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Exploring non-linear built environment effects on urban vibrancy under COVID-19: The case of Hong Kong
The coronavirus disease (COVID-19) pandemic has enormously changed the way people perceive and use urban spaces, exacerbating some pre-existing issues including urban vibrancy decline. This study aims to explore built environment effects on urban vibrancy under COVID-19, which will help recalibrate...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099149/ https://www.ncbi.nlm.nih.gov/pubmed/37077238 http://dx.doi.org/10.1016/j.apgeog.2023.102960 |
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author | Xiao, Longzhu Liu, Jixiang |
author_facet | Xiao, Longzhu Liu, Jixiang |
author_sort | Xiao, Longzhu |
collection | PubMed |
description | The coronavirus disease (COVID-19) pandemic has enormously changed the way people perceive and use urban spaces, exacerbating some pre-existing issues including urban vibrancy decline. This study aims to explore built environment effects on urban vibrancy under COVID-19, which will help recalibrate planning models and design principles. Based on multi-source geo-tagged big data of Hong Kong, this study reveals variations in urban vibrancy and employs machine learning modeling and interpretation methods to examine built environment effects on urban vibrancy before, during, and after the outbreak of COVID-19, with review volume of restaurants & food retailers as the indicator for urban vibrancy and built environment depicted from five dimensions (i.e., building form, street accessibility, public transport accessibility, functional density, and functional mixture). We found that (1) urban vibrancy concussively decreased during the outbreak and slowly recovered afterwards; (2) built environment's capability to stimulate urban vibrancy was weakened during the outbreak and restored afterwards; (3) the relationships between built environment and urban vibrancy were non-linear and moderated by the pandemic. This research enriches our understandings of the role of the pandemic in influencing urban vibrancy and its correlation with built environment, enlightening decision makers with nuanced criteria for pandemic-adaptive urban planning and design. |
format | Online Article Text |
id | pubmed-10099149 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100991492023-04-13 Exploring non-linear built environment effects on urban vibrancy under COVID-19: The case of Hong Kong Xiao, Longzhu Liu, Jixiang Appl Geogr Article The coronavirus disease (COVID-19) pandemic has enormously changed the way people perceive and use urban spaces, exacerbating some pre-existing issues including urban vibrancy decline. This study aims to explore built environment effects on urban vibrancy under COVID-19, which will help recalibrate planning models and design principles. Based on multi-source geo-tagged big data of Hong Kong, this study reveals variations in urban vibrancy and employs machine learning modeling and interpretation methods to examine built environment effects on urban vibrancy before, during, and after the outbreak of COVID-19, with review volume of restaurants & food retailers as the indicator for urban vibrancy and built environment depicted from five dimensions (i.e., building form, street accessibility, public transport accessibility, functional density, and functional mixture). We found that (1) urban vibrancy concussively decreased during the outbreak and slowly recovered afterwards; (2) built environment's capability to stimulate urban vibrancy was weakened during the outbreak and restored afterwards; (3) the relationships between built environment and urban vibrancy were non-linear and moderated by the pandemic. This research enriches our understandings of the role of the pandemic in influencing urban vibrancy and its correlation with built environment, enlightening decision makers with nuanced criteria for pandemic-adaptive urban planning and design. Elsevier Ltd. 2023-06 2023-04-13 /pmc/articles/PMC10099149/ /pubmed/37077238 http://dx.doi.org/10.1016/j.apgeog.2023.102960 Text en © 2023 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Xiao, Longzhu Liu, Jixiang Exploring non-linear built environment effects on urban vibrancy under COVID-19: The case of Hong Kong |
title | Exploring non-linear built environment effects on urban vibrancy under COVID-19: The case of Hong Kong |
title_full | Exploring non-linear built environment effects on urban vibrancy under COVID-19: The case of Hong Kong |
title_fullStr | Exploring non-linear built environment effects on urban vibrancy under COVID-19: The case of Hong Kong |
title_full_unstemmed | Exploring non-linear built environment effects on urban vibrancy under COVID-19: The case of Hong Kong |
title_short | Exploring non-linear built environment effects on urban vibrancy under COVID-19: The case of Hong Kong |
title_sort | exploring non-linear built environment effects on urban vibrancy under covid-19: the case of hong kong |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099149/ https://www.ncbi.nlm.nih.gov/pubmed/37077238 http://dx.doi.org/10.1016/j.apgeog.2023.102960 |
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