Abstract
The street network is considered the skeleton of the city structure; it determines the efficiency and productivity of the city in that it acts like blood vessels transporting people, goods, and information. The relationship between street networks and economic development is an important research topic in urban geography. In recent years, complex network theory has been successfully used for understanding the characteristics of street network structure. However, researchers lack an analytical framework and methods for studying the relationship between the morphological structure of urban streets and the economic development level of cities. Accordingly, this paper proposes a methodological framework for first, quantitatively characterizing the urban morphological structure based on open street network data, and second, exploring the relationship between the morphological structure of the urban street and the urban economic development level. The proposed methodology was applied to 31 provincial capital cities in China. The results indicate that urban morphological structure can be quantitatively described by betweenness and closeness centrality extracted from street networks. Cities with similar structures have similar levels of economic development. Moreover, the results suggest a significant positive correlation between street network betweenness centrality Gini coefficients and cities’ economic development levels, indicating that the street network may affect city productivity. This study makes two major contributions to the scholarly literature. Methodologically, the proposed framework provides technical and methodological support for a better understanding of the relationship between cities’ economic development and urban street structure. Empirically, the demonstrated case study may guide decision-making involving regional development and the optimization of urban space.
Highlights
The street network is considered the skeleton of a city as it links geographical units in urban space
To the best of the authors’ knowledge, have considered a city’s street network as a whole and examined whether or not the characteristics of its morphological structures may correlate to the economic development levels of the city
To bridge these research gaps, this paper proposes a general analytical framework for characterizing cities’ street network structures and for quantitatively examining the relationship between a city’s street network structure and its economic development level using open street network data
Summary
The street network is considered the skeleton of a city as it links geographical units in urban space. Studies that fully consider the inter-relationships within the street networks from a micro-scale perspective (e.g., the complex interactions among street network elements) or that provide a quantitative methods framework for studying the morphology and structure of the street networks are still generally lacking. Complex network methods may assist in providing new insight into the relationship between street network structures and urban economic activities Along these lines, many studies have deployed complex network approaches for evaluating the integrity and accessibility of street networks by analyzing street networks’ topological characteristics and their spatial distributions [23,24,25,26]. To the best of the authors’ knowledge, have considered a city’s street network as a whole and examined whether or not the characteristics of its morphological structures may correlate to the economic development levels of the city. The rest of the paper is organized as follows: Section 2 reviews relevant studies that use complex network methods to examine the street network; Section 3 presents the proposed methodological framework and describes analytical methods in detail; Section 4 uses a case study to examine the proposed methods by first briefly introducing the study area and data source, and discussing the results of the case study; and Section 5 concludes the paper with a discussion about the potential applications of the proposed method and how insights gained from the case study may shed light on regional planning and development as well as future research
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