全球LNG海上运输网络演化及中国贸易现状分析

doi:10.12082/dqxxkx.2022.220021

Abstract

Abstract:

With the proposal of "carbon peak" and "carbon neutralization", Liquefied Natural Gas (LNG) has gradually garnered the attention of energy market as a clean and low-carbon energy. In this context, it is of great significance to analyze the evolution mode of the LNG maritime transport network, so as to master the dynamic of global energy pattern and the status of China's import trade. In this paper, the evolution trend of the global LNG maritime transport network from 2018 to 2020 is explored based on the ship trajectory data and complex network theory. Meanwhile, according to China's trade status, LNG import sources, distribution of main import ports, and the inflow status of the top three import ports in China are analyzed. The results show that: (1) From 2018 to 2020, the global LNG maritime transport network expanded with a “scale-free” characteristic. The "breadth" and "depth" of node connections in the backbone network are increasing, and there is a risk that global LNG trade will become monopolistic; (2) The countries along the "Belt and Road Initiative" actively participated in trade. The numbers of import ports and import voyages in Central and North America, South and Southeast Asia have significantly increased, and in particular, Sabetta and Bonny ranked the top eight globally according to their export volume; (3) The average shortest path length of the network is increasing year by year from 2018 to 2020, and the new mode of "transshipment port" business is gradually emerging. By 2020, 21 transshipment ports have participated in LNG trade, and the United States occupies the dominant position in global transshipment; (4) In recent three years, China's LNG import scale has developed rapidly, and the flow direction of the maritime transport network tends to be diversified. However, Australia is still the main LNG source for China. In terms of import volume, the ports of Tianjin, Shenzhen, and Yung'an rank the top three in China, and the pressure to reduce carbon emissions has prompted the economically developed regions to build terminals and increase imports.

Key words: carbon peak, COVID-19, complex network Analysis, LNG, the Belt and Road, clean energy, global, China

MEI Qiang, HU Qinyou, LIU Xiliang, ZHAO Ruina, YANG Chun, WANG Peng, QI Yuling, YANG Yang, YUAN Qirui. Research on the Evolution of Global LNG Maritime Transportation Network and Trade Condition of China[J].Journal of Geo-information Science, 2022, 24(9): 1701-1716.DOI:10.12082/dqxxkx.2022.220021

