Journal of Geo-information Science >
Multi-scale Spatio-temporal Changes and Influencing Factors of the Shipping Network in the Great Lakes of North America during the COVID-19 Pandemic Period
Received date: 2022-11-13
Revised date: 2023-02-17
Online published: 2023-06-30
Supported by
National Natural Science Foundation of China(42101452)
Shandong Provincial Natural Science Foundation, China(ZR2021QD027)
The COVID-19 pandemic has had a serious impact on the global maritime transportation industry, and there are new challenges and opportunities for the recovery of the shipping industry in the post-pandemic era. However, the limited time span of existing studies is insufficient to fully recognize the change in shipping network. Additionally, analysis of only macro-scale changes in spatial pattern ignores the intrinsic drivers of network changes. Therefore, based on the complex network theory, community detection algorithm, and TOPSIS analysis method, this study proposes a multi-scale change analysis framework for shipping network. The change characteristics of the shipping network, port community, and ports of three scales are analyzed using the North American Great Lakes ship trajectory data from 2019 to 2021. In addition, the change mechanism of each type of shipping is tracked. The results show that: (1) In terms of network traffic, freighters and tugboats accounted for 80% of the total traffic volume before the pandemic outbreak. After the pandemic, the total volume of ship traffic decreased by 22.4%. The change period and rate of the traffic volume of various types of ships are different. Cruise and cargo ships have strong recovery capability, followed by oil tankers, while passenger ships have the highest decrease in traffic volume with a decrease of more than 50% and have the weakest recovery capability. During the post-pandemic period, the total traffic volume increased by 4.4% compared to that before the epidemic, indicating that the overall network traffic recovery ability is strong; (2) In terms of network structure, before the pandemic, the shipping network showed an expansion trend with warmer temperatures, and the number of ports and routes increased incrementally. After the pandemic, the network structure was damaged, leading to a decreased connectivity. The route density increased, and the network "skeleton" was not destroyed during the period. Overall, the Great Lakes shipping network demonstrated strong resilience; (3) Large port groups in the Great Lakes region are located inside the major lakes with a stable spatial structure, and the key ports are located at the junctions of major lakes. The change of port evaluation values before and after the pandemic is complex and asymmetric. This study analyzes network changes from a multi-scale perspective, providing reference for practitioners to understand the impact of the pandemic on the shipping industry, and the method can be applied to other transportation network analyses.
