Spatial-temporal big data analysis of ship avoidance patterns during typhoon approaches SCIE SCOPUS

Cited 0 time in WEB OF SCIENCE Cited 0 time in Scopus
Title
Spatial-temporal big data analysis of ship avoidance patterns during typhoon approaches
Author(s)
Lee, Jeongseok; Kim, Minkyeong; Kim, Bo Ram; Kim, Tae Kyun; Lee, Chol Young; Park, Yong Gil
KIOST Author(s)
Lee, Jeongseok(이정석)Kim, Bo Ram(김보람)Kim, Tae Kyun(김태균)Lee, Chol Young(이철용)Park, Yong Gil(박용길)
Alternative Author(s)
이정석; 김민경; 김보람; 김태균; 이철용; 박용길
Publication Year
2025-03
Abstract
Typhoons pose a significant threat to maritime safety, affecting numerous ships and ports in South Korea annually. This study analyzes ship avoidance patterns during Typhoons SOULIK and KONG-REY using Automatic Identification System data. Through K-means clustering, anchorage and drifting patterns both inside and outside territorial waters are identified. A spatial-temporal analysis, utilizing minimum bounding geometry and centroid comparison, assesses the positions of ship clusters relative to the typhoon's path. The analysis recommends maintaining a minimum distance of 300 km from the typhoon's path for safe avoidance. Statistically significant differences in ship patterns under non-typhoon conditions were also identified using Kuiper's test. These findings emphasize the importance of data-driven decisions for enhancing maritime safety and developing typhoon avoidance strategies.
ISSN
0029-8018
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/46626
DOI
10.1016/j.oceaneng.2025.120316
Bibliographic Citation
Ocean Engineering, v.320, 2025
Publisher
Pergamon Press Ltd.
Keywords
Typhoon; Big AIS data; K-means; Spatial-temporal analysis; Avoidance pattern
Type
Article
Language
English
Files in This Item:
There are no files associated with this item.

qrcode

Items in ScienceWatch@KIOST are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse