Detection of maritime traffic anomalies using Satellite-AIS and multisensory satellite imageries: Application to the 2021 Suez Canal obstruction
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Title
- Detection of maritime traffic anomalies using Satellite-AIS and multisensory satellite imageries: Application to the 2021 Suez Canal obstruction
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Author(s)
- Harun-Al-Rashid, Ahmed; Yang, Chan Su; Shin, Dae Woon
- KIOST Author(s)
- Yang, Chan Su(양찬수); Shin, Dae Woon(신대운)
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Alternative Author(s)
- AHMED; 양찬수; 신대운
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Publication Year
- 2022-09
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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.
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ISSN
- 0373-4633
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/43184
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DOI
- 10.1017/s0373463322000364
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Bibliographic Citation
- Journal of Navigation, v.75, no.5, pp.1082 - 1099, 2022
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Publisher
- Cambridge University Press
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Keywords
- automatic identification system; maritime surveillance; traffic anomaly; Sentinel-1; Sentinel-2
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Type
- Article
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Language
- English
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Document Type
- Article; Early Access
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