PAN Jiale , XIN Rui . Multi-scale Spatio-temporal Changes and Influencing Factors of the Shipping Network in the Great Lakes of North America during the COVID-19 Pandemic Period[J]. Journal of Geo-information Science, 2023 , 25(7) : 1481 -1499 . DOI: 10.12082/dqxxkx.2023.220884
表1 AIS数据属性和示例值Tab. 1 AIS data attributes and example values |
属性 | 类型 | 属性含义 | 示例值 |
---|---|---|---|
MMSI | 静态 | 船舶ID | 369***030 |
IMO | 静态 | 海事编号 | IMO92***12 |
VesselName | 静态 | 船名 | KI** |
CallSign | 静态 | 呼号 | KA**07 |
VesselType | 静态 | 船舶类型 | 90 |
LAT | 动态 | 船舶纬度 | 46.59858 |
LON | 动态 | 船舶经度 | -90.8791 |
BaseDateTime | 动态 | UTF时间 | 2019/1/1T00:09:12 |
Status | 航行 | 航行状态 | 5 |
Draft | 航行 | 吃水 | 2.4 |
表2 五大湖航运OD数据属性及示例值Tab. 2 Great Lakes maritime OD data attributes and example values |
序号 | 属性 | 示例值 | 序号 | 属性 | 示例值 |
---|---|---|---|---|---|
1 | MMSI | 244***000 | 7 | VesselType | 80 |
2 | VesselName | IV** ***GHT | 8 | IMO | IMO96***59 |
3 | start_time | 2020/1/5 20:46 | 9 | end_time | 2020/1/8 6:20 |
4 | start_port_name | DETROIT | 10 | end_port_name | LEXINGTON |
5 | start_port_lat | 42.258 | 11 | end_port_lat | 43.268 |
6 | start_port_lon | -83.123 | 12 | end_port_lon | -82.524 |
表3 各类型船舶交通量统计Tab. 3 Statistical table of vessel traffic by type (次) |
时间 | 游船 | 客船 | 货轮 | 油轮 | 牵引船 | 全部 |
---|---|---|---|---|---|---|
2019-01 | 0 | 32 | 805 | 165 | 583 | 1 585 |
2019-04 | 6 | 244 | 2 611 | 357 | 949 | 4 167 |
2019-07 | 847 | 613 | 3 082 | 415 | 1 319 | 6 276 |
2019-11 | 3 | 167 | 2 739 | 397 | 1 255 | 4 561 |
2020-01 | 0 | 56 | 599 | 230 | 497 | 1 382 |
2020-04 | 2 | 95 | 2 482 | 316 | 986 | 3 881 |
2020-07 | 705 | 301 | 2 287 | 307 | 1 268 | 4 868 |
2020-11 | 6 | 90 | 2 592 | 198 | 946 | 3 832 |
2021-01 | 0 | 43 | 801 | 121 | 461 | 1 426 |
2021-04 | 11 | 198 | 2 941 | 331 | 1 173 | 4 654 |
2021-07 | 1 068 | 418 | 3 194 | 384 | 1 396 | 6 460 |
2021-11 | 3 | 163 | 2 910 | 369 | 1 331 | 4 776 |
表4 五大湖船舶航行网络指标Tab. 4 Great Lakes vessel navigation network indicators |
指标 | 指标描述 | 年份 | 1月 | 4月 | 7月 | 11月 | |
---|---|---|---|---|---|---|---|
拓扑指标 | N | 节点数 | 2019 | 53 | 80 | 180 | 80 |
2020 | 59 | 75 | 179 | 81 | |||
2021 | 55 | 85 | 200 | 81 | |||
L | 边数 | 2019 | 186 | 357 | 718 | 389 | |
2020 | 216 | 335 | 635 | 388 | |||
2021 | 185 | 387 | 844 | 395 | |||
