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The exploration of human activity zones using geo-tagged big data during the COVID-19 first lockdown in London, UK

Chen, Tongxin; Tao, Cheng; Di, Zhu; (2021) The exploration of human activity zones using geo-tagged big data during the COVID-19 first lockdown in London, UK. In: Proceedings of the 29th Annual GIS Research UK Conference (GISRUK). GIS Research UK (GISRUK): Cardiff, UK. Green open access

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Abstract

Exploring the human activity zones (HAZs) gives significant insights into understanding the complex urban environment and reinforcing urban management and planning. Though previous studies have reported the significant human activity shifting at the city-level in global metropolises due to COVID-19 containment policies, the dynamic of human activity across urban areas at space and time during such an ever-changing socioeconomic period has not been examined and discussed hitherto. In this study, we proposed an analysis framework to explore the human activities zones using geo-tagged big data in London, UK. We first utilised the activity- detection method to extract visits/stops at space and time as the human activity metric from the mobile phone GPS trajectory data. Then, we characterised HAZs based on the homogeneity of hourly human activity footfalls on the middle layer super output areas (MSOAs). The results show the HAZs not only exhibit declines in human activity but are strongly associated with urban land-use and population variables during the COVID-19 pandemic.

Type: Proceedings paper
Title: The exploration of human activity zones using geo-tagged big data during the COVID-19 first lockdown in London, UK
Event: 29th Annual GIS Research UK Conference (GISRUK)
Open access status: An open access version is available from UCL Discovery
DOI: 10.5281/zenodo.4670050
Publisher version: https://doi.org/10.5281/zenodo.4670050
Language: English
Additional information: This is an Open Access paper published under a Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/).
Keywords: Urban functions, human activity, social sensing, geo-tagged big data, COVID-19
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10149746
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