Identification of suspicious behavior through anomalies in the tracking data of fishing vessels

Jorge P. Rodríguez, Xabier Irigoien, Carlos M. Duarte, Víctor M. Eguíluz

Research output: Contribution to journalArticlepeer-review

Abstract

Automated positioning devices can generate large datasets with information on the movement of humans, animals and objects, revealing patterns of movement, hot spots and overlaps among others. However, in the case of Automated Information Systems (AIS), attached to vessels, observed strange behaviors in the tracking datasets may come from intentional manipulation of the electronic devices. Thus, the analysis of anomalies can provide valuable information on suspicious behavior. Here, we analyze anomalies of fishing vessel trajectories obtained with the Automatic Identification System. The map of silent anomalies, those that occur when positioning data are absent for more than 24 hours, shows that they are most likely to occur closer to land, with 87.1% of anomalies observed within 100 km of the coast. This behavior suggests the potential of identifying silence anomalies as a proxy for illegal activities. With the increasing availability of high-resolution positioning of vessels and the development of powerful statistical analytical tools, we provide hints on the automatic detection of illegal activities that may help optimize the management of fishing resources.

Original languageEnglish
Article number23
Number of pages13
JournalEPJ Data Science
Volume13
DOIs
Publication statusPublished - 21 Mar 2024
Externally publishedYes

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