Visible to the public Automatic generation of geographical networks for maritime traffic surveillance

TitleAutomatic generation of geographical networks for maritime traffic surveillance
Publication TypeConference Paper
Year of Publication2014
AuthorsFernandez Arguedas, V., Pallotta, G., Vespe, M.
Conference NameInformation Fusion (FUSION), 2014 17th International Conference on
Date PublishedJuly
Keywordsanomaly detection, automatic generation, geographic information systems, geographical maritime network, hierarchical graph based representations, historical vessel positioning data, Knowledge discovery, knowledge discovery process, marine systems, Maritime Knowledge Discovery, maritime shipping lanes, Maritime Surveillance, Maritime Traffic Networks, maritime traffic surveillance, network nodes, Ports (Computers), route segments, security, Standards, surveillance, track reconstruction, traffic, Trajectory, Trajectory Mining and Synthetic Trajectories
Abstract

In this paper, an algorithm is proposed to automatically produce hierarchical graph-based representations of maritime shipping lanes extrapolated from historical vessel positioning data. Each shipping lane is generated based on the detection of the vessel behavioural changes and represented in a compact synthetic route composed of the network nodes and route segments. The outcome of the knowledge discovery process is a geographical maritime network that can be used in Maritime Situational Awareness (MSA) applications such as track reconstruction from missing information, situation/destination prediction, and detection of anomalous behaviour. Experimental results are presented, testing the algorithm in a specific scenario of interest, the Dover Strait.

Citation Key6915990