D | 网络密度 | 2019 | 0.067 | 0.056 | 0.022 | 0.062 | |
2020 | 0.063 | 0.060 | 0.020 | 0.060 | |||
2021 | 0.062 | 0.054 | 0.021 | 0.061 | |||
C | 全局聚集系数 | 2019 | 0.292 | 0.326 | 0.333 | 0.332 | |
2020 | 0.226 | 0.327 | 0.292 | 0.332 | |||
2021 | 0.223 | 0.359 | 0.339 | 0.346 | |||
<K> | 节点平均度值 | 2019 | 7.019 | 8.925 | 7.978 | 9.725 | |
2020 | 7.322 | 8.933 | 7.095 | 9.580 | |||
2021 | 6.727 | 9.106 | 8.440 | 9.753 | |||
流量指标 | <F> | 节点平均流量 | 2019 | 59.811 | 104.175 | 69.733 | 114.025 |
2020 | 46.847 | 103.493 | 54.391 | 94.617 | |||
2021 | 51.855 | 109.506 | 64.600 | 117.926 | |||
<W> | 边平均流量 | 2019 | 8.522 | 11.672 | 8.741 | 11.725 | |
2020 | 6.398 | 11.585 | 7.666 | 9.876 | |||
2021 | 7.708 | 12.026 | 7.654 | 12.091 | |||
指标分布 | CV(F) | 节点流量变异系数 | 2019 | 1.626 | 1.971 | 2.685 | 1.991 |
2020 | 1.656 | 1.974 | 2.555 | 2.020 | |||
2021 | 1.611 | 2.069 | 2.650 | 2.001 | |||
CV(W) | 边流量变异系数 | 2019 | 2.061 | 2.755 | 3.409 | 2.923 | |
2020 | 2.176 | 2.797 | 3.150 | 2.921 | |||
2021 | 1.919 | 2.899 | 3.496 | 2.929 |
表5 游船网络指标Tab. 5 Cruise network indicators |
时间 | N | L | L/N | D | C |
---|---|---|---|---|---|
2019-07 | 100 | 277 | 2.77 | 0.028 | 0.174 |
2020-07 | 100 | 238 | 2.38 | 0.024 | 0.155 |
2021-07 | 109 | 353 | 3.24 | 0.030 | 0.224 |
<K> | <F> | <W> | CV(F) | CV(W) | |
2019-07 | 5.540 | 16.940 | 3.058 | 1.583 | 2.324 |
2020-07 | 4.760 | 14.100 | 2.962 | 1.500 | 2.081 |
2021-07 | 6.477 | 19.596 | 3.025 | 1.415 | 2.009 |
表6 客船网络指标Tab. 6 Passenger network indicators |
年份 | 拓扑指标 | 1月 | 4月 | 7月 | 11月 | 流量指标及分布 | 1月 | 4月 | 7月 | 11月 |
---|---|---|---|---|---|---|---|---|---|---|
2019 | N | 9 | 30 | 49 | 23 | <F> | 7.111 | 16.267 | 25.020 | 14.522 |
2020 | 12 | 16 | 37 | 19 | 9.333 | 11.875 | 16.270 | 9.474 | ||
2021 | 11 | 25 | 51 | 28 | 7.818 | 15.840 | 16.392 | 11.643 | ||
2019 | L | 11 | 41 | 140 | 38 | <W> | 2.909 | 5.951 | 4.379 | 4.395 |
2020 | 14 | 20 | 62 | 25 | 4.000 | 4.750 | 4.855 | 3.600 | ||
2021 | 13 | 36 | 91 | 36 | 3.308 | 5.500 | 4.593 | 4.528 | ||
2019 | D | 0.153 | 0.047 | 0.060 | 0.075 | CV(F) | 0.754 | 2.218 | 1.205 | 1.749 |
2020 | 0.106 | 0.083 | 0.047 | 0.073 | 1.121 | 1.003 | 1.981 | 1.095 | ||
2021 | 0.118 | 0.060 | 0.036 | 0.048 | 0.907 | 1.676 | 2.158 | 1.614 | ||
2019 | <K> | 2.444 | 2.733 | 5.714 | 3.304 | CV(W) | 0.873 | 2.464 | 1.766 | 2.109 |
2020 | 2.333 | 2.500 | 3.351 | 2.632 | 1.073 | 1.120 | 2.342 | 1.267 | ||
2021 | 2.364 | 2.880 | 3.569 | 2.571 | 1.030 | 2.034 | 2.781 | 1.765 |
表7 货轮与油轮网络指标Tab. 7 Cargo and tanker network indicators |
指标 | 年份 | 货船 | 油轮 | |||||||
---|---|---|---|---|---|---|---|---|---|---|
1月 | 4月 | 7月 | 11月 | 1月 | 4月 | 7月 | 11月 | |||
