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

Cited 4 time in WEB OF SCIENCE Cited 4 time in Scopus
Title
Detection of maritime traffic anomalies using Satellite-AIS and multisensory satellite imageries: Application to the 2021 Suez Canal obstruction
Author(s)
Harun-Al-Rashid, Ahmed; Yang, Chan Su; Shin, Dae Woon
KIOST Author(s)
Yang, Chan Su(양찬수)Shin, Dae Woon(신대운)
Alternative Author(s)
AHMED; 양찬수; 신대운
Publication Year
2022-09
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.
ISSN
0373-4633
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/43184
DOI
10.1017/s0373463322000364
Bibliographic Citation
Journal of Navigation, v.75, no.5, pp.1082 - 1099, 2022
Publisher
Cambridge University Press
Keywords
automatic identification system; maritime surveillance; traffic anomaly; Sentinel-1; Sentinel-2
Type
Article
Language
English
Document Type
Article; Early Access
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