A Data Visualization Approach for Intersection Analysis using AIS Data

Ricardo Pereira, Pedro Abreu, Evgheni Polisciuc, Penousal Machado

Abstract

Automatic Identification System data has been used in several studies with different directions like traffic forecasting, pollution control or anomalous behavior detection in vessels trajectories. Considering this last subject, the intersection between vessels is often related with abnormal behaviors, but this topic has not been exploited yet. In this paper an approach to assist the domain experts in the task of analyzing these intersections is introduced, based on data processing and visualization. The work was experimented with a proprietary dataset that covers the Portuguese maritime zone, containing an average of 6460 intersections by day. The results show that several intersections were only noticeable with the visualization strategies here proposed.

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Paper Citation


in Harvard Style

Pereira R., Abreu P., Polisciuc E. and Machado P. (2019). A Data Visualization Approach for Intersection Analysis using AIS Data.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, ISBN 978-989-758-354-4, pages 208-215. DOI: 10.5220/0007312802080215


in Bibtex Style

@conference{ivapp19,
author={Ricardo Pereira and Pedro Abreu and Evgheni Polisciuc and Penousal Machado},
title={A Data Visualization Approach for Intersection Analysis using AIS Data},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,},
year={2019},
pages={208-215},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007312802080215},
isbn={978-989-758-354-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,
TI - A Data Visualization Approach for Intersection Analysis using AIS Data
SN - 978-989-758-354-4
AU - Pereira R.
AU - Abreu P.
AU - Polisciuc E.
AU - Machado P.
PY - 2019
SP - 208
EP - 215
DO - 10.5220/0007312802080215