SPATIAL CORRELATION AND EVOLUTION OF COMPLEX URBAN-RURAL ROAD NETWORK OF WUHAN METROPOLITAN AREA
LIU Cheng-liang1, DUAN De-zhong2, YU Rui-lin2, LUO Jing2
1. College of Resources and Environmental Science, East China Normal University, Shanghai 200062, China;
2. School of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China
Abstract：The 21st century is the century of complexity, as a powerful tool for the study of the complexity science and complex systems, complex networks provides a new perspective for the study of complexity. Transportation network is a typical, open and complex giant system, its topology complexity has been a hotspot in the field of complex network research. But both abroad and domestic, from the perspective of geography, the comprehensive analysis of the traffic network space complexity research is relatively weak, and the traffic network topology space correlation almost empty. Therefore, taking Wuhan metropolitan area as an example, based on its urban-rural road network topological spatial database, introducing the complex network statistical characteristics and spatial autocorrelation models and then spatial correlation and its evolution on topological structure of urban-rural road network(URRN) within the last 20 years in Wuhan metropolitan area are performed. The study reveals that the global spatial autocorrelation of URRN is well and there has some spatial agglomeration which presents the fluctuation variation with the lapse of time. On local level, the spatial gathering pattern maintains a good stable mechanism as a whole, basically presenting the high value directive property of central area and the low value directive property characteristics of peripheral area. Wuhan city has become the gathering center with high value of topological variables. Overall, by using the spatial autocorrelation models, this article explored the topological space correlation of road network in Wuhan metropolitan area based on the past research experience on complex traffic network, and its evolution characteristics were discussed.
