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.


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    Title :

    Automatic generation of geographical networks for maritime traffic surveillance




    Publication date :

    2014-07-01


    Size :

    1665346 byte



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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