Spatiotemporal distribution characteristics and mechanism analysis of urban population density: A case of Xi'an, Shaanxi, China

《Spatiotemporal distribution characteristics and mechanism analysis of urban population density: A case of Xi'an, Shaanxi, China》

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关键字: Spatiotemporal distribution;Urban population density;Mechanism analysis;Baidu heat map data;POI

作者单位: Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China;Xi'an Northwest University Research Institute of Urban-Rural Planning and Environment Engineering, Xi'an 710127, China;Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China;Xi'an Northwest University Research Institute of Urban-Rural Planning and Environment Engineering, Xi'an 710127, China

摘要: The complexity of cities and their internal structure make it more and more important to study the distribution of urban population density, and big data provide some new technical means for this theme. Based on the Baidu heat map data and urban POI data in Xi'an, China, the spatiotemporal distribution characteristics and mechanism of urban population density were explored with the population density index (PDI), spatial correlation index (SCI) and ordinary least squares (OLS) models. The results suggest that the change of population density in different regions is different, and the change on working days and off days is also different; no matter on working days or off days, the urban population density distribution in different time slots shows the characteristics of agglomeration; land use has great influence on distribution of urban population density in different time slots; the purpose of residents' activities, the difference of spatial functions, and the interaction between them cause the spatiotemporal evolution of urban population density. The conclusion shows that the Baidu heat map data and POI data are of great value for studying the spatiotemporal distribution characteristics and mechanism of urban population density.