Extraction of Frequently Active Areas of Ships Based on Advanced Grid Density Peak Clustering

The cognition of the frequent activity areas of ships based on AIS data is of great significance in reducing port navigation risks and improving the efficiency of ships entering and leaving ports. Traditional extraction methods only consider spatial information and ignore the impact of temporal information on clustering results, resulting in inaccurate extraction of frequently active areas. We propose an advanced grid density peak clustering method (AGDPC) to extract frequently active areas, which can advanced select cluster centers and density thresholds to solve the problem that grid density peak clustering methods cannot advanced select cluster centers. The improved grid density peak clustering method is used to extract frequent ship motion regions under a single spatial-temporal granularity according to a given spatial-temporal granularity. Then, we fuse multiple ship frequent activity areas to obtain multi-temporal and spatial granularity ship frequent activity areas. Experimental results show that this method can extract frequent motion are-as more accurately than traditional methods, and better reflect the ship’s navigation rules.