Application of trajectory clustering and regionalization to ocean eddies in the South China Sea

Moving characteristics of ocean eddy have become one of the research foci, based on more advanced detection and tracking method. This study applied trajectory data mining to the analysis of eddies trajectories in the South China Sea (SCS), and experimented with two methods. One of them identified moving patterns of eddies by trajectory clustering and obtained representative paths. The other one discovered flow patterns using regionalization method with contiguous constrained, which partitioned of SCS into 4 regions. In the SCS, eddies mainly propagate in three parts with various moving characteristics and present regional flow patterns. Both of these methods validate the effectiveness of the application of trajectory data mining to the ocean eddies study.