sustainability Article Spatiotemporal Patterns of Population Mobility and Its Determinants in Chinese Cities Based on Travel Big Data Zhen Yang 1,2 , Weijun Gao 1,2,* , Xueyuan Zhao 1,2, Chibiao Hao 3 and Xudong Xie 3 1 Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao 266033, China;
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[email protected] (X.Z.) 2 Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan 3 College of Architecture and Urban Planning, Qingdao University of Technology, Qingdao 266033, China;
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[email protected] (X.X.) * Correspondence:
[email protected]; Tel.: +81-93-695-3234 Received: 16 April 2020; Accepted: 13 May 2020; Published: 14 May 2020 Abstract: Large-scale population mobility has an important impact on the spatial layout of China’s urban systems. Compared with traditional census data, mobile-phone-based travel big data can describe the mobility patterns of a population in a timely, dynamic, complete, and accurate manner. With the travel big dataset supported by Tencent’s location big data, combined with social network analysis (SNA) and a semiparametric geographically weighted regression (SGWR) model, this paper first analyzed the spatiotemporal patterns and characteristics of mobile-data-based population mobility (MBPM), and then revealed the socioeconomic factors related to population mobility during the Spring Festival of 2019, which is the most important festival in China, equivalent to Thanksgiving Day in United States. During this period, the volume of population mobility exceeded 200 million, which became the largest time node of short-term population mobility in the world.