesian identification of oil spill source parameters from image contours

Samah El Mohtar, Boujemaa Ait-El-Fquih, Omar Knio, Issam Lakkis, Ibrahim Hoteit

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

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.

Original language	English (US)
Pages (from-to)	112514
Journal	Marine Pollution Bulletin
Volume	169
DOIs	https://doi.org/10.1016/j.marpolbul.2021.112514
State	Published - Jun 4 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-06-07
Acknowledged KAUST grant number(s): OSR-CRG2018-3711, REP/1/3268-01-01
Acknowledgements: 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).

ASJC Scopus subject areas

Oceanography
Pollution
Aquatic Science

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10.1016/j.marpolbul.2021.112514

https://repository.kaust.edu.sa/bitstream/10754/669383/1/MPB-D-20-01662.pdf

Cite this

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title = "Bayesian identification of oil spill source parameters from image contours",

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.",

author = "{El Mohtar}, Samah and Boujemaa Ait-El-Fquih and Omar Knio and Issam Lakkis and Ibrahim Hoteit",

note = "KAUST Repository Item: Exported on 2021-06-07 Acknowledged KAUST grant number(s): OSR-CRG2018-3711, REP/1/3268-01-01 Acknowledgements: We thank Prof. H{\aa}vard 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).",

year = "2021",

month = jun,

day = "4",

doi = "10.1016/j.marpolbul.2021.112514",

language = "English (US)",

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journal = "Marine Pollution Bulletin",

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T1 - Bayesian identification of oil spill source parameters from image contours

AU - El Mohtar, Samah

AU - Ait-El-Fquih, Boujemaa

AU - Knio, Omar

AU - Lakkis, Issam

AU - Hoteit, Ibrahim

N1 - KAUST Repository Item: Exported on 2021-06-07 Acknowledged KAUST grant number(s): OSR-CRG2018-3711, REP/1/3268-01-01 Acknowledgements: 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).

PY - 2021/6/4

Y1 - 2021/6/4

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10754/669383

UR - https://linkinghub.elsevier.com/retrieve/pii/S0025326X21005488

U2 - 10.1016/j.marpolbul.2021.112514

DO - 10.1016/j.marpolbul.2021.112514

M3 - Article

C2 - 34091253

SN - 0025-326X

VL - 169

SP - 112514

JO - Marine Pollution Bulletin

JF - Marine Pollution Bulletin

ER -

Bayesian identification of oil spill source parameters from image contours

Abstract

Bibliographical note

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