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Detection of maritime traffic anomalies using Satellite-AIS and multisensory satellite imageries: Application to the 2021 Suez Canal obstruction

Published online by Cambridge University Press:  15 August 2022

Ahmed Harun-Al-Rashid ,
Chan-Su Yang  and
Dae-Woon Shin
Ahmed Harun-Al-Rashid
Affiliation:
Marine Security and Safety Research Center, Korea Institute of Ocean Science & Technology, Busan, Korea Department of Aquatic Resource Management, Sylhet Agricultural University, Sylhet, Bangladesh
Chan-Su Yang*
Affiliation:
Marine Security and Safety Research Center, Korea Institute of Ocean Science & Technology, Busan, Korea Department of Convergence Study on the Ocean Science and Technology, Ocean Science and Technology School, Korea Maritime & Ocean University, Busan, Korea Applied Ocean Sciences, University of Science & Technology, Daejeon, Korea
Dae-Woon Shin
Affiliation:
Marine Security and Safety Research Center, Korea Institute of Ocean Science & Technology, Busan, Korea Department of Convergence Study on the Ocean Science and Technology, Ocean Science and Technology School, Korea Maritime & Ocean University, Busan, Korea
*
*Corresponding author. E-mail: yangcs@kiost.ac.kr.
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Abstract

This study summarises the scenario of maritime traffic anomalies, like the increased congestion and U-turn of ships caused by the ship grounding in the Suez Canal in March 2021. Here, satellite automatic identification system based ship trajectories, and Sentinel-1 and Sentinel-2 images based ship positions are analysed after subdividing the study area into seas, lakes and canals. The results show that the blockage affected the maritime traffic for more than three weeks, waiting ship numbers increased from 5 to 122, and daily one to three ships made a U-turn between 23 and 31 March in the Gulf of Suez. Ship density also increased to more than double in Bitter Lakes with a minimum waiting time of 7 days. Hence, to avoid such prolonged waiting of ships, we propose a warning method based on the sharp speed decrease rate, U-turn and congestion.

Keywords

automatic identification systemmaritime surveillancetraffic anomalySentinel-1Sentinel-2

Information

Type
Research Article
Information
The Journal of Navigation , Volume 75 , Issue 5 , September 2022 , pp. 1082 - 1099
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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