Figures/Tables 15

Fig. 1

Fig. 2

Tab. 1

Fig. 3

Tab. 2

Tab. 3

Tab. 4

Fig. 4

Tab. 5

Fig. 5

Tab. 6

Fig. 6

Fig. 7

Tab. 7

Fig. 8

References 53

[1]	韩梦瑶, 熊焦, 刘卫东. 中国跨境能源贸易及隐含能源流动对比——以"一带一路"能源合作为例[J]. 自然资源学报, 2020, 35(11):108-120.
	[ Han M Y, Xiong J, Liu W D. China's cross-border energy relations between direct trade and embodied transfers: based on "the Belt and Road" energy cooperation[J]. Journal of Natural Resources, 2020, 35(11):108-120. ] DOI: 10.31497/zrzyxb.20201109 doi: 10.31497/zrzyxb.20201109
[2]	杨宇, 于宏源, 鲁刚, 等. 世界能源百年变局与国家能源安全[J]. 自然资源学报, 2020, 35(11):2803-2820.
	[ Yang Y, Yu H Y, Lu G. Interview on the unprecedented changes of energy geopolitics and national energy security[J]. Journal of Natural Resources, 2020, 35(11):2803-2820. ] DOI: 10.31497/zrzyxb.20201119 doi: 10.31497/zrzyxb.20201119
[3]	Steinberger J K, Roberts J T. Pathways of human development and carbon emissions embodied in trade[J]. Nature Climate Change, 2012, 2:81-85. DOI: 10.1038/nclimate1371 doi: 10.1038/nclimate1371
[4]	邓祥征, 丹利, 叶谦, 等. 碳排放和减碳的社会经济代价研究进展与方法探究[J]. 地球信息科学学报, 2018, 20(4):405-413. doi: 10.12082/dqxxkx.2018.170590
	[ Deng X Z, DAN L, Ye Q, et al. Methodological framework and research progress on the social and economic costs of carbon emission and reduction[J]. Journal of Geo-information Science, 2018, 20(4):405-413. ] DOI: 10.12082/dqxxkx.2018.170590 doi: 10.12082/dqxxkx.2018.170590
[5]	徐冠华, 葛全胜, 宫鹏, 等. 全球变化和人类可持续发展:挑战与对策[J]. 科学通报, 2013, 58(21):2100-2106.
	[ Xu G H, Ge Q S, Gong P, et al. Societal response to challenges of global change and human sustainable development[J]. Chinese Science Bulletin, 2013, 58(21):2100-2106. ] DOI: 10.1007/s11434-013-5947-3 doi: 10.1007/s11434-013-5947-3
[6]	武凤阳, 邹戈阳, 张沥月, 等. 2020年中国天然气产业特点分析[J]. 油气与新能源, 2021, 33(2):59-66.
	[ Wu F Y, Zou G Y, Zhang L Y, et al. Features of 2020 natural gas industry in China[J]. Petroleum and New Energy, 2021, 33(2):56-66. ] DOI: 10.3969/j.issn.2097-0021.2021.02.011 doi: 10.3969/j.issn.2097-0021.2021.02.011
[7]	Arora V, Cai Y Y. U.S.natural gas exports and their global impacts[J]. Applied Energy, 2014, 120:95-103. DOI: 10.1016/j.apenergy.2014.01.054 doi: 10.1016/j.apenergy.2014.01.054
[8]	Bittante A, Pettersson F, Saxen H. Optimization of a small-scale LNG supply chain[J]. Energy, 2018, 148:79-89. DOI: 10.1016/j.energy.2018.01.120 doi: 10.1016/j.energy.2018.01.120
[9]	房卓, 沈忱, 张民辉, 等. 环渤海地区港口LNG运输特点及泊位合理通过能力研究[J]. 水运工程, 2019, 11:36-39.
	[ Fang Z, Shen C, Zhang M H, et al. Investigation on characteristics of LNG transpotation and reasonable throughput capacity of LNG berth around Bohai region[J]. Port &Waterway Engineering, 2019, 11:36-39. ] DOI: 10.16233/j.cnki.issn1002-4972.20191104.020 doi: 10.16233/j.cnki.issn1002-4972.20191104.020
[10]	Koromila I, Aneziris O, Nivolianitou Z, et al. Stakeholder analysis for safe LNG handling at ports[J]. Safety Science, 2022, 146:105565. DOI: 10.1016/J.SSCI.2021.105565 doi: 10.1016/J.SSCI.2021.105565
