Fractal evolution of urban street networks in form and structure: a case study of Hong Kong

ABSTRACT

Cities are spatially evolving complex systems. The order and pattern beneath the apparent chaos and diverse physical forms of cities are still unclear. How the form and structure of a city evolve to improve its functions needs further exploration. To fill thisgap, we examine the geometric fractal (GF), the topological fractal (TF), and the hierarchical fractal (HF) evolution of cities by taking Hong Kong street networks from year 1971 to 2018 as an example. We find that these networks keep to be fractals both in form and structure. The values of GF, TF, and HF dimensions increase with fluctuations, revealing a more mature and complex street network. The radius-length GF dimensions demonstrate the bi-fractal property, with values ranged 1.653–1.832 and 0.677–0.892, respectively, reflecting a core-periphery pattern. The values of TF dimensions increase steadily with a wider gap to GF dimensions, indicating progressively structural optimization of street networks. These street networks keep showing fractal properties in form and structure through spatial extension, local densification, vertical stratification, hierarchies enrichment, and shortcuts construction. Moreover, street networks are GFs and TFs at the city, county, and MSA scales. The discoveries advance our understanding of urban development.

KEYWORDS:

• Geometric fractal
• topological fractal
• hierarchical fractal
• fractal evolution

Acknowledgements

We wish to thank the editor and three anonymous reviewers for their constructive and useful comments, which led to significant improvement in the quality of this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data and Codes Availability Statement

The data and codes that support the findings of this study are available with the identifier(s) at the link https://doi.org/10.6084/m9.figshare.16437627.v1.

Additional information

Funding

This work was jointly supported by the National Natural Science Foundation of China [No.42171420 and 42101442], and the Natural Science Foundation of Shanghai [No. 21ZR1421100].

Notes on contributors

Hong Zhang

Hong Zhang is currently an associate professor at East China Normal University, working in the field of spatial complexity and urban geography. Before joining East China Normal University in 2020, she had worked at Southwest Jiaotong University (as associate professor) and the Hong Kong Polytechnic University (as research associate). Dr. Zhang obtained her PhD in Cartography and GIS from the Hong Kong Polytechnic University in 2011, BSc in Tourism Management and MSc in Human Geography from Hubei University in 2000 and 2004 respectively.

Tian Lan

Tian Lan is currently working as a research associate in the Hong Kong Polytechnic University. He obtained PhD from the same university in 2020. His research interests include map generalization, GeoAI, urban allometry, and fractal.

Zhilin Li

Zhilin Li is currently a professor at Southwest Jiaotong University, working in the field of cartography and geoinformation as well as their applications in high-speed railway safety. Before joining Southwest Jiaotong University in 2020, he had worked at the Hong Kong Polytechnic University (as assistant professor, associate professor, professor and chair professor), Curtin University of Technology (as lecturer), Berlin University of Technology (as research fellow), Southampton University (as research fellow) and Newcastle upon Tyne (as research associate). Prof. Li obtained his PhD from Glasgow University in 1990 and BSc from Southwest Jiaotong University in 1982.