A Multi-scale Network-based Topological Analysis of Urban Road Networks in Highly Populated Cities
Authors: Kozhabek, A. and Chai, W.K.
Journal: Environment and planning. B: Urban analytics and city science
eISSN: 2399-8091
ISSN: 2399-8083
Abstract:In this paper, we study urban road infrastructure in densely populated cities. As the subject of our study, we choose road networks from 35 populous cities worldwide, including China, India, Pakistan, Colombia, Brazil, Bangladesh, and Cˆote d’Ivoire. We abstract road networks as complex systems, represented by graphs consisting of nodes and links, and employ tools from network science to study their topological properties. Our multi-scale analysis includes macro-, meso-, and micro-scale perspectives, deriving insights into both common and unexpected patterns in these networks. At the macro-scale, we examine the global properties of these networks, summarizing the results in radar diagrams. This analysis reveals significant correlations among key metrics, indicating that more robust networks tend to be more efficient, while diameter and average path length show negative correlations with other properties. At the meso-scale, we explore the existence of sub-structures embedded within the road networks using two main concepts, namely community and core-periphery structures. We find that while these densely populated city road networks show particularly strong community structures (high modularity values, close to 1.0) that are not typical to other networks, they exhibit a low level of presence of core-periphery structures, with an average coreness of 6.3%. This points to the cities being polycentric. At the micro-scale, we find nodal-level properties of the network. Specifically, we compute the various centrality measures and examine their distributions to capture the prevalent characteristics of these networks. We observe that the centrality measures present different distribution patterns. While the degree distribution demonstrates a limited range of degree values, the betweenness centrality distribution follows a power law, and the closeness centrality exhibits a binomial distribution— yet these patterns remain consistent across the studied cities. Overall, our multi-scale analysis provides valuable insights into the topological properties of urban road networks, informing city planning, traffic management, and infrastructure development in similar urban environments.
https://eprints.bournemouth.ac.uk/40703/
Source: Manual
A Multi-scale Network-based Topological Analysis of Urban Road Networks in Highly Populated Cities
Authors: Kozhabek, A. and Chai, W.K.
Journal: Environment and planning. B: Urban analytics and city science
ISSN: 2399-8083
Abstract:In this paper, we study urban road infrastructure in densely populated cities. As the subject of our study, we choose road networks from 35 populous cities worldwide, including China, India, Pakistan, Colombia, Brazil, Bangladesh, and Cˆote d’Ivoire. We abstract road networks as complex systems, represented by graphs consisting of nodes and links, and employ tools from network science to study their topological properties. Our multi-scale analysis includes macro-, meso-, and micro-scale perspectives, deriving insights into both common and unexpected patterns in these networks. At the macro-scale, we examine the global properties of these networks, summarizing the results in radar diagrams. This analysis reveals significant correlations among key metrics, indicating that more robust networks tend to be more efficient, while diameter and average path length show negative correlations with other properties. At the meso-scale, we explore the existence of sub-structures embedded within the road networks using two main concepts, namely community and core-periphery structures. We find that while these densely populated city road networks show particularly strong community structures (high modularity values, close to 1.0) that are not typical to other networks, they exhibit a low level of presence of core-periphery structures, with an average coreness of 6.3%. This points to the cities being polycentric. At the micro-scale, we find nodal-level properties of the network. Specifically, we compute the various centrality measures and examine their distributions to capture the prevalent characteristics of these networks. We observe that the centrality measures present different distribution patterns. While the degree distribution demonstrates a limited range of degree values, the betweenness centrality distribution follows a power law, and the closeness centrality exhibits a binomial distribution— yet these patterns remain consistent across the studied cities. Overall, our multi-scale analysis provides valuable insights into the topological properties of urban road networks, informing city planning, traffic management, and infrastructure development in similar urban environments.
https://eprints.bournemouth.ac.uk/40703/
Source: BURO EPrints