[11]	Miętkiewicz R. LNG supplies' security with autonomous maritime systems at terminals' areas. Safety Science, 2021, 142:105397. DOI: 10.1016/J.SSCI.2021.105397 doi: 10.1016/J.SSCI.2021.105397
[12]	母宝颍, 方卓, 王问渊, 等. 日本LNG码头与接收站建设特征研究[J]. 水运工程, 2019, 5:67-72.
	[ Mu B Y, Fang Z, Wang W Y, et al. Construction characteristics of Japanese LNG wharf and receiving terminal[J]. Port &Waterway Engineering, 2019, 5:67-72. ] DOI: 10.16233/j.cnki.issn1002-4972.20190505.022 doi: 10.16233/j.cnki.issn1002-4972.20190505.022
[13]	沈忱, 张民辉, 苏孟超, 等. 不同通航模式下LNG泊位组船舶通航效率研究[J]. 港工技术, 2021, 58(5):94-98.
	[ Shen C, Zhang M H, Su M C, et al. Assessment on the navigability efficiency of liquefied natural gas ship multi-berths under different navigable organization modes[J]. Port Engineering Technology, 2021, 58(5):94-98. ] DOI: 10.16403/j.cnki.ggjs20210522 doi: 10.16403/j.cnki.ggjs20210522
[14]	Li T T, He X, Gao P. Analysis of offshore LNG storage and transportation technologies based on patent informatics[J]. Cleaner Engineering and Technology, 2021, 5:100317. DOI: 10.1016/j.clet.2021.100317 doi: 10.1016/j.clet.2021.100317
[15]	Wood D A. A review and outlook for the global LNG trade[J]. Journal of Natural Gas Science and Engineering, 2012, 9:16-27. DOI: 10.1016/j.jngse.2012.05.002 doi: 10.1016/j.jngse.2012.05.002
[16]	Shi Y P, Shen Y F. Macroeconomic uncertainty and natural gas prices: Revisiting the Asian Premium[J]. Energy Economics, 2021, 94:105081. DOI: 10.1016/J.ENECO.2020.105081 doi: 10.1016/J.ENECO.2020.105081
[17]	Jiang H, Xue M M, Dong K, et al. How will natural gas market reforms affect carbon marginal abatement costs? Evidence from China[J]. Economic Systems Research, 2021. DOI: 10.1080/09535314.2020.1868410 doi: 10.1080/09535314.2020.1868410
[18]	曾兴球. 中美贸易摩擦油气市场深受影响[J]. 国际石油经济, 2019, 27(1):4-6.
	[ Zeng X Q. Deep influence on oil and gas market due to trade frictions between China and the United States[J]. International Petroleum Economics, 2019, 27(1):4-6. ]
[19]	高振宇, 高鹏, 刘倩, 等. 中国LNG产业现状分析及发展建议[J]. 天然气技术与经济, 2019, 13(6):14-19.
	[ Gao Z Y, Gao P, Liu Q, et al. LNG industry in China and some suggestions on its development[J]. Natural Gas Technology and Economy, 2019, 13(6):14-19. ] DOI: 10.3969/j.issn.2095-1132.2019.06.003 doi: 10.3969/j.issn.2095-1132.2019.06.003
[20]	张耀光, 刘桂春, 刘锴, 等. 中国沿海液化天然气 (LNG) 产业布局与发展前景[J]. 经济地理, 2010, 30(6):881-885.
	[ Zhang Y G, Liu G C, Liu K, et al. Study on development and distribution of lng industry of coastal in china[J]. Economic Geography, 2010, 30(6):881-885. ] DOI: 10.15957/j.cnki.jjdl.2010.06.020 doi: 10.15957/j.cnki.jjdl.2010.06.020
[21]	Biresselioglu M E, Yelkenci T, OZ I O. Investigating the natural gas supply security: A new perspective[J]. Energy, 2015, 80(11):168-176. DOI: 10.1016/j.energy.2014.11.060 doi: 10.1016/j.energy.2014.11.060
[22]	张珺, 黄艳. 中国天然气供应安全指数构建与建议[J]. 天然气工业, 2015, 35(3):125-128.
