While pressure on marine ecosystems leading to declines in global fish catches have been attributed to excessive fishing and to unregulated and unreported fishing, existing management practices have yet to fully address these declines. Estimation of spatial and temporal distribution of fisheries resources and the extent of fishing impacts on marine ecosystems using vessel trajectories has become central in recent studies. This study proposed the use of trajectories of 771 Korean coastal and offshore fishing vessels and one-year fish landing data to estimate variations in commercial fish species, vessel, and fishing gear activity distributions in the waters around Jeju island. A set of standards were applied to identify individual fishing tracks of major gears and uniformly distributed catch to fishing segments of trajectories to produce spatio-temporal distributions of catch, fishing activities, and vessel reliance on fishing grounds at a fine spatial scale. The method identified reference points that can inform management at local and regional scales. We discuss the opportunities of combining larger datasets collected over a longer period and applying predictive modeling techniques in making extensive assessments, including climate change impacts on fishing activities that can inform resource management and marine spatial planning.

The rapid development and adoption of automatic identification systems as surveillance tools have resulted in the widespread application of data analysis technology in maritime surveillance and route planning. Traditional, manual, experience-based route planning has been widely used owing to its simplicity. However, the method is heavily dependent on officer experience and is time-consuming. This study aims to extract shipping routes using unsupervised machine-learning algorithms. The proposed three-step approach: maneuvering point detection, waypoint discovery, and traffic network construction was used to construct a maritime traffic network from historical AIS data, which quantitatively reflects ship characteristics by ship length and ship type, and can be used for route planning. When the constructed maritime traffic network was compared to the macroscopic ship traffic flow, the Symmetrized Segment-Path Distance (SSPD) metric returned lower values, indicating that the constructed traffic network closely resembles the routes ships transit. The result indicates that the proposed approach is effective in extracting a route from the maritime traffic network.

No abstract