拓扑指标 | N | 2019 | 32 | 49 | 53 | 51 | 12 | 23 | 24 | 22 |
2020 | 36 | 46 | 47 | 48 | 14 | 19 | 18 | 18 | ||
2021 | 37 | 46 | 50 | 48 | 10 | 22 | 22 | 23 | ||
L | 2019 | 100 | 194 | 245 | 218 | 31 | 57 | 61 | 53 | |
2020 | 102 | 188 | 204 | 221 | 34 | 44 | 48 | 48 | ||
2021 | 107 | 201 | 250 | 222 | 24 | 57 | 65 | 63 | ||
D | 2019 | 0.101 | 0.082 | 0.089 | 0.085 | 0.235 | 0.113 | 0.111 | 0.115 | |
2020 | 0.081 | 0.091 | 0.094 | 0.098 | 0.187 | 0.129 | 0.157 | 0.157 | ||
2021 | 0.080 | 0.097 | 0.102 | 0.098 | 0.267 | 0.123 | 0.141 | 0.125 | ||
C | 2019 | 0.279 | 0.302 | 0.351 | 0.294 | 0.214 | 0.244 | 0.277 | 0.340 | |
2020 | 0.175 | 0.327 | 0.321 | 0.345 | 0.217 | 0.179 | 0.263 | 0.371 | ||
2021 | 0.153 | 0.351 | 0.356 | 0.355 | 0.231 | 0.329 | 0.377 | 0.254 | ||
<K> | 2019 | 6.250 | 7.918 | 9.245 | 8.549 | 5.167 | 4.957 | 5.083 | 4.818 | |
2020 | 5.667 | 8.174 | 8.681 | 9.208 | 4.857 | 4.632 | 5.333 | 5.333 | ||
2021 | 5.784 | 8.739 | 10.000 | 9.250 | 4.800 | 5.182 | 5.909 | 5.478 | ||
流量指标 | <F> | 2019 | 50.31 | 106.57 | 116.30 | 107.41 | 27.50 | 31.04 | 34.58 | 36.09 |
2020 | 33.28 | 107.91 | 97.32 | 108.00 | 32.86 | 33.26 | 34.11 | 22.00 | ||
2021 | 43.30 | 127.87 | 127.76 | 121.25 | 24.20 | 30.09 | 34.91 | 32.09 | ||
<W> | 2019 | 8.050 | 13.459 | 12.580 | 12.564 | 5.323 | 6.263 | 6.803 | 7.491 | |
2020 | 5.873 | 13.202 | 11.211 | 11.729 | 6.765 | 7.182 | 6.396 | 4.125 | ||
2021 | 7.486 | 14.632 | 12.776 | 13.108 | 5.042 | 5.807 | 5.908 | 5.857 | ||
指标分布 | CV(F) | 2019 | 1.316 | 1.756 | 1.760 | 1.753 | 0.647 | 1.123 | 1.131 | 1.060 |
2020 | 1.450 | 1.671 | 1.642 | 1.694 | 0.859 | 0.973 | 0.906 | 0.841 | ||
2021 | 1.451 | 1.658 | 1.713 | 1.648 | 0.557 | 1.026 | 0.993 | 1.046 | ||
CV(W) | 2019 | 1.617 | 2.331 | 2.526 | 2.425 | 0.799 | 1.199 | 1.202 | 1.097 | |
2020 | 1.702 | 2.306 | 2.369 | 2.475 | 0.977 | 0.974 | 1.078 | 0.973 | ||
2021 | 1.560 | 2.362 | 2.610 | 2.440 | 0.649 | 1.108 | 1.198 | 1.150 |
表8 船舶航行网络港口中心性指标全局权重Tab. 8 Global weighting of port centrality indicators for ship navigation networks |
时间 | 中介中心性 | 度中心性 | 接近中心性 |
---|---|---|---|
2019-01 | 0.679 4 | 0.233 9 | 0.086 6 |
2019-04 | 0.687 8 | 0.204 2 | 0.108 0 |
2019-07 | 0.616 6 | 0.255 2 | 0.128 2 |
2019-11 | 0.682 1 | 0.244 8 | 0.073 1 |
2020-01 | 0.731 5 | 0.216 5 | 0.051 9 |
2020-04 | 0.686 6 | 0.211 3 | 0.102 1 |
2020-07 | 0.622 1 | 0.219 4 | 0.158 5 |
2020-11 | 0.712 8 | 0.233 6 | 0.053 6 |
2021-01 | 0.689 4 | 0.232 2 | 0.078 4 |
2021-04 | 0.653 9 | 0.208 3 | 0.137 8 |
2021-07 | 0.603 5 | 0.263 7 | 0.132 8 |
2021-11 | 0.693 8 | 0.223 9 | 0.082 3 |
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