期刊
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
卷 -, 期 -, 页码 -出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/23998083231219048
关键词
Mobile phone data; spatiotemporal data analysis; urban planning; time series decomposition; population density; emerging patterns
Mobile phones can be used to monitor and understand emerging population dynamics in urban centers by sharing location records. This study introduces a scalable methodology for extracting and organizing spatiotemporal statistics from population density data, with the aim of supporting urban planning. The methodology aims to assess the predictability of density patterns, detect emerging trends, and uncover actionable seasonality patterns.
Mobile phones share location records, offering the opportunity to monitor and understand emerging population dynamics in urban centers. With the aim of supporting urban planning, this study introduces a scalable methodology grounded on extracting and organizing spatiotemporal statistics from decomposed population density data. The proposed methodology serves three major purposes: (i) assess the predictability of spatiotemporal citizen density patterns; (ii) detect emerging spatiotemporal trends in population density; and (iii) uncover multi-level seasonality patterns with guarantees of actionability. Additionally, it makes available an open-access tool for deploying the proposed methodology and analyzing mobile phone network data with easy-to-use spatiotemporal visualization and navigation facilities. The results obtained from real-world, large-scale mobile data in Lisbon, Portugal, demonstrate the effectiveness and validity of the proposed methodology in extracting actionable statistics in linear time to guide both tactic and strategic urban planning.
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