PROGRESS IN GEOGRAPHY ›› 2018, Vol. 37 ›› Issue (9): 1257-1267.doi: 10.18306/dlkxjz.2018.09.008

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Spatial structures and influencing factors of multiple urban networks based on the perspective of directed-multivalued relation

Qiong SONG1(), Xinzheng ZHAO1, Tongsheng LI1,*(), Jingyu LIU2   

  1. 1. College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China
    2. College of Environment and Planning, Henan University, Kaifeng 475004, Henan, China
  • Received:2017-12-14 Revised:2018-05-03 Online:2018-09-28 Published:2018-09-28
  • Contact: Tongsheng LI E-mail:songqiongnwu@163.com;leetang@nwu.edu.cn
  • Supported by:
    Project of Humanities and Social Sciences of Ministry of Education, China, No.14YJCZH222;Natural Science Foundation of MOE in Shaanxi Province, No.14JK1753;Graduate Student Innovation Project of Northwest University, No.YZZ17148

Abstract:

Urban system is one of the core subjects of human-economic geography. From the perspective of directed-multivalued relation, taking the Zhongyuan urban agglomeration as the case study area, a comparative study on spatial structures and influencing factors of multiple urban networks—static network, Baidu information network, and comprehensive transportation network—will provide a new train of thought for urban system research under relational transition. This study analyzed the hierarchical structure and the node structure of the networks of the Zhongyuan urban agglomeration, to extract generality and particularity of the three networks mentioned above. Furthermore, we built a relational regression model with the help of the quadratic assignment procedure (QAP) method to dissect the influencing factors of these three networks, from the aspects of economy, culture, administration, and time distance. The empirical results are as follows: (1) The correlation coefficients of the three networks are over 0.582, presented as Baidu information versus comprehensive transportation > Baidu information versus static > Comprehensive transportation versus static, and the overall similarity is stronger than the difference. (2) Integrating the three networks, the Zhongyuan urban agglomeration, a mononuclear spatial structure cored by Zhengzhou, consisted of two regional development belts along with the Beijing-Guangzhou railway and the Lianyungang-Lanzhou railway, and formed a central area with obvious advantages of radiation and concentration with a backbone network constituted by Zhengzhou, Kaifeng, Xinxiang, Luoyang, and Xuchang. Outside of the central area, the three networks showed obvious particularity. The radiation and agglomeration ability of cities have negative correlation in static network, while showed positive correlation in Baidu information network and comprehensive transportation network. (3) The seven influencing factors have different effects on the three networks. Enterprise cooperation, industrial structure similarity, and economic system proximity lead to the similarity of the three networks. Meanwhile, income gap, cultural similarity, administrative affiliation, and average time distance lead to their differences.

Key words: multiple urban networks, spatial structure, relational regression model, influencing factors, directed-multivalued relation, Zhongyuan urban agglomeration