	[ Zhang J, Huang Y. Some suggestions on the construction of an integrated gas supply security index in China[J]. Natural Gas Industry, 2015, 35(3):125-128. ] DOI: 10.3787/j.issn.10000976.2015.03.020 doi: 10.3787/j.issn.10000976.2015.03.020
[23]	周云亨, 陈佳巍, 叶瑞克, 等. 国家天然气安全评价指标体系的构建与应用[J]. 自然资源学报, 2020, 35(11):2645-2654.
	[ Zhou Y H, Chen J W, Ye R K, et al. Construction and application of national natural gassecurity indicator system[J]. Journal of Natural Resources, 2020, 35(11):2645-2654. ] DOI: 10.31497/zrzyxb.20201107 doi: 10.31497/zrzyxb.20201107
[24]	胡昊宇, 黄莘绒, 李沛霖, 等. 流空间视角下中国城市群网络结构特征比较—基于铁路客运班次的分析[J/OL]. 地球信息科学学报, 2022,1-16[2022-06-04].
	[ Hu H Y, Huang X R, Li P L, et al. Comparison of network structure patterns of urban agglomerations in China from the perspective of space of flows: analysis based on railway schedule[J/OL]. Journal of Geo-information Science, 2022,1-16[2022-06-04].] DOI: https://kns.cnki.net/kcms/detail/11.5809.P.20211008.1433.002.html doi: https://kns.cnki.net/kcms/detail/11.5809.P.20211008.1433.002.html
[25]	Fang Z X, Yu, H C, Lu, F, et al. Maritime network dynamics before and after international events[J]. Journal of Geographical Sciences, 2018, 28(7):937-956. DOI: 10.1007/s11442-018-1514-9 doi: 10.1007/s11442-018-1514-9
[26]	余红楚, 方志祥, 陆锋, 等. 重要经济发展区域间海运网络时空演变特性分析[J]. 地球信息科学学报, 2018, 20(5):582-592. doi: 10.12082/dqxxkx.2018.180085
	[ Yu H C, Fang Z X, Lu F, et al. Spatial-temporal evolution patterns of maritime networks between important economic developing zones revealed[J]. Journal of Geographical Sciences, 2018, 20(5):582-592.] DOI: 10.12082/dqxxkx.2018.180085 doi: 10.12082/dqxxkx.2018.180085
[27]	Mou N X, Sun S Y, Yang T F, et al. Assessment of the resilience of a complex network for crude oil transportation on the maritime silk road[J]. IEEE ACCESS, 2020, 8:181311-181325. DOI: 10.1109/ACCESS.2020.3028214 doi: 10.1109/ACCESS.2020.3028214
[28]	王介勇, 戴纯, 周墨竹, 等. 全球粮食贸易网络格局及其影响因素[J]. 自然资源学报, 2021, 36(6):1545-1556.
	[ Wang J Y, Dai C, Zhou M Z, et al. Research on global grain trade network pattern its influencing factors[J]. Journal of Natural Resources, 2021, 36(6):1545-1556.] DOI: 10.31497/zrzyxb.20210615 doi: 10.31497/zrzyxb.20210615
[29]	李天祥, 刘星宇, 王容博, 等. 2000—2019年全球猪肉贸易格局演变及其对中国的启示—基于复杂贸易网络分析视角[J]. 自然资源学报, 2021, 36(6):1557-1572.
	[ Li T X, Liu X Y, Wang R B, et al. Dynamics of global pork trade networks during 2000-2019 and its implications for China: A complex network analysis[J]. Journal of Natural Resources, 2021, 36(6):1557-1572. ] DOI: 10.31497/zrzyxb.20210616 doi: 10.31497/zrzyxb.20210616
[30]	魏景斌, 李雅婷. 全球LNG贸易网络特征及其团块分布研究[J]. 中外能源, 2021, 9:1-11.
	[ Wei J B, Li Y T. Characteristics of global LNG trade network and its block distribution[J]. Sino-Global Energy, 2021, 9:1-11. ]
[31]	Geng J B, Ji Q, Fan Y. A Dynamic Analysis on Global Natural Gas Trade Network[J]. Applied Energy, 2014, 132:23-33. DOI: 10.1016/j.apenergy.2014.06.064 doi: 10.1016/j.apenergy.2014.06.064
[32]	郑玉华, 李静云, 汪楝钦. 基于复杂网络的全球LNG市场分析[J]. 天然气与石油, 2016, 34(3):106-111.
