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|Title:||Automatic Generation of Geographical Networks for Maritime Traffic Surveillance|
|Authors:||FERNANDEZ ARGUEDAS VIRGINIA; PALLOTTA Giuliana; VESPE MICHELE|
|Citation:||FUSION 2014 17th International Conference on Information Fusion|
|Publisher:||IEEE (Institute of Electrical and Electronics Engineer)|
|Type:||Articles in periodicals and books|
|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 vessels 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.|
|JRC Directorate:||Space, Security and Migration|
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