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On the degree correlation of urban road networks
Authors:Jing Tian  Huaqiang Fang  Yiheng Wang  Chang Ren
Institution:1. School of Resource and Environment Science, Wuhan University, Wuhan, China;2. Key Laboratory of Geographic Information System, Wuhan University, Wuhan, China;3. Key Laboratory of Digital Mapping and Land Information Application Engineering, National Administration of Surveying, Mapping and Geoinformation, Wuhan University, Wuhan, China;4. Institute of Remote Sensing and Geographic Information System, Peking University, Beijing, China;5. State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, China
Abstract:Recent advances in network science and the development of volunteered geographic information (VGI) have created new research opportunities in the topological analysis of road networks. The degree correlation of road networks is rarely studied. This study applied four measures, including the average degree of nearest neighbor, correlation profile, Newman's assortativity coefficient, and Litvak–Hofstad's assortativity coefficient, to measure the degree correlations of road networks represented as dual graphs of strokes, axial lines, and named roads. After investigating 100 road networks worldwide obtained from OpenStreetMap, it has been found that road networks are mostly disassortative or uncorrelated in stroke and named road representations, but assortative when represented as axial lines. Inconsistency in different measures persists regardless of method of representation; therefore, qualitative dichotomy or trichotomy is insufficient to describe the actual connection pattern in road networks. A taxonomy of road network assortativity is proposed. Two of the proposed disassortative types are associated with the absence of a grid pattern and are less robust than the typical disassortative type.
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