Cited by 298Human Mobility and Location-Based AnalysisUrban Design and Spatial AnalysisGeographic Information Systems Studies

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Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns

Tu, Wei, Cao, Jinzhou, Yue, Yang, Shaw, Shih-Lung, Zhou, Meng, Wang, Zhensheng, Chang, Xiaomeng, Xu, Yang, Li, Qingquan·2017·International Journal of Geographical Information Science

DOI 10.1080/13658816.2017.1356464

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Abstract

Understanding urban functions and their relationships with human activities has great implications for smart and sustainable urban development. In this study, we present a novel approach to uncovering urban functions by aggregating human activities inferred from mobile phone positioning and social media data. First, the homes and workplaces (of travelers) are estimated from mobile phone positioning data to annotate the activities conducted at these locations. The remaining activities (such as shopping, schooling, transportation, recreation and entertainment) are labeled using a hidden Markov model with social knowledge learned from social media check-in data over a lengthy period. By aggregating identified human activities, hourly urban functions are inferred, and the diurnal dynamics of those functions are revealed. An empirical analysis was conducted for the case of Shenzhen, China. The results indicate that the proposed approach can capture citywide dynamics of both human activities and urban functions. It also suggests that although many urban areas have been officially labeled with a single land-use type, they may provide different functions over time depending on the types and range of human activities. The study demonstrates that combining different data on human activities could yield an improved understanding of urban functions, which would benefit short-term urban decision-making and long-term urban policy making.

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Authors: Tu, W., Cao, J., Yue, Y., Shaw, S.-L., Zhou, M., Wang, Z., Chang, X., Xu, Y., & Li, Q.
Affiliations: Shenzhen University (CN)
Wuhan University (CN)
University of Tennessee at Knoxville (US)
Hong Kong Baptist University (HK)
Singapore-MIT Alliance for Research and Technology (SG)
Corresponding author: Yue, Yang
ORCID: Tu, Wei
Cao, Jinzhou
Yue, Yang
Shaw, Shih-Lung
Zhou, Meng
Xu, Yang
Li, Qingquan
Venue: International Journal of Geographical Information Science
Publisher: Informa UK Limited
Published: 2017-07-31
Volume: 31
Issue: 12
Pages: 2331-2358
ISSN: 0269-3798 (ISSN-L)
1365-8816
1362-3087
DOI: 10.1080/13658816.2017.1356464
OpenAlex: W2741078791
Cited by: 298
References: 61
Citations by year: 2026: 25 · 2025: 33 · 2024: 33 · 2023: 29 · 2022: 44 · 2021: 43 · 2020: 42 · 2019: 29 · 2018: 18 · 2017: 2
FWCI: 36.51
Type: journal article
Language: en
Open access: closed
Locations: International Journal of Geographical Information Systems (publishedVersion)
Funders: National Natural Science Foundation of China (41401444, 41671387, 91546106)
the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources (KF-2016-02-009, KF-2016-02-010)
Shenzhen Scientific Research and Development Funding Program (CXZZ20150504141623042)
Nature Science Foundation of Shenzhen University (2016065)
Topics: Social Sciences › Transportation › Human Mobility and Location-Based Analysis
Social Sciences › Urban Studies › Urban Design and Spatial Analysis
Social Sciences › Geography, Planning and Development › Geographic Information Systems Studies
Keywords: urban functions, diurnal patterns, human activities, social media check-ins, hidden Markov models, land use, activity inference, Shenzhen, urban decision-making

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Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns

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