Cities are typical dynamic complex systems that connect people and facilitate interactions. Revealing universal collective patterns behind spatio-temporal interactions between residents is crucial for various urban studies, of which we are still lacking a comprehensive understanding. Massive cellphone data enable us to construct interaction networks based on spatio-temporal co-occurrence of individuals. The rank-size distributions of hourly dynamic population of locations are stable, although people are almost constantly moving in cities and hotspots that attract people are changing over time in a day. A larger city is of a stronger heterogeneity as indicated by a larger scaling exponent. After aggregating spatio-temporal interaction networks over consecutive time windows, we reveal a switching behavior of cities between two states. During the "active" state, the whole city is concentrated in fewer larger communities; while in the "sleeping" state, people are scattered in more smaller communities. Above discoveries are universal over diversified cities across continents. In addition, a city sleeps less, when its population grows larger. And spatio-temporal interaction segregation can be well approximated by residential segregation in smaller cities, but not in larger ones. We propose a temporal-population-weighted-opportunity model by integrating time-dependent departure probability to make dynamic predictions on human mobility, which can reasonably well explain observed patterns of spatio-temporal interactions in cities.
Bidirectional yet asymmetric causality between urban systems and traffic dynamics in 30 cities worldwide
ETH Zurich（苏黎世联邦理工学院）；University College London（伦敦大学学院）；Singapore-ETH Centre, ETH Zurich（新加坡-苏黎世联邦理工学院中心，苏黎世联邦理工学院）；Department of Geography, University of Wisconsin-Madison（威斯康星大学麦迪逊分校地理系）
Classifying Urban Regions by Aggregated Pollutant Weather Correlation Strength: A Spatiotemporal Study
Maulana Abul Kalam Azad University of Technology, West Bengal（西孟加拉马乌拉纳·阿卜杜勒·卡兰·阿扎德理工大学）；S. N. Bose National Centre for Basic Sciences（S.N.玻色基础科学国家中心）；Indian Statistical Institute（印度统计研究所）