	[ Zheng Y H, Li J Y, Wang L Q. Analysis on global LNG market based on complex network[J]. Natural Gas and Oil, 34(3):106-111. ] DOI: 10.3969/j.issn.1006-5539.2016.03.022 doi: 10.3969/j.issn.1006-5539.2016.03.022
[33]	Peng P, Cheng S, Chen J, et al. A fine-grained perspective on the robustness of global cargo ship transportation networks[J]. Journal of Geographical Sciences, 2018, 28(7):881-889. DOI: 10.1007/s11442-018-1511-z doi: 10.1007/s11442-018-1511-z
[34]	Peng P, Yang Y, Cheng S, et al. Hub-and-spoke structure: Characterizing the global crude oil transport network with mass vessel trajectories[J]. Energy, 2019, 168:966-974. DOI: 10.1016/j.energy.2018.11.049 doi: 10.1016/j.energy.2018.11.049
[35]	Mou N, Ren H N, Zheng Y H, et al. Traffic inequality and relations in maritime silk road: A network flow analysis[J]. ISPRS Int.J.Geo-Inf, 2021, 10:40. DOI: 10.3390/ijgi10010040 doi: 10.3390/ijgi10010040
[36]	Yu H, Fang Z, Lu F, et al. Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes[J]. Applied Energy, 2019, 237:390-403. DOI: 10.1016/j.apenergy.2019.01.011 doi: 10.1016/j.apenergy.2019.01.011
[37]	彭澎, 程诗奋, 陈闪闪, 等. 全球液化石油气运输网络贸易社区特征及其演化分析[J]. 自然资源学报, 2020, 35(11):2687-2695.
	[ Peng P, Cheng S F, Chen S S, et al. Global liquefied petroleum gas trading communities:Ananalysis from the perspective of maritime transportation network[J]. Journal of Natural Resources, 2020, 35(11):2687-2695. ] DOI: 10.31497/zrzyxb.20201110 doi: 10.31497/zrzyxb.20201110
[38]	Mou N X, Wang C Y, Yang T F, et al. Evaluation of Development Potential of Ports in the Yangtze River Delta Using FAHP-Entropy Model[J]. Sustainability, 2020,12,493. DOI: 10.3390/su12020493 doi: 10.3390/su12020493
[39]	Peng P, Yang Y, Lu F, et al. Modelling the competitiveness of the ports along the Maritime Silk Road with big data[J]. Transportation Research Part A: Policy and Practice, 2018, 118: 852-867. DOI: 10.1016/j.tra.2018.10.041 doi: 10.1016/j.tra.2018.10.041
[40]	Peng P, Lu F, Cheng S F, et al. Mapping the global liquefied natural gas trade network: A perspective of maritime transportation[J]. Journal of Cleaner Production, 2021, 283:124640. DOI: 10.1016/j.jclepro.2020.124640 doi: 10.1016/j.jclepro.2020.124640
[41]	夏四友, 郝丽莎, 唐文敏, 等. 复杂网络视角下世界石油流动的竞合态势演变及对中国石油合作的启示[J]. 自然资源学报, 2020, 35(11):2655-2673.
	[ Xia S Y, Hao L S, Tang W M, et al. The evolution of competition and cooperation in world crude oil flows from the perspective of complex networks and its enlightenment to China's oil cooperation[J]. Journal of Natural Resources, 2020, 35(11):2655-2673. ] DOI: 10.31497/zrzyxb.20201108 doi: 10.31497/zrzyxb.20201108
[42]	Shibasaki R, Kanamoto K, Suzuki T. Estimating global pattern of LNG supply chain: a port-based approach by vessel movement database[J]. Maritime Policy & Management, 2019, 47:143-171. DOI: 10.1080/03088839.2019.1657974 doi: 10.1080/03088839.2019.1657974
