Journal of Geographical Sciences ›› 2018, Vol. 28 ›› Issue (7): 937-956.doi: 10.1007/s11442-018-1514-9

• Special Issue: Geopolitical Environment Simulation on the Belt and Road Region • Previous Articles     Next Articles

Maritime network dynamics before and after international events

Zhixiang FANG1,3(), Hongchu YU1,*(), Feng LU2, Mingxiang FENG1, Meng HUANG1   

  1. 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
    2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    3. Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China
  • Received:2017-10-17 Online:2018-07-20 Published:2018-07-20
  • Contact: Hongchu YU;
  • About author:

    Author: Fang Zhixiang (1977-), Professor, specializing in transport geography, human behavior modeling, space-time GIS and intelligent navigation. E-mail:

  • Supported by:
    Key Project of the Chinese Academy of Sciences, No.ZDRW-ZS-2016-6-3;The National Key Research and Development Program of China, No.2017YFB0503802;National Natural Science Foundation of China, No.40971233, No.41771473;LIESMARS Special Research Funding


Investigating the influence of international events on global maritime networks is a challenging task that must comprehensively incorporate geographical, political, and maritime sciences. Understanding global maritime network dynamics is an initial and critical step in this investigation. This study proposes an automatic identification system (AIS)-based approach to understanding maritime network dynamics before and after international events. In this approach, a spatiotemporal modeling method is introduced to measure the similarity in shipping trends before and after international events. Then, a spatiotemporal analytic framework is proposed to understand the maritime network dynamics by grouping similar situation, and assessing possible indirect effects within a network. Finally, three case studies of international events, military conflict, lifted economic sanctions, and government elections, were used to investigate the observed network dynamics possibly affected by international events. The results indicate that container, tanker, and bulk shipping between India and its connected countries all declined more than 69% after military conflicts between India and Pakistan in August 2015. Tanker shipping between Iran and the United Arab Emirates increased 51% after economic sanctions on Iran were lifted. Container shipping between Sri Lanka and Singapore, Malaysia, and India increased more than 74% after the general election in Sri Lanka. These investigations demonstrate the feasibility of the proposed approach in assessing the possible effects of international events on maritime network dynamics.

Key words: global maritime network, fluctuation dynamics, international events, spatiotemporal similarity