Abstract
Leisure is an important part of the daily activities of urban residents. A relatively dense flow of people will be generated between residential areas and supermarkets, as well as between residential areas and highly popular park facilities. These flows of people can reflect the characteristics of residents’ leisure activities and the spatial characteristics of urban residence–leisure functions, as opposed to static leisure facilities and places; it is a new perspective for the study of urban spatial structure. Network studies on the relationship between residential and leisure functions within cities are rarely seen. In this study, from the flow space perspective, based on the questionnaire data, points of interest data, and mobile phone signaling data, the actual leisure travel flows of residents with different travel purposes can be identified, including residence–shopping leisure flows and residence–park leisure flows, and the corresponding urban networks can be constructed from them. With the help of complex network analysis, this paper discusses different types of residence–leisure network structures and their influencing factors in terms of network characteristics, node strength, and QAP analysis. It deepens the understanding of the urban spatial structure and provides the theoretical basis and technical support for urban structure analysis, urban layout optimization, and urban planning and management. The results show that: ① Both residence–shopping leisure and residence–park leisure networks have the small-world characteristics and scale-free properties of complex networks. ② The characteristics of the nodes of the residence–leisure network for different leisure travel purposes indicate that residents go more to Taiyuan Street and the New North Station business circle for shopping activities, and the parks that attract residents to go out for walks are concentrated in the central part of the city. ③ Different types of network structures have a strong correlation with the number of residential functions and leisure facilities but have a weak correlation with the difference in the number of inhabitants and leisure travel distance. This study enriches the research cases of the urban residence–leisure network structure to a certain extent. Shenyang City has the same background of rapid expansion as other large cities in China, and this study has an important role in planning and inspiration for solving urban diseases and achieving the orderly and rational development of large cities.
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