[43]	Chen Z H, An H Z, Gao X Y, et al. Competition pattern of the global Liquefied Natural Gas(LNG) trade by network analysis[J]. Journal of Natural Gas Science & Engineering, 2016, 33:769-776. DOI: 10.1016/j.jngse.2016.06.022 doi: 10.1016/j.jngse.2016.06.022
[44]	Shan Y L, Liu J H, Liu Z L, et al. New provincial CO2 emission inventories in China based on apparent energy consumption data and updated emission factors[J]. Applied Energy, 2016, 184:742-750. DOI: 10.1016/j.apenergy.2016.03.073 doi: 10.1016/j.apenergy.2016.03.073
[45]	向哲, 胡勤友, 施朝健, 等. 基于AIS数据的受限水域船舶领域计算方法[J]. 交通运输工程学报, 2015, 15(5):110-117.
	[ Xiang Z, Hu Q Y, Shi C J, et al. Computation method of ship domains in restricted waters based on AIS data[J]. Journal of Traffic and Transportation Engineering, 2015, 15(5):110-117. ] DOI: 10.19818/j.cnki.1671-1637.2015.05.014 doi: 10.19818/j.cnki.1671-1637.2015.05.014
[46]	Wu L, Xu Y J, Wang F. Identifying Port Calls of Ships by Uncertain Reasoning with Trajectory Data[J]. International Journal of Geo-Information, 2020, 9:756. DOI: 10.3390/IJGI9120756 doi: 10.3390/IJGI9120756
[47]	陈闪闪, 彭澎, 陆锋, 等. 海洋主航道对全球集装箱运输网络的影响分析[J]. 地理研究, 2019, 38(9):2273-2287. doi: 10.11821/dlyj020181375
	[ Chen S S, Peng P, Lu F, et al. Influence of the main channels on global container ship network[J]. Geographical Research, 2019, 38(9):2273-2287. ] DOI: 10.11821/dlyj020181375 doi: 10.11821/dlyj020181375
[48]	王列辉, 林羽珊. 1895—2016年全球海运网络中的海峡两岸港口运输联系变化[J]. 地理学报, 2018, 73(12):2282-2296. doi: 10.11821/dlxb201812002
	[ Wang L H, Lin Y S. Changes of ports’ connection across the Taiwan Straits in the global maritime network(1895-2016)[J]. Acta Geographical Sinica, 2018, 73(12):2282-2296. ] DOI: 10.11821/dlxb201812002 doi: 10.11821/dlxb201812002
[49]	Kong Y X, Shi G Y, Wu R J, et al. k-core:Theories and applications[J]. Physics Reports, 2019, 832:1-32. DOI: 10.1016/j.physrep.2019.10.004 doi: 10.1016/j.physrep.2019.10.004
[50]	王宇坤. 非洲各国油气资源潜力及选区研究[J]. 国际石油经济, 2020, 28(7):70-79.
	[ Wang Y K. Study on oil and gas resource potential and blocks selection of African Countries[J]. International Petroleum Economics, 2020, 28(7):81-89. ]
[51]	赵越, 刘建民, 韩淑琴, 等. 冰上丝绸之路与北极油气资源[J]. 地质力学学报, 2021, 27(5):880-889.
	[ Zhao Y, Liu J M, Han S Q, et al. Polar Silk Road and Arctic petroleum and gas resources[J]. Journal of Geomechanics, 2021, 27(5):880-889. ] DOI: 10.12090/j.issn.1006-6616.2021.27.05.071 doi: 10.12090/j.issn.1006-6616.2021.27.05.071
[52]	沈珏新, 张洪林, 杜敏, 等. 中国主要石油公司LNG业务现状、挑战和应对策略[J]. 油气与新能源, 2021, 33(4):33-38.
	[ Shen J X, Zhang H L, Du M, et al. Development Status, Challenges and Countermeasures of LNG Business for Major Oil Companies in China[J]. Petroleum and New Energy, 2021, 33(4):33-38.] DOI: 10.3969/j.issn.2097-0021.2021.03.007 doi: 10.3969/j.issn.2097-0021.2021.03.007
[53]	李艳磊, 于海涛, 金博, 等. 澳大利亚油气投资环境与新项目开发的思考与建议[J]. 国际合作, 2019, 27(8):81-89.
	[ Li Y L, Yu H T, J B, et al. Australian oil and gas investment environment and suggestions on new project development[J]. Internation Cooperation, 2019, 27(8):81-89. ]

