Abstract
Since the spread of the coronavirus disease 2019 (COVID-19) pandemic, the transportation of cargo by ship has been seriously impacted. In order to prevent and control maritime COVID-19 transmission, it is of great significance to track and predict ship sailing behavior. As the nodes of cargo ship transportation networks, ports of call can reflect the sailing behavior of the cargo ship. Accurate hierarchical division of ports of call can help to clarify the navigation law of ships with different ship types and scales. For typical cargo ships, ships with deadweight over 10,000 tonnages account for 95.77% of total deadweight, and 592,244 berthing ships’ records were mined from automatic identification system (AIS) from January to October 2020. Considering ship type and ship scale, port hierarchy classification models are constructed to divide these ports into three kinds of specialized ports, including bulk, container, and tanker ports. For all types of specialized ports (considering ship scale), port call probability for corresponding ship type is higher than other ships, positively correlated with the ship deadweight if port scale is bigger than ship scale, and negatively correlated with the ship deadweight if port scale is smaller than ship scale. Moreover, port call probability for its corresponding ship type is positively correlated with ship deadweight, while port call probability for other ship types is negatively correlated with ship deadweight. Results indicate that a specialized port hierarchical clustering algorithm can divide the hierarchical structure of typical cargo ship calling ports, and is an effective method to track the maritime transmission path of the COVID-19 pandemic.
Highlights
With the popularity of ship-borne automatic identification systems, the data of ship trajectory have increased exponentially, which provide data support for the analysis of ship sailing patterns
What’s more, bulk ports are divided into handy size, canal size, and cape size ports, the number of which are 642, 338, and 145 respectively; container ports are divided into 1st to 3rd generation, 4th to 5th generation, and 6th generation container ports, the numbers of which are 447, 149, and 88 respectively; tanker ports are divided into handy size, canal size, and Very large crude carrier (VLCC) size, the number of which are 634, 416, and 163 respectively
Calculating the arrival frequency degree of port for each specialized port, the results indicate that top 66 handy size bulk ports account for 71%, canal size bulk ports account for 80.5%, and cape size bulk ports account for 94%
Summary
With the popularity of ship-borne automatic identification systems, the data of ship trajectory have increased exponentially, which provide data support for the analysis of ship sailing patterns. Sustainability 2021, 13, 1089 important to use the big data of ship automatic identification systems to monitor ship navigation behavior. In order to effectively monitor the ship’s navigation behavior, the information of the ship’s berthing port is mined according to the ship’s speed and position, based on the typical cargo ship trajectory data provided by the ship-borne automatic identification system. The probability distribution of ships berthing at corresponding ports (ship type and size) can accurately reflect the behavior pattern of ships, which could provide an effective way to track the marine transmission path of the COVID-19 pandemic. This paper ends with a conclusion including suggestions for future works
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