| 中国城际公路零担专线网络空间结构特征 |
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| 引用本文： | 施路,杜国鹏,庞鸿立,王晓婷,郑中阳,李国旗.中国城际公路零担专线网络空间结构特征[J].热带地理,2022,42(11):1806-1815. |
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| 作者姓名： | 施路 杜国鹏 庞鸿立 王晓婷 郑中阳 李国旗 |
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| 作者单位： | 1.中铁二院工程集团有限责任公司，成都 610031;2.西南交通大学，交通运输与物流学院，成都 610031;3.西南交通大学，土木工程学院，成都 610031;4.西南交通大学，材料科学与工程学院，成都 610031;5.西南交通大学，电气工程学院，成都 610031 |
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| 基金项目： | 国家自然科学基金项目(42271195);四川省科技厅软科学研究项目(21RXX0635) |
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| 摘 要： | 基于社会网络分析方法，利用国家交通运输物流公共信息平台2018年全国地级及以上城市的公路零担专线数据，从城市节点、城际联系、子网络3个层面对中国城市网络结构特征进行识别，结果表明：1）上海、天津、郑州、广州、杭州在网络中处于主导性地位，根据货流组织系数，可将城市节点划分为强中心、次强中心、弱中心、从属型4种类型。2）在首位联系总量排名前十的城市中，输出型城市和输入型城市的比例为4∶1，反映货流流向的不均衡性。由公路零担专线数据刻画的网络空间呈现显著的距离衰减规律，集中在500 km的专线数量占比为41.9%。3）公路零担专线网络形成东北―冀鲁蒙社区、中原社区、关中社区、江淮社区、泛珠三角―长三角社区、长株潭社区6个具有显著地域特征的城市社区，社区结构表现出明显的空间集聚和跨行政区特征。最后，提出以下建议：增强成渝城市群公路零担专线服务能力，发挥核心城市产业集聚和带动作用；优化边缘城市产业结构，加强交通与产业融合；积极引导无车承运人平台发挥网络规模化效应，提高公路货运组织效率。
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| 关 键 词： | 公路零担专线 节点 城际联系 社会网络 距离衰减定律 中国 |
| 收稿时间： | 2021-12-14 |
Urban Network Structures and Organization Models Based on the Road Less-Truck-Load Dedicated Line Data in China |
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| Lu Shi,Guopeng Du,Hongli Pang,Xiaoting Wang,Zhongyang Zheng,Guoqi Li.Urban Network Structures and Organization Models Based on the Road Less-Truck-Load Dedicated Line Data in China[J].Tropical Geography,2022,42(11):1806-1815. |
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| Authors: | Lu Shi Guopeng Du Hongli Pang Xiaoting Wang Zhongyang Zheng Guoqi Li |
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| Institution: | 1.China Railway Eryuan Engineering Group Co. Ltd. , Chengdu 610031, China;2.School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China;3.School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China;4.Institute of Materials Science and Engineering, Southwest Jiaotong University, Chengdu 610031, China;5.School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China |
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| Abstract: | Against the background of the increasing trend of fragmentation of freight demand, the spatial structure analysis of urban networks using road Less-Truck-Load (LTL) dedicated lines has positive implications for enriching the flow space theory and empirical evidence. Based on the social network analysis method, this study used the data of the national prefecture-level and above cities' road LTL dedicated lines on the China Communications Logistics LOGINK System in 2018, and conducted feature mining of Chinese city network relationships from the perspective of road LTL dedicated lines at three levels: city nodes, intercity connections, and sub-networks. The results show the following: (1) Shanghai, Tianjin, Zhengzhou, Guangzhou, and Hangzhou dominated the network. Based on the cargo flow organization coefficients, urban nodes can be divided into four types: strong center, second strong center, weak center, and subordinate. The number of high-grade cities in the network was relatively small and mainly concentrated in the eastern and central regions. The imbalance in the spatial distribution is obvious. (2) Among the top ten cities in terms of the amount of first contact, the ratio of export-oriented cities to import-oriented cities is 4:1, which reflects the imbalance in cargo flow. The network space carved by the road LTL dedicated lines data showed a significant distance attenuation law. The road LTL dedicated lines connections are mainly distributed in the intercity range of 0-200 km and the interprovincial range of 200-500 km, with the number of special lines concentrated in 500 km accounting for 41.9%. (3) The community detection algorithm was used to identify six urban communities with significant regional characteristics, including the Northeast Jilumeng, Zhongyuan, Guanzhong, Jianghuai, Pan-Pearl, Delta-Yangtze River Delta, and Changzhutan communities. The community structures showed clear spatial agglomeration and cross-administrative features. (4) To enhance the status of the nodes of the road LTL network and optimize the organization of the network space, the following suggestions are put forward: Urban networks based on the road LTL dedicated line data should enhance the service capacity of the Chengdu-Chongqing urban agglomeration road LDL line, strengthen the industrial agglomeration and driving role of core cities, optimize the industrial structure of marginal cities, strengthen the integration of transportation and industry, and actively guide the car-free carrier platform to improve the efficiency of road freight organization. In future studies, long-term cycles and multiple data sources should be enhanced to verify the validity and reliability of the findings. |
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| Keywords: | road LTL dedicated line node city pair social network law of distance attenuation China |
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