年份	航次数/次	发货量/万t	参与船舶总艘数/条	平均航次发货量/万t
2018	4668	29 748.82	481	6.37
2019	5440	35 434.99	557	6.51
2020	5854	38 353.05	559	6.55

年份	节点数/个	连边数/条	平均度	平均集聚系数
2018年	140	864	5.993	0.092
2019年	165	1095	6.636	0.113
2020年	167	1351	8.048	0.113

年份	低度值点 (1~10) 点占比/%	中度值 (11~25) 点占比/%	次高度值 (26~40) 点占比/%	高度值 (41~85) 点占比/%	R²	拟合方程
2018	60	28.5	7.9	3.6	0.704	y = 0.1669x^-0.795
2019	52.7	35.8	7.3	4.2	0.739	y = 0.1662x^-0.80
2020	43.7	38.3	9.6	8.4	0.643	y = 0.1186x^-0.702

年份	k值	港口数/个	航次数/次	港口数占比/%	航次数占比/%
2018	11	31	1698	22.1	36.4
2019	12	42	2031	25.5	37.3
2022	14	59	2965	35.3	50.7

排名	2018年		2019年		2020年
排名	出强度	入强度	出强度	入强度	出强度	入强度
1	拉斯拉凡	达荷	拉斯拉凡	达荷	拉斯拉凡	川崎
2	格拉德斯通	亚瑟	民都洛	仁川	格拉德斯通	达荷
3	丹皮尔	仁川	亚瑟	川崎	民都洛	天津
4	邦尼	平泽	格拉德斯通	平泽	丹皮尔	仁川
5	民都洛	川崎	邦尼	永安	邦尼	永安
6	亚瑟	永安	丹皮尔	天津	亚瑟	深圳
7	巴罗岛	木更津	福廷角	米尔福德	萨贝塔	泽布吕赫
8	福廷角	千叶	巴罗岛	木更津	巴罗岛	米尔福德

Research on the Evolution of Global LNG Maritime Transportation Network and Trade Condition of China

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 15

References 53

Related Articles 15

Metrics

Comments

Recommended 0

排名	2018年		2019年		2020年
排名	港口	中介中心度	港口	中介中心度	港口	中介中心度
1	亚瑟	0.071	亚瑟	0.049	亚瑟	0.040
2	鹿特丹	0.026	泽布吕赫	0.020	新加坡	0.030
3	泽布吕赫	0.014	蒙托伊尔	0.015	弗里波特	0.023
4	蒙托伊尔	0.009	鹿特丹	0.015	鹿特丹	0.019
5	湾点	0.006	湾点	0.014	泽布吕赫	0.010
6	福斯	0.005	阿尔赫西拉斯	0.009	敦刻尔克	0.010
7	杰拜勒·阿里	0.004	梅德韦	0.008	艾哈迈迪	0.010
8	洪宁斯沃格	0.004	敦刻尔克	0.007	蒙托伊尔	0.009

排名	2018年		2019年		2020年
排名	港口	进口货量/万t	港口	进口货量/万t	港口	进口货量/万t
1	永安	1038.77	永安	1017.65	天津	1227.52
2	天津	696.12	天津	1007.46	永安	1106.91
3	深圳	645.47	深圳	749.64	深圳	1047.81
4	洋口	645.19	董家口	614.16	台中	695.05
5	曹妃甸	526.43	台中	613.70	董家口	687.91
6	台中	525.25	洋口	532.34	洋口	608.74
7	宁波	524.1	宁波	506.17	宁波	538.60
8	董家口	490.54	上海	504.69	上海	501.01

