Study On Maritime Traffic Density Calculation And Maritime Hotspots Discovery Based On AIS Data

Maritime information analysis is a main method for marine supervision departments to know and grasp marine situation. With the great development of marine transportation industry, more requirements about maritime information analysis has been asked by marine supervision departments and various kinds of informationize analysis methods has appeared. The appearance and widely using of AIS makes it possible to get real-time information of vessel. Maritime information analysis based on AIS data can analyze and mine real-time marine situation, which overcomes the poor timeliness of traditional methods. However, currently research on maritime affairs information analysis based on AIS data is still in the beginning step without high reliability and universality. Thus, it is an urgent issue to discuss and find out a more reliable and universal method of maritime information analysis based on AIS data.As the direct mirror of marine traffic situation, the maritime traffic density has always been focused a lot by marine supervision departments. Currently, maritime traffic density is obtained mainly by manual observations qualitatively. In terms of the quantitative analysis, we often measure it by the number of AIS messages, which cannot show the maritime traffic situation comprehensively and accurately. For the purpose of solving these problems, this paper proposes a grid-based method to characterize the maritime traffic density, which takes different aspects, including the number of passing ships,the sum of crossing time, the number of messages sent, the interval between messages sent, to show the maritime traffic situation. Based on the idea mentioned above, design and implement an algorithm for maritime traffic density calculation.The maritime hotspots refers to the zone in which ships appear and act frequently. Therefore, they are the important area during the maritime supervision. Previously, discovering for maritime hotspots mainly depends on human reservation and electronic chart with low timeliness and incompleteness. Aiming to solving this problem, this paper offers a way based on clustering analysis to find the maritime hotspots, and optimizes the agglomerative hierarchical algorithm in aspects of time complexity, space complexity and optimal clustering number.In order to evaluate the effectiveness of proposed methods mentioned above, this paper takes the real AIS data as research objective to conduct experiment analysis for maritime traffic density calculation and maritime hotspots discovering respectively. It verified the effectiveness for both of these two methods, which is of great positive meaning for maritime information analysis.