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Revealing the relationship between human mobility and urban deprivation using geo-big data: a case study from London in the post-pandemic era Creators

Chen, Tongxin

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Abstract

Investigating the association between human mobility and urban deprivation helps to understand the disparate routines of urban residents with different socioeconomic vulnerabilities. Though lots of research have revealed the difference in the population's mobility behaviours impacted by social distancing measures during the COVID-19 pandemic since 2020, limited analytics focuses on the inequality in mobility recovery patterns of urban residents in the post-pandemic era. Using a large-scale geo-big data set (mobile phone GPS trajectories), we calculated the associations between the measured mobility recovery rate and urban deprivation indices (seven categories) in 4835 London communities (LSOAs) during the first four months of 2022. We show that mobility recovery is associated with urban deprivation (particularly the 'Barriers to Housing and Services' deprivation index) over the observed post-pandemic period. The results further demonstrate that the residents from higher deprived/vulnerable communities are likely to obtain lower mobility recovery rates in London.

Citation

Chen, T. (2023, April). Revealing the relationship between human mobility and urban deprivation using geo-big data: a case study from London in the post-pandemic era Creators. Presented at 31st Geographical Information Science Research UK (GISRUK), Glasgow, UK

Presentation Conference Type Conference Paper (published)
Conference Name 31st Geographical Information Science Research UK (GISRUK)
Start Date Apr 19, 2023
End Date Apr 21, 2023
Acceptance Date Feb 1, 2023
Online Publication Date Apr 12, 2023
Publication Date Apr 12, 2023
Deposit Date Nov 6, 2024
Publicly Available Date Mar 14, 2025
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.5281/zenodo.7822769
Keywords Human mobility; urban deprivation; vulnerability; geo big data; post-pandemic
Public URL https://hull-repository.worktribe.com/output/4909995

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