Investigating maritime traffic routes: integrating AIS data and topographic statistics
This paper presents an innovative integration of topographic statistics with automatic identification system data to identify the distribution of conventionally formed maritime routes. This methodology utilizes navigation frequency data to precisely discern the locations and distribution of linear maritime routes. A key strength lies in the explicit identification of crucial points of connectivity, including intersections and confluences, which contribute to the construction of maritime route networks. This advantage becomes evident by providing a nuanced depiction of individual route centerlines and a detailed spatial representation based on quantitative evidence of vessel navigation conventions. This enhances the accuracy of identifying major routes and facilitates their precise location and distribution, and is particularly adept at supporting maritime route establishment and spatial management, the methodology provides quantitative evidence for key points, such as intersections and confluence areas. In addition to conventional applications, this methodology enhances maritime safety, contributes to effective marine spatial management policies, identifies suitable locations for new maritime activities, and resolves potential spatial conflicts.
Authors
- Chan Woong Kim (ORCID: https://orcid.org/0000-0001-7821-8980)
- Wan Hee Kim (ORCID: https://orcid.org/0000-0003-4541-2036)
- Jae Young Park (ORCID: https://orcid.org/0000-0002-6664-6846)
- Sung‐Jin Cho (ORCID: https://orcid.org/0000-0002-2445-6905)
- Jongseo Yim (ORCID: https://orcid.org/0000-0002-5812-6453)
Institutions
- Korea Maritime Institute (KR)
- C-Green Technology (Sweden) (SE)
- Green Chemistry (PL)
- University of Tennessee at Knoxville (US)
Publication Details
- Journal
- Maritime Policy & Management
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1080/03088839.2024.2428646
- Citations
- 4
- Primary Topic
- Maritime Navigation and Safety
- Type
- article
- Field-Weighted Citation Impact
- 1.34
Funders
- Korea Institute of Energy Technology Evaluation and Planning