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基于有向转变中心性与控制力的长三角城市网络空间结构分析
引用本文:文超,詹庆明,刘达,米子豪.基于有向转变中心性与控制力的长三角城市网络空间结构分析[J].地理科学,2021,41(6):971-979.
作者姓名:文超  詹庆明  刘达  米子豪
作者单位:武汉大学城市设计学院,湖北武汉430072
基金项目:广东省重点领域研发计划项目(2020B0202010002);国家自然科学基金项目(52078389);中国工程科技发展战略湖北研究院咨询项目(HB2019B14)
摘    要:采用腾讯人口迁徙数据构建长三角的有向城市网络,利用有向转变中心性与控制力研究人口流动视角下的区域空间结构。研究表明,长三角地区已形成“区域性核心-局域性核心-人口扩散型城市”联动发展的多核心、等级化、网络化的空间结构。在该地区同时存在“同城化”“核心-边缘”空间发展模式。长三角41个城市可划分为7种发展类型,其中资源集聚型城市对人口资源存在普遍争夺的情况。研究进一步分析了长三角地区有向城市网络的空间结构及发展特征,并对相关影响因素进行分析,为长三角地区实现高质量发展的区域战略布局提供支撑。

关 键 词:有向转变中心性  有向转变控制力  区域空间结构  长三角  人口流动
收稿时间:2020-02-16
修稿时间:2020-10-16

Urban Network Structure Analysis of the Yangtze River Delta Based on Directed Alternative Centrality and Power
Wen Chao,Zhan Qingming,Liu Da,Mi Zihao.Urban Network Structure Analysis of the Yangtze River Delta Based on Directed Alternative Centrality and Power[J].Scientia Geographica Sinica,2021,41(6):971-979.
Authors:Wen Chao  Zhan Qingming  Liu Da  Mi Zihao
Affiliation:School of Urban Design, Wuhan University, Wuhan 430072, Hubei, China
Abstract:The rise of urban network research provides a new perspective to analyze the spatial structure of urban agglomeration. The Yangtze River Delta urban agglomeration, one of the most developed and the most active area of human migration in China, has gradually formed a network development pattern, and it is of great significance to study its network spatial structure. This article used the Tencent’s population migration data to construct a directed weighted urban network. The directed alternative centrality (DAC) and power (DAP) were used to measure the characteristics of urban network spatial structure in the Yangtze River Delta. Then the related influencing factors on DAC and DAP of the cities were studied. The results showed that the Yangtze River Delta urban agglomeration has formed a multi-core and hierarchical network structure. Specifically, Shanghai was the core city facing the whole Yangtze River Delta, while Suzhou (Jiangsu), Nanjing, Hangzhou, Hefei, Wuxi, and Ningbo were the core cities facing the local area. There were several spatial development patterns including “urban integration” and “core-periphery” patterns. For example, the population flow connection between Shanghai and Suzhou (Jiangsu) showed that there was an obvious urban integration development mode. The population flow connections between Hangzhou and Shaoxing, Wuxi and Changzhou showed a kind of primary urban integration development patterns, while that between Hefei and Lu’an presented a significant core-periphery development model. The connection between Shanghai, Wuxi, and Ningbo and some cities with population diffusion revealed that there was a development model of “strong core-general core-periphery”. According to the results of DAC, DAP, and the population hinterlands, there were 7 different development types of the 41 cities in this region. The population hinterlands of core cities were generally overlapped and competed. For example, the population hinterlands of Shanghai covered the entire region, and those of Soochow and Nanjing were mainly in Jiangsu and some cities in Anhui Province. The population hinterlands of Hangzhou mainly covered cities in the northern Zhejiang and southern Anhui. Generally, the migration of people from edge cities, such as Lu’an, Huainan, Yancheng, and Quzhou, tends to go to more than one core city, which may lead to fierce competitions among core cities, such as Shanghai, Suzhou (Jiangsu), Nanjing, and Hangzhou. Correlation analysis showed that the city’s economy, administrative level, employment opportunities and income level had great impacts on the DAC and DAP of one city, and the accessibility had some impacts on the DAP of the cities. The study further summarized the spatial structure and development characteristics of the directed urban network, and could provide supports for achieving a high-quality and coordinated development of the Yangtze River Delta urban agglomeration.
Keywords:directed alternative centrality  directed alternative power  regional spatial structure  the Yangtze River Delta  population flow  
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