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
Zhixiang FANG1,3(), Hongchu YU1,*(
), Feng LU2, Mingxiang FENG1, Meng HUANG1
Received:
2017-10-17
Online:
2018-07-20
Published:
2018-12-28
Contact:
Hongchu YU
E-mail:zxfang@whu.edu.cn;hongshuxifan8140@163.com
About author:
Author: Fang Zhixiang (1977-), Professor, specializing in transport geography, human behavior modeling, space-time GIS and intelligent navigation. E-mail:
Supported by:
Zhixiang FANG, Hongchu YU, Feng LU, Mingxiang FENG, Meng HUANG. Maritime network dynamics before and after international events[J].Journal of Geographical Sciences, 2018, 28(7): 937-956.
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Table 1
Summary of research on maritime networks"
Research category | Research contents |
---|---|
Structure and dynamics | Spatial structure (Xu et al., 2015); regional dynamics (Ducruet and Notteboom 2012; ; Yu et al., 2017); time dynamics (Ducruet, 2016); spatial heterogeneity (Liu et al., 2017; Li et al., 2016); reachability (Li et al., 2014b), and local strength and global weakness (Ducruet et al., 2009). |
Network and flows | Network diversity and maritime flows (Ducruet, 2013; Dinwoodie et al., 2013); statistical properties, including distribution extent, correlations, weight distribution, strength distribution, average shortest path length, line length distribution, and centrality measures (Hu and Zhu, 2009; Fugazza, 2017); centrality and vulnerability (Laxe et al., 2012; Viljoen and Joubert, 2016; Wu et al., 2017; Wang et al., 2016); connectivity and complexity (Jiang et al., 2015; Tian et al., 2007; Liu and Hu et al., 2017); inequality (Xu et al., 2015a); and evaluations of robustness (Peng et al., 2017). |
Maritime transport and efficiency | Direct port-to-port service, hub, and spoke networks (Fremont, 2007; Wang and Wang, 2011); maritime economics (Stopford, 2009); logistics (Rodrigue and Browne, 2002; Song and Lee, 2009; Davarzani et al., 2016); transportation (Guerrero and Rodrigue, 2014; Gagatsi et al., 2017); transport network design (Angeloudis et al., 2015; Karsten et al., 2017) and their network efficiency (Song et al., 2005; Tai and Hwang, 2005; Zeng and Yang, 2002; Fahmiasari and Parikesit, 2017); intermediacy (Rodrigue, 2017); maritime transport chain choice (Talley and Ng, 2013; Lam and Yam, 2011) and interactions (Knappett et al., 2008); and oligopolistic and competitive carrier behavior (Lee et al., 2012). |
Maritime safety | Risk (Akhtar and Utne, 2014; Lam et al., 2014a); safety (H?nninen et al., 2014); and maritime search and rescue operations (Bezgodov and Esin, 2014a) |
Table 1
Data categories in the vessel OD dataset"
Item | Meaning |
---|---|
MMSI | Unique ID for the vessel |
Start time (Ship entering the port)/End time (Ship leaving the port) | Second-level timestamp (e.g., 2015-06-10 01:16:58) |
Port’s location | Longitude and latitude of the port location |
World_port_index_number | Index number for a port |
Region_index | Index number for a region |
Port_name | Name of the port |
Wpi_country_code | Code for the port country |
Vessel_type | Type of vessel (bulk / container / tanker) |
Vessel_name | Name of the vessel |
Figure 9
Variations in the number of bulk, container, and tanker shipping voyages before and after Event C between Sri Lanka and countries linked by shipping, (a) bulk shipping linked with major countries and regions, (b) tanker shipping linked with major countries and regions, (c)-1 container shipping linked with India, and (c)-2 container shipping linked with Malaysia and Singapore"
Table 2
Countries potentially affected by Event B"
Link | Highest number of voyages and time period | Lowest number of voyages and time period | Average voyages before Event B | Average voyages after Event B | Minimum crossing area after standardi- zation | Time period for the same trend after standardi- zation | Similarity of time-varying changes (1/journeys) |
---|---|---|---|---|---|---|---|
Iran-United Arab Emirates | 143 (2015-10) | 64 (2015-01) | 59.806 | 121.176 | 0.353 | 0.167 | 0.473 |
United Arab Emirates- Indonesia | 17 (2015-10) | 3 (2015-02) | 5.871 | 12.294 |
Table 3
Countries potentially affected by Event C"
Link | Highest number of voyages and time period | Lowest number of voyages and time period | Average voyages before Event C | Average voyages after Event C | Minimum crossing area after standardi- zation | Time period of the same trend after standardi- zation | Similarity of time- varying changes (1/journeys) |
---|---|---|---|---|---|---|---|
Sri Lanka-India | 412 (2015-03) | 0 (2014-07) | 34.286 | 241.286 | |||
India-United Arab Emirates | 136 (2015-06) | 0 (2014-07) | 15.571 | 85.857 | 0.444 | 0.361 | 0.811 |
India-Saudi Arabia | 39 (2015-03) | 0 (2014-06) | 4.429 | 23.857 | 0.530 | 0.259 | 0.489 |
India-Pakistan | 91 (2015-03) | 3 (2014-06) | 10.286 | 59.571 | 0.250 | 0.185 | 0.741 |
Sri Lanka-Singapore | 114 (2015-06) | 1 (2014-07) | 18.571 | 70.429 | 0.413 | 0.315 | 0.762 |
Singapore-Bangladesh | 50 (2015-03) | 1 (2014-07) | 8.833 | 23.714 | |||
Sri Lanka-Malaysia | 148 (2015-06) | 0 (2014-07) | 17.571 | 83.143 |
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