Research On Wuhan Urban Agglomerations Urban Network Based On Traffic Flow

Since the 1990s,Internet information and communication technology has further developed,allowing various flow elements to flow freely around the world.Logistics,capital flow,and people flow have rebuilt the global urban system under different scales through transportation and communication infrastructure.With the multi-center open and flowing urban network structure model began to appear,and the related research of urban network is becoming more and more abundant.Based on relevant theories such as urban network and regional spatial structure,this paper uses Python big data crawling technology to sort out the traffic connections between the three different modes of transportation of cars,Pule,and high-speed rail in Wuhan.Establish a traffic connection network at the two scales of prefecture-level cities and districts and counties,use geographic spatial analysis and social network analysis methods,and use ArcGIS to visualize the connection volume to explore the two cities and districts of Wuhan.Based on the characteristics and structure of urban network space in different scales,the future development path of Wuhan city circle is proposed based on the results.Draw conclusions from the above research:The urban association pattern of the Wuhan city circle based on the amount of traffic association:the spatial differentiation of the amount of traffic in different scales of the city is obvious.The spatial distribution of the amount of traffic connections of the three transportation modes at the prefecture-level city scale is more in the east and less in the west,while,At the county level,the traffic connection between cars and Pule is more in the east and less in the west,while the high-speed rail is more in the west and less in the east.There are no train stations in the northern and southern parts of the Wuhan city circle and the counties in the northeast;in terms of spatial agglomeration characteristics,based on the positive Moran’s I index based on the total number of cars and ordinary trains,there is a positive spatial correlation between the strength of connections between cities,and areas with similar spatial connection strength characteristics show a clustering state.Based on the negative Moran’s I index of the total number of high-speed rail trains,the strength of connections between cities is spatially distributed;in terms of urban spatial organization,Wuhan is an important contact object for each district,county and city node in the Wuhan urban circle,forming a strong radiation Attraction,the eastern districts and counties have strong cohesion.The urban network structure of the Wuhan city circle:In terms of network connection characteristics,the connection strength of the automobile passenger transportation network shows the characteristics of being stronger as the distance is closer.The connection between Pule and the high-speed rail passenger network is no longer limited to the close distance between districts and counties.The influence of distance gradually weakened.In terms of network centrality analysis,Wuhan City and Xiaogan City have high degree centrality,close centrality,and intermediate centrality,which play an important role in the network.However,Qianjiang City,because of its location on the western fringe,has weak links with other cities in the network.At the district/county level,the traffic flow of passenger cars near the outlying city and other districts and counties near Wuhan’s central urban area has been separated by Wuchang,causing the effect of "black under the lights".The development path of urban cyberspace optimization in Wuhan city circle:Based on the existing resources,socio-economic and technological,it guides the evolution of urban population spatial structure measure from industrial measures,institutional measures,etc.,infrastructure improvement measures,and path optimization measures,etc.To achieve the best space configuration.