Research on urban network characteristics of Shanghai metropolitan area ——based on population migration data of AutoNavi Map

With the advancement of urban development, the relationship between cities has gradually evolved from a hierarchical structure to a network structure. This change accelerates the flow of various elements between cities and benefits to the sharing of social development results. “Shanghai 2035” emphasizes on strengthening collaboration with surrounding cities and develop a metropolitan area with global influence. This study selects 9 cities (Shanghai, Suzhou, Wuxi, Changzhou, Jiaxing, Nantong, Huzhou, Ningbo, Zhoushan) in the Shanghai metropolitan area mentioned in the “Shanghai 2035” as the preliminary research scope. In recent years, due to the development of geographic big data, there have been many researches on geographic big data based on platforms such as Tencent and Baidu. The results prove that this type of big data has a strong verification effect for the analysis of metropolitan areas and urban agglomerations. This study use python to obtain population migration data of AutoNavi Map to promote research on urban network characteristics.This study refers to some mature urban network construction methods, and uses migration index to reflect the degree of connection between cities. Combine social network analysis and other methods to build a city relationship network based on migration index to analyze urban network characteristics of Shanghai metropolitan area. Data processing, analysis and calculation are carried out through the database, and visual expression is carried out through ArcGIS. This study's purpose is to reveal the urban network structure of the Shanghai metropolitan area. To analyze the urban connection strength and the urban centrality of Shanghai metropolitan area. Identify the radiation range of the Shanghai metropolitan area and discuss the development of Shanghai Metropolitan Area in the Yangtze River Delta. Provide some advise on the further development of Shanghai Metropolitan Area.