交通运输系统工程与信息

交通运输系统工程与信息 ›› 2021, Vol. 21 ›› Issue (3): 26-33.

• 综合交通运输体系论坛 • 上一篇    下一篇

2000—2018年全国民航网络结构特征及演化

曹炜威*1，李政2，冯项楠3, 4   

  1. 1. 中国民用航空飞行学院，民航飞行技术与飞行安全重点实验室，四川 广汉 618307；2. 四川省国土空间规划研究院，成都 610081；3. 西南交通大学，经济管理学院，成都 610031；4. 复旦大学，管理学院，上海 200433
  • 收稿日期:2021-01-10 修回日期:2021-03-19 出版日期:2021-06-25 发布日期:2021-06-25
  • 作者简介:曹炜威(1989- )，男，河南商丘人，讲师，博士。
  • 基金资助:

    国家自然科学基金/ National Natural Science Foundation of China(71802166)；四川省科技支撑计划/ Program of Science and Technology of Sichuan Province(2020YJ0325)；学院科研基金面上项目/ Program of Science and Research of Civil Aviation Flight University of China(J2021-110)。

Structural Evolution of China's Air Transport Network Across 2000—2018

CAO Wei-wei*1 , LI Zheng2 , FENG Xiang-nan3, 4   

  1. 1. Key Laboratory of Flight Techniques and Flight Safety, Civil Aviation Flight University of China, Guanghan 618307, Sichuan, China; 2. Sichuan Provincial Land and Space Planning Research Institute, Chengdu 610081, China; 3. School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China; 4. School of Management, Fudan University, Shanghai 200433, China
  • Received:2021-01-10 Revised:2021-03-19 Online:2021-06-25 Published:2021-06-25

PDF

摘要：

航空网络在实现区域互联互通，加强社会经济体发展与合作中起着重要作用。基于网络分析方法，采用2000—2018年航班数据，探索研究全国民航网络结构特征及其变化规律。结果表明：网络密度表现出先降低后升高的趋势，具有异速增长特征，航班密度则先升高后降低。网络具有小世界特征，特征路径长度和集聚系数分别呈下降态势和倒“U”型变化。节点度和邻近中心性均值增加，城市直接连通性和全局可达性显著提高。不同中心性指标之间具有较高相关性，度与邻近中心性相关性最高，但随时间变化不明显；度与中介中心性、中介中心性与邻近中心性的相关性较低，整体呈上升趋势。航班分布空间分异特征明显，东部地区城市间航班联系数量占比最高，但呈下降趋势；东-中、东-西部地区城市间航班联系数量占比提升，民航网络的发展重心呈现向西偏移趋势。

关键词: 航空运输, 演化过程, 网络分析, 结构特征, 航班时刻表

Abstract:

Air transport network plays an important role in connecting regions and facilitating the development of the social economy. China has the second- biggest aviation transport scale in the world, which brings time- space compression and accelerates socio-economic development steadily. By utilizing social network methods, this paper investigates the structural characteristics and evolution of China's air transport network (CATN) from 2000 to 2018 based on the flight schedule data. Firstly, CATN presents an allometric growth pattern. Network density decreases firstly and then increases, while flight density presents an inverse pattern. CANT has been characterized by small-world properties. The characteristic path length is reduced from 2.115 to 1.965, indicating an enhancement of accessibility, while the clustering coefficient shows an inverse“U”change pattern. Secondly, both the average degree and closeness of cities increase, implying an improvement of connectivity and global accessibility. Degree and closeness have the biggest correlation among different centrality measures, but the correlation coefficient has no obvious fluctuation over time. Furthermore, the correlation coefficient between betweenness and degree and the correlation coefficient between betweenness and closeness both tend to increase. Finally, the spatial distributions of flights are extremely uneven and heterogeneous. Flights between cities in the eastern region have the highest proportion, but it shows a downward trend. The eastern region has the highest proportion of inter-city flight connections but presents a descending trend. Meanwhile, the proportions of flights between cities in the east- central and east- western regions are increased. The development center of CATN is shifting westward.

Key words: air transportation, evolution, network analysis, structure, flight schedules

中图分类号: