FVRD: Fishing Vessels Relationships Discovery System Through Vessel Trajectory

Abstract

Vessel monitoring system (VMS) is an effective tool for the quantified study of fishing. As the fishing vessels equipped with VMS clients, a large amount of trajectory data has been collected, which brings a new opportunity for fishing research. According to fishery safety production regulations, fishing vessels should perform grouping operations based on actual conditions, but the group information cannot be collected by the VMS. In this paper, we propose the Fishing Vessels Relationships Discovery system (FVRD) by calculating the interaction time among fishing vessels and then using it as a weight to generate a relationship network. The experiment of the proposed FVRD on the vessel dataset of Zhejiang Province reveals that the generated fishing community is consistent with the type of operation of the fishing vessels, which means the proposed method is effective. The experiment also indicates that the fishing vessel relationship network has the characteristics of small-world and scale-free that is similar to the human social network, Moreover, FVRD shows that 86.78% of vessels share the collaboration relationships over one week, 10.72% of vessels are in the long-term cooperation, confirming the regulation that most fishing vessels are sailing together for fishing.

Keywords

• VMS
• FVRD
• data visualization
• fishing density
• trajectory analysis
• group