| 海洋运输网络研究进展与趋势探讨 |
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| 引用本文： | 方志祥,余红楚,黄守倩.海洋运输网络研究进展与趋势探讨[J].地球信息科学,2018,20(5):554-563. |
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| 作者姓名： | 方志祥 余红楚 黄守倩 |
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| 作者单位： | 1. 武汉大学 测绘遥感信息工程国家重点实验室,武汉 4300792. 时空数据智能获取技术与应用教育部工程研究中心,武汉 430079 |
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| 基金项目： | 中国科学院重点项目(ZDRW-ZS-2016-6-3);国家自然科学基金项目（41771473）;国家重点研发计划项目(2017YFC1405302);测绘遥感信息工程国家重点实验室专项科研经费资助 |
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| 摘 要： | 随着经济全球一体化快速发展,国际海运贸易的规模不断扩大,全球海运网络研究成为当前的研究热点领域。该研究是海洋运输、地理信息科学、数学物理、统计科学、复杂网络科学、大数据科学、计算机科学等多学科交叉领域共同关注的研究主题,对国家宏观战略与政策制定具有重要作用。本文总结了海运网络研究数据基础、理论模型和研究方法,包括数学物理统计理论方法,基于复杂网络的分析方法、数据挖掘理论方法等,然后从海运网络运输模式设计与优化,网络结构静动态特征,网络结构和交通流演化机制等角度总结海运网络的研究进展、分析所存在的问题,提出海运网络研究在跨学科跨领域研究方法的交叉、多源异构数据融合分析、理论与实际应用结合等方面的未来研究趋势。
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| 关 键 词： | 船舶自动识别系统 船舶轨迹 海运网络 复杂网络 运输模式 拓扑结构 演化机制 |
| 收稿时间： | 2018-04-01 |
Review of Research Works on Maritime Network |
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| FANG Zhixiang,YU Hongchu,HUANG Shouqian.Review of Research Works on Maritime Network[J].Geo-information Science,2018,20(5):554-563. |
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| Authors: | FANG Zhixiang YU Hongchu HUANG Shouqian |
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| Institution: | 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China2. Engineering Research Center for Spatiotemporal Data Smart Acquisition and Application, Ministry of Education of China, Wuhan 430079, China |
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| Abstract: | With the rapid development of economic globalization, the scale of international trade has continued to be expanded. Global maritime network are attracting much attention from researchers in multidisciplinary areas, such as ocean transportation, geographical information science, mathematical physics, statistics science, complex network science, big data science, computer science and so on. The maritime network studies become hot research topics among them, which plays an important role in designing affective and sustainable macro strategies and policies for countries. This paper summarizes the data sources, theoretical models and research methods in maritime network studies, for example, the used data includes the statistics data and Automatic Identification System （AIS） traced vessel trajectory data, the used methods are from mathematics, physics and statistical theory methods, complex network science, data mining theory, etc. Then, this paper reviewed the research works of maritime network from the perspectives of maritime network transportation mode, network structure characteristics, and evolution mechanism of maritime network, and concluded the existing problems in these perspectives. Previous studies on maritime transportation mode design and optimization are useful to improve shipping service quality, assess the feasibility of new routes and improve the efficiency and capacity of the transportation system. The researches for maritime network structure reveal the static （i.e. network connectivity, clustering coefficient, mean shortest path lengths, closeness centrality, betweeness centrality, and straightness centrality） and dynamic characteristics （i.e. spatial-temporal changes, hierarchical characteristics, dynamic connectivity） through the approaches of modelling, statistical and empirical analyzing. The studies on evolution mechanism for maritime network focus on the structure evolution and traffic flow evolution, which are helpful to identify the influential factors and to predict traffic flow in the maritime network. The future promising research avenues on maritime network include involving experts from multidisciplinary areas, using the research methods from cross-domains, integrating multi-source heterogeneous data, and linking the theoretical analysis with practical application problems. |
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| Keywords: | automatic identification system vessel trajectory maritime network complex network transportation mode topological structure evolution mechanism |
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