• 论文 •

### 中国航空网络空间结构的复杂性

1. 1. 中国科学院地理科学与资源研究所, 北京 100101;
2. 美国路易斯安那州立大学, 巴吞鲁日 70803;
3. 中国交通运输协会, 北京 100053
• 收稿日期:2009-02-10 修回日期:2009-06-18 出版日期:2009-08-20 发布日期:2009-08-20
• 作者简介:王姣娥 (1981-), 女, 博士后, 湖南涟源人, 主要从事交通运输、城市交通、区域发展等研究。 E-mail: jiaoewang@163.com
• 基金资助:

国家自然科学重点基金项目(40635026);; 中国博士后科学基金项目(20080440065)

### Spatial Structural Characteristics of Chinese Aviation Network Based on Complex Network Theory

WANG Jiao'e1, 2,  MO Huihui1, 3,  JIN Fengjun1

1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
2. Louisiana State University, Baton Rouge, LA 70803, USA;
3. China Communications and Transportation Association, Beijing 100053, China
• Received:2009-02-10 Revised:2009-06-18 Online:2009-08-20 Published:2009-08-20
• Supported by:

Key Project of National Natural Science Foundation of China, No.40635026; Project of China Postdoctoral Science Foundation, No.20080440065

Abstract:

Today, air transport plays an important role in transportation systems, especially for medium and long distance. Based on complex network theory, Chinese aviation network is abstracted as a set of edges (linkages) connecting a set of nodes (cities), and 144 cities and 1018 air routes were chosen for this research operated from winter 2007 to spring 2008. Then, this paper analyzes the spatial structure of Chinese aviation network using indices of degree distribution, the average path length, the clustering coefficient, degree-degree correlation, and clustering-degree correlation. Degree is the number of edges that a node shares with others, and thus symbolizes the importance of the node in the network. Degree distribution is used to reflect the distribution function of degree and donates the statistical characteristics of a network. Average path length is defined as the average number of edges along the shortest paths for all possible node-pairs in the network and it is a measurememt of the efficiency of transportation network. The clustering coefficient of a node is the ratio of actual edges to maximal edges between nodes which are directly connected with the node. The clustering coefficient of the whole network is the average of all individuals. As for an airport network, the average path length and the clustering coefficient are the two most important parameters reflecting network properties and configurations. The results show that Chinese aviation network has a relatively small average path length of 2.23 and a relatively large cluster coefficient of 0.69. More importantly, the accumulative degree distribution follows an exponential expression, with significance of 0.977. Therefore, Chinese aviation network shows the characteristic of a "Small World" network. Due to most new airports' preferences for direct connections with the three top-level national hubs: Beijing, Shanghai, and Guangzhou, the network hierarchy has no distinct difference with the exception of the top one. Also, the spatial distribution of Chinese aviation network is imbalanced according to the indices of degree, clustering coefficient and accessibility index. Besides, the correlation coefficients of these indices mentioned above are analyzed. The results show that there are negative degree correlation, nonlinear clustering-degree correlation, positive accessibility-degree correlation, and slightly positive clustering-accessibility correlation. In conclusion, with the rapid development of air transport demand driven by the market economy, Chinese aviation network will further evolve to a combined model of "Scale Free" and "Small World" networks, and its spatial structure will be more complex.