The geography of human activity and land use: A big data approach

Wei Liu; Wenjie Wu; Piyushimita Thakuriah; Jianghao Wang

doi:10.1016/j.cities.2019.102523

The geography of human activity and land use: A big data approach

Wei Liu, Wenjie Wu, Piyushimita Thakuriah, Jianghao Wang

Research output: Journal article publication › Journal article › Academic research › peer-review

38 Citations (Scopus)

Abstract

The application of location-based social media big data in urban contexts offers new and alternative strategies for understanding city liveliness in developing countries where traditional census data are poor. This paper demonstrates how the spatial-temporal distribution of China's Tencent social media usage intensities can be effectively used as a proxy for modelling the geographic patterns of human activity at fine scales. Our results suggest that the spatially-temporally contextualized nature of human activity is dependent upon land use mixing characteristics. With billions of social media data being collected in the virtual world, findings of this study suggest that land use policies to delineating the density, orderly or disorderly geographic patterns of human activity are important for city liveliness.

Original language	English
Article number	102523
Journal	Cities
Volume	97
DOIs	https://doi.org/10.1016/j.cities.2019.102523
Publication status	Published - Feb 2020
Externally published	Yes

Keywords

Big data
Human activity
Land use

ASJC Scopus subject areas

Development
Sociology and Political Science
Urban Studies
Tourism, Leisure and Hospitality Management

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

More information

10.1016/j.cities.2019.102523

Cite this

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title = "The geography of human activity and land use: A big data approach",

abstract = "The application of location-based social media big data in urban contexts offers new and alternative strategies for understanding city liveliness in developing countries where traditional census data are poor. This paper demonstrates how the spatial-temporal distribution of China's Tencent social media usage intensities can be effectively used as a proxy for modelling the geographic patterns of human activity at fine scales. Our results suggest that the spatially-temporally contextualized nature of human activity is dependent upon land use mixing characteristics. With billions of social media data being collected in the virtual world, findings of this study suggest that land use policies to delineating the density, orderly or disorderly geographic patterns of human activity are important for city liveliness.",

keywords = "Big data, Human activity, Land use",

author = "Wei Liu and Wenjie Wu and Piyushimita Thakuriah and Jianghao Wang",

note = "Funding Information: The authors thank the editor and the reviewers for helpful comments. We thank Michael Batty and colleagues from the Urban Big Data Center at the University of Glasgow for suggestions. This work is supported by the National Natural Science Foundation of China ( 41971194 ), and the Research Center for the Industrial Development of Guangdong and its Regional Cooperation with Hong Kong, Macau and Taiwan. Appendix A Funding Information: The authors thank the editor and the reviewers for helpful comments. We thank Michael Batty and colleagues from the Urban Big Data Center at the University of Glasgow for suggestions. This work is supported by the National Natural Science Foundation of China (41971194), and the Research Center for the Industrial Development of Guangdong and its Regional Cooperation with Hong Kong, Macau and Taiwan. Publisher Copyright: {\textcopyright} 2019",

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doi = "10.1016/j.cities.2019.102523",

language = "English",

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AU - Liu, Wei

AU - Wu, Wenjie

AU - Thakuriah, Piyushimita

AU - Wang, Jianghao

N1 - Funding Information: The authors thank the editor and the reviewers for helpful comments. We thank Michael Batty and colleagues from the Urban Big Data Center at the University of Glasgow for suggestions. This work is supported by the National Natural Science Foundation of China ( 41971194 ), and the Research Center for the Industrial Development of Guangdong and its Regional Cooperation with Hong Kong, Macau and Taiwan. Appendix A Funding Information: The authors thank the editor and the reviewers for helpful comments. We thank Michael Batty and colleagues from the Urban Big Data Center at the University of Glasgow for suggestions. This work is supported by the National Natural Science Foundation of China (41971194), and the Research Center for the Industrial Development of Guangdong and its Regional Cooperation with Hong Kong, Macau and Taiwan. Publisher Copyright: © 2019

PY - 2020/2

Y1 - 2020/2

N2 - The application of location-based social media big data in urban contexts offers new and alternative strategies for understanding city liveliness in developing countries where traditional census data are poor. This paper demonstrates how the spatial-temporal distribution of China's Tencent social media usage intensities can be effectively used as a proxy for modelling the geographic patterns of human activity at fine scales. Our results suggest that the spatially-temporally contextualized nature of human activity is dependent upon land use mixing characteristics. With billions of social media data being collected in the virtual world, findings of this study suggest that land use policies to delineating the density, orderly or disorderly geographic patterns of human activity are important for city liveliness.

AB - The application of location-based social media big data in urban contexts offers new and alternative strategies for understanding city liveliness in developing countries where traditional census data are poor. This paper demonstrates how the spatial-temporal distribution of China's Tencent social media usage intensities can be effectively used as a proxy for modelling the geographic patterns of human activity at fine scales. Our results suggest that the spatially-temporally contextualized nature of human activity is dependent upon land use mixing characteristics. With billions of social media data being collected in the virtual world, findings of this study suggest that land use policies to delineating the density, orderly or disorderly geographic patterns of human activity are important for city liveliness.

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KW - Land use

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The geography of human activity and land use: A big data approach

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

More information

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