Journal of Geodesy and Geoinformation Science ›› 2022, Vol. 5 ›› Issue (2): 60-74.doi: 10.11947/j.JGGS.2022.0207

• Special Issue • Previous Articles     Next Articles

Spatial Interaction Network Analysis of Crude Oil Trade Relations between Countries along the Belt and Road

Qixin WANG1(),Kun QIN1,2(),Donghai LIU1,Gang XU2,3,Yanqing XU1,2,Yang ZHOU1,Rui XIAO1,2   

  1. 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
    2. Geo-computation Center for Social Sciences, Wuhan University, Wuhan 430079, China
    3. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
  • Received:2021-10-11 Accepted:2022-05-08 Online:2022-06-20 Published:2022-07-22
  • Contact: Kun QIN;
  • About author:Qixin WANG (1990—), male, PhD candidate, majors in spatiotemporal big data analysis. E-mail:
  • Supported by:
    National Natural Science Foundation of China(42171448);Key Laboratory of National Geographic Census and Monitoring, Ministry of Nature Resources(2020NGCMZD03)


Based on the theories and methods of complex network, crude oil trade flows between countries along the Belt and Road (B&R, hereafter) are inserted into the Geo-space of B&R and form a spatial interaction network which takes the countries as nodes and takes the trade relations as edges. The networked mining and evolution analysis can provide important references for the research on trade relations among the B&R countries and the formulation of trade policy. This paper researches and discusses the construction, statistical analysis, top networks and stability of the crude oil trade network between the B&R countries from 2001 to 2020 from the perspectives of Geo-Computation for Social Sciences (GCSS) and spatial interaction. Firstly, evolutions of out-degree, in-degree, out-strength and in-strength of the top 10 countries in the crude oil trade network are computed and analyzed. Secondly, the top network method is used to explore the evolution characteristics of hierarchical structures. And finally, the sequential evolution characteristics of the crude oil trade network stability are analyzed utilizing the network stability measure method based on the trade relationship autocorrelation function. The analysis results show that Russia has the largest out-degree and out-strength, and China has the largest in-degree and in-strength. The crude oil trade volume of the top 10 import and export networks between 2001—2020 accounts for over 90% of the total trade volume of the crude oil trade network, and the proportion remains relatively stable. However, the stability of the network showed strong fluctuations in 2009, 2012 and 2014, which may be closely related to major international events in these years, which could furtherly be used to build a correlation model between network volatility and major events. This paper explores how to construct and analyze the spatial interaction network of crude oil trade and can provide references for trade relations research and trade policy formulation of B&R countries.

Key words: spatial interaction network; Geo-Computation for Social Sciences (GCSS); the Belt and Road Initiative (BRI); trade relation; network stability