Spatial Cluster Detection for the Fishing Vessel Monitoring Systems

Fishing vessel monitoring system (VMS) is an effective tool of fisheries monitoring, control and surveillance measures to counter over-fishing. It can also help the coast guard to safeguard vessels more efficiently. As VMS is widely implemented, more and more efforts focus on mining the VMS database to discover knowledge and clues that would further enhance the benefits .This paper reports on a density-based spatial cluster detection method developed for and implemented into the VMS of Taiwan. The request was to constantly identify wherever there are at least three fishing vessels within 10 nautical miles of range. The proposed solution was based on DBSCAN clustering algorithm. The performances in accuracy and rum-time were evaluated and improved with vessel position prediction, partitioning of datasets, data structure and algorithm design. With the promising results, this solution has been recognized by the fisheries management and VMS operation experts to be of many extended use in VMS.