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How to determine city hierarchies and spatial structure of a megaregion?

Authors :
Yanyan Gu
Run Shi
Yan Zhuang
Qingquan Li
Yang Yue
Source :
Geo-spatial Information Science, Vol 27, Iss 2, Pp 276-288 (2024)
Publication Year :
2024
Publisher :
Taylor & Francis Group, 2024.

Abstract

ABSTRACTMegaregion has emerged as a global urban form, typically based on the polycentric strategy to enhance regional development. How to measure megaregional spatial structure and discriminate different roles of cities has become increasingly important to enrich the knowledge of the formation of a megaregion. Meanwhile, various indices have been used to identify vital nodes in the field of complex network. Which indices, however, are suitable for megaregion analysis remain unsolved. To address this requirement, this study first reviewed the typical indices for identifying vital nodes in the complex network theory, and pointed out that in a weighted city network scenario, weighted degree centrality, hub & authority score, and S-core decomposition (which represent network centrality, connectivity, and structures, respectively) are suitable for analyzing megaregional spatial structures. Then, we explored the city hierarchies and spatial structure in Guangdong Province, China, using the three indices. The hierarchical structure of the weighted city network in Guangdong Province had been identified using S-core decomposition. From the perspective of polycentric structure, Guangzhou and Shenzhen have the strongest node degrees and strength of mobility flows, while the Guangzhou-Dongguan-Shenzhen corridor has been identified via the hub & authority score which is designed to evaluate the connectivity in a weighted network. Moreover, we conducted a comparison analysis of three indices. The findings of this study not only enrich the understanding of city hierarchies and the structure of a megaregion, but also highlight that although various indices are available, they should be applied selectively in accordance with the study context.

Details

Language :
English
ISSN :
10095020 and 19935153
Volume :
27
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Geo-spatial Information Science
Publication Type :
Academic Journal
Accession number :
edsdoj.8e0f127b8e124896825873103d3a7724
Document Type :
article
Full Text :
https://doi.org/10.1080/10095020.2022.2161425