Analysis of the evolution of China's urban network pattern based on aviation connection network

doi:10.3969/j.issn.1004-9479.2022.01.2020744

Abstract

Abstract:

Based on airports' passenger throughput and airlines' passenger flow of China in 2000, 2005, 2010 & 2017(excluding Hong Kong, Macao and Taiwan), applied complex network, GIS and geographical detector to analyze the characteristics of urban network pattern reflected by China's aviation connections, and explored the evolution process and influencing factors of urban network in China. The results show that China has formed a multi-level, multi-center network pattern with Shanghai, Beijing, Guangzhou and Chengdu as the first-level core cities. The urban network has gradually evolved from a "three-center" structure to a "four-center" structure. The distribution of central cities has spatial heterogeneity, showing the situation of "tripartite confrontation, prominent in the west, weak in the middle"; the national urban network has obvious scale-free, small-world characteristics and strong agglomeration. The national central cities mainly concentrated in the southeast coast before 2005, and gradually spread to the central and western regions after 2005. The evolution of China's urban network pattern is driven by many factors such as policy support, tourism development level, economic foundation, and public services.

Key words: aviation, urban network, complex networks, geographical detector, China

摘要：

运用2000、2005、2010、2017年全国民航机场及航线客流的截面数据（不含港澳台地区），结合复杂网络、GIS与地理探测器方法，刻画了21世纪以来我国航空联系网络所反映的城市网络格局，并分析其演变过程及影响因素。结果表明：中国目前形成了以上海、北京、广州、成都为一级核心城市，多层次、多中心的网络格局，并由“三中心”逐渐演变为“四中心”结构；中心城市分布具有明显的东西差异，呈现“三足鼎立、西部突出、中部薄弱”态势；全国城市网络具有无标度、小世界特征及较强的集聚性，中心城市在2005年前向东南沿海集聚，而后向中西部地区扩散，集聚性有所降低；中国城市网络格局的演变由政策支持、旅游发展水平、经济基础、产业结构等多因素共同驱动。

关键词: 航空, 城市网络, 复杂网络, 地理探测器, 中国

Tingting ZHANG, Ying CHEN, Menglin WANG. Analysis of the evolution of China's urban network pattern based on aviation connection network[J]. World Regional Studies, 2022, 31(1): 166-176.

张婷婷, 陈瑛, 王孟林. 基于航空联系的中国城市网络格局演变分析[J]. 世界地理研究, 2022, 31(1): 166-176.

Figures/Tables 9

Tab.1 Number of nationally certified transport airports in 2017

地区	颁证运输机场数量/个	颁证运输机场数量占全国比重	民航运输机场旅客吞吐量占全国比重	民航运输机场货邮吞吐量占全国比重
东北地区	27	11.8%	6.3%	3.4%
东部地区	54	23.6%	53.5%	75.2%
西部地区	114	49.8%	29.6%	15.1%
中部地区	34	14.8%	10.6%	6.3%

Fig.1 Ranking scale diagram of the top 100 cities of China in 2000 and 2017

Fig.2 Evolution of China's urban network based on aviation network in 2000，2005，2010 and 2017注：本图基于国家测绘地理信息局标准地图服务网站下载的审图号为GS（2016）2884 号的标准地图制作，底图无修改，以下各图同。

Fig.3 Change of national urban degree and weighted degree by node scale in 2017 （top 50）

Fig.4 The evolution of urban spatial pattern based on weighted degree in 2000， 2005， 2010 and 2017

Fig.5 The evolution of urban spatial pattern based on closeness centrality in 2000， 2005， 2010 and 2017

Fig.6 The evolution of urban spatial pattern based on clustering coefficient in 2000， 2005， 2010 and 2017

Tab.2 Influencing factors of urban network pattern

影响因素	代表变量/单位
人口集聚程度 ( $x 1)$	市辖区人口密度 /（人/平方千米）
城市等级 $(x 2)$	行政区划级别
地区经济实力 $(x 3$ )	地区生产总值/万元
人民生活水平 ( $x 4$ )	人均生产总值/元
产业结构 $(x 5$ )	三产增加值占比/%
公共服务水平 $(x 6$ )	地方一般公共预算支出/万元
旅游发展水平 $(x 7$ )	旅游总收入/万元
对外开放程度 $(x 8$ )	货物进出口额/万美元
基础设施建设 $(x 9$ )	人均城市道路面积 /（平方米/人）

Tab.2 Influencing factors of urban network pattern

影响因素	代表变量/单位
人口集聚程度 ( $x 1)$	市辖区人口密度 /（人/平方千米）
城市等级 $(x 2)$	行政区划级别
地区经济实力 $(x 3$ )	地区生产总值/万元
人民生活水平 ( $x 4$ )	人均生产总值/元
产业结构 $(x 5$ )	三产增加值占比/%
公共服务水平 $(x 6$ )	地方一般公共预算支出/万元
旅游发展水平 $(x 7$ )	旅游总收入/万元
对外开放程度 $(x 8$ )	货物进出口额/万美元
基础设施建设 $(x 9$ )	人均城市道路面积 /（平方米/人）

Tab.3 Detection results of influencing factors of urban network pattern (2017)

因	加权度（ $y 1$ ）		接近中心性（ $y 2$ ）		聚类系数（ $y 3$ ）
子	q值	p值	q值	p值	q值	p值
$x 1$	0.231	0.000	0.140	0.000	0.159	0.000
$x 2$	0.630	0.000	0.619	0.000	0.450	0.000
$x 3$	0.783	0.000	0.355	0.000	0.180	0.000
$x 4$	0.211	0.000	0.250	0.000	0.198	0.000
$x 5$	0.172	0.000	0.175	0.000	0.134	0.000
$x 6$	0.785	0.000	0.366	0.000	0.196	0.000
$x 7$	0.798	0.000	0.439	0.000	0.349	0.000
$x 8$	0.707	0.000	0.227	0.000	0.091	0.000
$x 9$	0.008	0.000	0.058	0.000	0.086	0.000

Tab.3 Detection results of influencing factors of urban network pattern (2017)

因	加权度（ $y 1$ ）		接近中心性（ $y 2$ ）		聚类系数（ $y 3$ ）
子	q值	p值	q值	p值	q值	p值
$x 1$	0.231	0.000	0.140	0.000	0.159	0.000
$x 2$	0.630	0.000	0.619	0.000	0.450	0.000
$x 3$	0.783	0.000	0.355	0.000	0.180	0.000
$x 4$	0.211	0.000	0.250	0.000	0.198	0.000
$x 5$	0.172	0.000	0.175	0.000	0.134	0.000
$x 6$	0.785	0.000	0.366	0.000	0.196	0.000
$x 7$	0.798	0.000	0.439	0.000	0.349	0.000
$x 8$	0.707	0.000	0.227	0.000	0.091	0.000
$x 9$	0.008	0.000	0.058	0.000	0.086	0.000

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