Abstract

In the context of rapid urbanization in developing countries, the spatial organization of cities has been progressively restructured over the past decades. However, little has been done to understand how the physical expansion affected the reorganization of socioeconomic spaces in cities. This study explores the association between various street network metrics and urban vitality and how it changes across different scales using geographic big data through a case study of Wuhan, China. Urban vitality is characterized by four components: concentration, accessibility, livability, and diversity. The new technique of spatial design network analysis (sDNA) is employed to characterize street network metrics, including connectivity, closeness, betweenness, severance, and efficiency, with 16 localized network variables. Furthermore, the stratified spatial heterogeneity between street network metrics at multiple scales and the four components of urban vitality is investigated using the Geodetector tool. First, concentration, accessibility, and diversity decline with distance from the urban center, whereas livability has a fluctuating upward trend with distance from the urban core. Second, the correlation between street network characteristics and urban vitality is sensitive to different spatial scales. Third, connectivity explains the largest amount of the variance in urban vitality (over 40%), while both betweenness and closeness explain roughly 28% of urban vitality. Efficiency and severance contribute 22 and 10% to the spatial heterogeneity of urban vitality, respectively. The study sheds light on the mechanisms between street configurations and urban vitality from the multi-scalar perspective. Some implications are provided for the improvement of the streets' urban vitality.

Highlights

  • The world is experiencing rapid urbanization, especially in developing countries [1]

  • It is interesting to explore the reason for the curious relation between geometry and urban vitality

  • The correlation coefficients and the q statistics between various spatial network metrics and urban vitality from the multiscalar perspective shed light on the details of their precise causal mechanisms. Some metrics, such as density, connectivity, and betweenness calculated by spatial network analysis, are not new

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Summary

Introduction

The world is experiencing rapid urbanization, especially in developing countries [1]. By 2050, two thirds of the world’s population will reside in cities. Urbanization visibly improves standards of living, it carries risks, such as shrinking or ghost cities, which are associated with considerably low urban vitality [2,3,4,5]. As an important proxy for the sustainability of urban growth [6], urban vitality measures the attractiveness and competitiveness of a city. As a new source of urban competitiveness, urban vitality helps a city gain comparative advantages and produce sustainable economic growth and endure regional innovation [7, 8]. Understanding urban vitality is essential to urban health monitoring, compact urban development, innovative urban growth, and peopleoriented urbanization

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