Vessel Trajectory Data Mining: A Review

TitleVessel Trajectory Data Mining: A Review
Publication TypeJournal Article
Year2025
AuthorsTroupiotis-Kapeliaris, A, Kastrisios, C, Zissis, D
JournalIEEE Access
Volume13
Pages4827-4856
Date Published03 January
PublisherIEEE
Place PublishedIEEE Access
Keywordsdata mining, descriptive analytics, maritime monitoring, pattern mining, predictive analytics, spatio-temporal data mining, trajectory analytics

Recent advancements in sensor and tracking technologies have facilitated the real-time tracking of marine vessels as they traverse the oceans. As a result, there is an increasing demand to analyze these datasets to derive insights into vessel movement patterns and to investigate activities occurring within specific spatial and temporal contexts. This survey offers a comprehensive review of contemporary research in trajectory data mining, with a particular focus on maritime applications. The article collects and evaluates state-of-the-art algorithmic approaches and key techniques pertinent to various use case scenarios within this domain. Furthermore, this study provides an in-depth analysis of recent developments in trajectory data mining as applied to the maritime sector, identifying available data sources and conducting a detailed examination of significant applications, including trajectory forecasting, activity recognition, and trajectory clustering.

DOI10.1109/ACCESS.2025.3525952
Refereed DesignationRefereed