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Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data

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State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
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Collaborative Innovation Center of Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China
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Senseable City Laboratory, SMART Centre, 1 Create Way, Singapore 138602, Singapore
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Department of Geography, University of Tennessee, Knoxville, TN 37996, USA
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Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Road, Shenzhen 518005, China
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Business Support Center, Hubei Mobile, 2 Jinyinhu Road, Wuhan 430040, China
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School of Mathematical Sciences, Peking University, 5 Yiheyuan Road Haidian District, Beijing 100871, China
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Authors to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(10), 177; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100177
Received: 19 July 2016 / Revised: 22 September 2016 / Accepted: 22 September 2016 / Published: 28 September 2016
Investigating human mobility patterns can help researchers and agencies understand the driving forces of human movement, with potential benefits for urban planning and traffic management. Recent advances in location-aware technologies have provided many new data sources (e.g., mobile phone and social media data) for studying human space-time behavioral regularity. Although existing studies have utilized these new datasets to characterize human mobility patterns from various aspects, such as predicting human mobility and monitoring urban dynamics, few studies have focused on human convergence and divergence patterns within a city. This study aims to explore human spatial convergence and divergence and their evolutions over time using large-scale mobile phone location data. Using a dataset from Shenzhen, China, we developed a method to identify spatiotemporal patterns of human convergence and divergence. Eight distinct patterns were extracted, and the spatial distributions of these patterns are discussed in the context of urban functional regions. Thus, this study investigates urban human convergence and divergence patterns and their relationships with the urban functional environment, which is helpful for urban policy development, urban planning and traffic management. View Full-Text
Keywords: human convergence and divergence; mobile phone data; spatiotemporal patterns; human mobility patterns human convergence and divergence; mobile phone data; spatiotemporal patterns; human mobility patterns
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MDPI and ACS Style

Yang, X.; Fang, Z.; Xu, Y.; Shaw, S.-L.; Zhao, Z.; Yin, L.; Zhang, T.; Lin, Y. Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data. ISPRS Int. J. Geo-Inf. 2016, 5, 177. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100177

AMA Style

Yang X, Fang Z, Xu Y, Shaw S-L, Zhao Z, Yin L, Zhang T, Lin Y. Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data. ISPRS International Journal of Geo-Information. 2016; 5(10):177. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100177

Chicago/Turabian Style

Yang, Xiping, Zhixiang Fang, Yang Xu, Shih-Lung Shaw, Zhiyuan Zhao, Ling Yin, Tao Zhang, and Yunong Lin. 2016. "Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data" ISPRS International Journal of Geo-Information 5, no. 10: 177. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100177

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