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The South China Sea, as critical waters of the 21st Century Maritime Silk Road (Zhong & White, 2017), is one of the most active waters in the world at present and is also a key area of high concern for countries around the world. Many scholars have been studying the waters of the South China Sea from multiple dimensions; the safety of ship navigation is the most important among these topics (Rosenberg & Chung, 2008). In view of the limitation of data sources in the South China Sea, most of the previous studies have focused on the port waterways along the South China Sea, including Singapore and the Strait of Malacca (Weng et al., 2012), and the Pearl River Delta region of China, etc. (Sasa et al., 2021). Few of them have analyzed the overall traffic conditions of the whole South China Sea and the key waters in depth (Du et al., 2016).
Figure 1. Recommended routes for major merchant ships in South China Sea
As Figure 1 shows, according to the recommended routes in the authoritative book World Ocean Routes (Jenkins, 1973), the recommended routes in the South China Sea are mainly in the southwest and northeast directions and are generally divided into the eastern, central, and western routes, of which the central route is the main route and the two directions of the southern Taiwan Strait and the Bashi Strait through which the route passes are the key waters.
At present, the installation of AIS data transceiver equipment on low-orbiting satellites has served the modern demand for larger “capacity” data exchange (Greidanus et al., 2016). The mining of ship AIS data to build a maritime navigation characteristics map is one of the important means to track the global ship behavior characteristics (Vespe et al., 2015) and regulate the ship order (Yliskylä-Peuralahti & Gritsenko, 2014). By analyzing and visualizing ship movement patterns, traffic density, route preferences, and other relevant navigation information to provide a comprehensive depiction of maritime navigation characteristics in a specific area or region.
There is little research on the spatiotemporal characteristics, key areas, and port spatial information of water transportation in the South China Sea by domestic and foreign scholars. Based on AIS data, using computer technologies and methods such as time-space division, linear density analysis, cluster analysis, and complex network, the paper explores the time-space characteristics of water traffic in the South China Sea waters, identifies the key areas of the South China Sea waters, divides the levels of ports, and provides decision-making reference for the water regulatory authorities to optimize the channel and formulate port management policies.
The technology roadmap of this paper is as follows. Firstly, this article extracts trajectory points from the AIS database and uses Python for voyage recognition, achieving the preprocessing process from trajectory points to trajectory lines. Secondly, the time-space division result map and linear density analysis map are obtained by using the time-space division of route set, linear density analysis, time-space statistical analysis, and other methods to explore the time-space distribution characteristics of water traffic in the South China Sea waters. Then, based on hierarchical clustering, the ship berthing points are clustered to identify key areas. Finally, this paper uses the complex network method to build the port shipping network, analyze the centrality of the port network, divide the port hierarchy, obtain the centrality analysis diagram and port hierarchy result diagram, and mine the characteristics of port spatial information.