Land Use Indexed Mobility Changes' Impact on Urban Crimes in Metropolitan Cities
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Li, Yijing
Sun, Ivan
Zhang, Yan
Wu, Yuying
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Technische Universiteit Delft/Delft University of Technology
Abstract
Social distancing and lockdown measures have been widely deployed in urban areas
worldwide to restrict citizens’ movement to help contain the COVID-19 pandemic. This resulted in
dramatic changes in people’s daily mobility, as well as the criminality and delinquency in cities.
Drawing on crime data in London, Sydney, and New York in 2020, this study attempts the first oneyear “look back” on the impact of massive lockdowns on crime trends in the assistance of two classic
criminological theories, routine activity, and general strain, as well as cutting-edge machine learning
techniques on relating the community-level geodemographics, socio-economic profiles, and mobility changes to changes in crime. The research findings suggest a general crime reduction upon mobility changes during lockdowns among the metropolitan cities, but some city-featured prominent
crime types had an eye-catching increase during the period. Holistic mobility change was found to
be the most crime-influential factor rather than any fine-scaled residents’ geodemographic characteristics, echoing commonly offsite criminal behaviors rather than committing crimes locally; the
data-driven evidence could be further utilised for city-wide crime prediction and prevention strategies towards post-pandemic recovery.
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TU Delft Open
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Open Access
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Creative Commons Attribution 4.0 International License
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