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Maritime Data Analytics

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Guide to Maritime Informatics

Abstract

The goal of mobility data analytics is to extract valuable knowledge out of a plethora of data sources that produce immense volumes of data. Focusing on the maritime domain, this relates to several challenging use-case scenarios, such as discovering valuable behavioural patterns of moving objects, identifying different types of activities in a region of interest, estimating fishing pressure or environmental fingerprint, etc. In this chapter, we focus on the exploration, preparation of data and application of several offline maritime data analytics techniques. Initially, we present several methods that assist an analyst to explore and gain insight of the data under analysis. Subsequently, we study several preprocessing techniques that aim to clean, transform, compress and partition long GPS traces into meaningful portions of movement. Finally, we overview some representative maritime knowledge discovery techniques, such as trajectory clustering, group behaviour identification, hot-spot analysis, frequent route or network discovery and data-driven predictive analytics methods.

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Notes

  1. 1.

    Characteristic points of trajectories include their start and end points, the points of significant turns, and the points of significant stops (pauses in the movement). If a trajectory has long straight segments, it is also necessary to take representative points from these segments too.

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Authors and Affiliations

  1. University of Piraeus, Karaoli & Dimitriou St. 80, Piraeus, Greece

    Panagiotis Tampakis, Stylianos Sideridis, Panagiotis Nikitopoulos, Nikos Pelekis & Yannis Theodoridis

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  1. Panagiotis Tampakis
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  2. Stylianos Sideridis
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  3. Panagiotis Nikitopoulos
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  4. Nikos Pelekis
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  5. Yannis Theodoridis
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Correspondence to Panagiotis Tampakis .

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Editors and Affiliations

  1. Department of Maritime Studies, University of Piraeus, Piraeus, Greece

    Alexander Artikis

  2. Department of Product and Systems Design Engineering, University of the Aegean, Syros, Greece

    Dimitris Zissis

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Tampakis, P., Sideridis, S., Nikitopoulos, P., Pelekis, N., Theodoridis, Y. (2021). Maritime Data Analytics. In: Artikis, A., Zissis, D. (eds) Guide to Maritime Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-61852-0_4

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  • DOI: https://doi.org/10.1007/978-3-030-61852-0_4

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