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Urban greening and public safety across day and night: A street-view and AI-based assessment of spatial safety context

Urban greening and public safety across day and night: A street-view and AI-based assessment of spatial safety context

Properties8
authorsXia, T., Wu, X., Zhao, W., He, J., Mao, Y., Li, P., Zhao, B., Zhang, J.
publication-typeJournal article
journalSustainable Cities and Society
doi10.1016/j.scs.2026.108009
linkhttps://doi.org/10.1016/j.scs.2026.108009
research-lineAI, urban analytics, and the built environment
tagspublication, visual-large-language-model, street-green-space, public-safety, urban-analytics
aliasesworking-papers/street-green-space-crime-vllm

Summary

This article examines how urban greening relates to public safety across daytime and nighttime contexts. It uses street-view imagery and AI-based assessment to study spatial safety context and differences between times of day.

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