[1]	QI Meng, CHEN Nan, LIN Siwei, ZHOU Qianqian. Geomorphic Recognition of China Considering Complex Network of Catchments [J]. Journal of Geo-information Science, 2023, 25(5): 909-923.
[2]	HOU Huitai, LAN Chaozhen, XU Qing. UAV Absolute Positioning Method based on Global and Local Deep Learning Feature Retrieval from Satellite Images [J]. Journal of Geo-information Science, 2023, 25(5): 1064-1074.
[3]	LIU Yaoming, LI Wanjing, ZHANG Xiuyuan, ZHANG Yuheng, LI Ran, ZHOU Qi. Evaluating Rural Access Index across China with Multi-source Open Data [J]. Journal of Geo-information Science, 2023, 25(4): 783-793.
[4]	ZHAO Long, LI Guoqing, YAO Xiaochuang, MA Yue. Code Operation Scheme for the Icosahedral Hexagonal Discrete Global Grid System [J]. Journal of Geo-information Science, 2023, 25(2): 239-251.
[5]	HUANG Xin, MAO Zhengyuan. Prediction of Passenger Demand for Online Car-hailing based on Spatio-temporal Multi-graph Convolution Network [J]. Journal of Geo-information Science, 2023, 25(2): 311-323.
[6]	MA Li, PAN Jinghu. Spatial Identification and Temporal-spatial Evolution of Wilderness Areas in China [J]. Journal of Geo-information Science, 2023, 25(2): 324-339.
[7]	LIN Qigen, WANG Leibin, ZHANG Jiahui. Assessment of the Rainfall-Induced Landslide Hazard and Population Exposure in China under 1.5 ℃ and 2.0 ℃ Global Warming Scenarios [J]. Journal of Geo-information Science, 2023, 25(1): 177-189.
[8]	SHI Changxing. A Method of Estimating Errors of DEM Constructed from Topographic Scanning Data by TIN Model [J]. Journal of Geo-information Science, 2023, 25(1): 40-48.
[9]	ZHANG Ying, WANG Xia, YAN Yihan, SHI Shuyue, HAI Shaoqi. The Spatio-temporal Changes of Tourism Multidimensional Poverty Alleviation Effect at County in Southwest China based on Night Light Data [J]. Journal of Geo-information Science, 2022, 24(8): 1541-1557.
[10]	GUO Chunhua, ZHU Xiufang, ZHANG Shizhe, TANG Mingxiu, XU Kun. Hazard Changes Assessment of Future High Temperature in China based on CMIP6 [J]. Journal of Geo-information Science, 2022, 24(7): 1391-1405.
[11]	WEI Haitao, DU Yunyan, ZHANG Jiali, SUN Luyao. An Adaptive Segmentation Algorithm for Spatial Data based on CNN [J]. Journal of Geo-information Science, 2022, 24(6): 1099-1106.
[12]	GENG Jiachen, SHEN Shi, CHENG Changxiu. Spatio-temporal Evolution and the Multi-scale Socio-economic Influencing Mechanism of PM_2.5 in the Yellow River Basin during the China's 13^th Five-Year Plan [J]. Journal of Geo-information Science, 2022, 24(6): 1163-1175.
[13]	YAO Jinyi, WANG Juanle, YAN Xinrong, WEI Haishuo, Altansukh Ochir, Davaadorj Davaasuren. Water Information Extraction of Selenga River Basin in Mongolia based on Deep Neural Network [J]. Journal of Geo-information Science, 2022, 24(5): 1009-1017.
[14]	ZHANG Wenxuan, WANG Juanle. Flood Monitoring of Heilongjiang River Basin in China and Russia Transboundary Region based on SAR Backscattering Characteristics [J]. Journal of Geo-information Science, 2022, 24(4): 802-813.
[15]	LIN Yu, ZHAO Quanhua, LI Yu. A Remote Sensing Image Classification Method based on Deep Transitive Transfer Learning [J]. Journal of Geo-information Science, 2022, 24(3): 495-507.