文章基本信息

标题：Revealing the Correlation between Population Density and the Spatial Distribution of Urban Public Service Facilities with Mobile Phone Data
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作者：Yi Shi ; Junyan Yang ; Peiyu Shen 等
期刊名称：ISPRS International Journal of Geo-Information
电子版ISSN：2220-9964
出版年度：2020
卷号：9
期号：1
页码：38
DOI：10.3390/ijgi9010038
语种：English
出版社：MDPI AG
摘要：Some studies have confirmed the association between urban public services and population density; however, other studies using census data, for example, have arrived at the opposite conclusion. Mobile signaling data provide new technological tools to investigate the subject. Based on the data of 20 million 2G mobile phone users in downtown Shanghai and the land use data of urban public service facilities, this study explores the spatiotemporal correlation between population density and public service facilities’ locations in downtown Shanghai and its variation laws. The correlation between individual population density at day vs. night and urban public service facilities distribution was also examined from a dynamic perspective. The results show a correlation between service facilities’ locations and urban population density at different times of the day. As a result, the average population density observed over a long period of time (day-time periodicity or longer) with census data or remote sensing data does not directly correlation with the distribution of public service facilities despite its correlation with public service facilities distribution. Among them, there is a significant spatial correlation between public service facilities and daytime population density and a significant spatial correlation between non-public service facilities and night-time population density. The spatial and temporal changes in the relationship between urban population density and service facilities is due to changing crowd behavior; however, the density of specific types of behavior is the real factor that affects the layout of urban public service facilities. The results show that mobile signaling data and land use data of service facilities are of great value for studying the spatiotemporal correlations between urban population density and service facilities.