A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow

Detalhes bibliográficos
Autor(a) principal: Jardim, Bruno
Data de Publicação: 2023
Outros Autores: Neto, Miguel de Castro, Barriguinha, André
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/153862
Resumo: Jardim, B., Neto, M. D. C., & Barriguinha, A. (2023). A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow. Computers, Environment and Urban Systems, 104(September), [101993]. https://doi.org/10.1016/j.compenvurbsys.2023.101993---This research was funded by the Project C-TECH—Climate Driven Technologies for Low Carbon Cities, grant number POCI-01-0247-FEDER-045919|LISBOA-01-0247-FEDER-045919, co-financed by the ERDF—European Regional Development Fund through the Operational Program for Competitiveness and Internationalization—COMPETE 2020, the Lisbon Portugal Regional Operational Program—LISBOA 2020 and by the Portuguese Foundation for Science and Technology—FCT under MIT Portugal Program. This work was also supported by Portuguese national funds through the Portuguese Foundation for Science and Technology—FCT under research grant FCT UIDB/04152/2020–Centro de Investigação em Gestão de Informação (MagIC).
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spelling A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flowWalkabilityActive mobilityComposite indicatorsMobile dataSustainable regionsUrban planningGeography, Planning and DevelopmentEcological ModellingEnvironmental Science(all)Urban StudiesSDG 11 - Sustainable Cities and CommunitiesJardim, B., Neto, M. D. C., & Barriguinha, A. (2023). A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow. Computers, Environment and Urban Systems, 104(September), [101993]. https://doi.org/10.1016/j.compenvurbsys.2023.101993---This research was funded by the Project C-TECH—Climate Driven Technologies for Low Carbon Cities, grant number POCI-01-0247-FEDER-045919|LISBOA-01-0247-FEDER-045919, co-financed by the ERDF—European Regional Development Fund through the Operational Program for Competitiveness and Internationalization—COMPETE 2020, the Lisbon Portugal Regional Operational Program—LISBOA 2020 and by the Portuguese Foundation for Science and Technology—FCT under MIT Portugal Program. This work was also supported by Portuguese national funds through the Portuguese Foundation for Science and Technology—FCT under research grant FCT UIDB/04152/2020–Centro de Investigação em Gestão de Informação (MagIC).Walkability indicators are a pivotal method to evaluate the role of the built environment in peoples' decisions regarding active mobility, supporting the application of public measures that contribute to more sustainable and resilient regions. Currently, data used to evaluate associations between walkability indicators and travel behavior is obtained via traditional methods of data collection, like questionnaires, that are costly and hard to scale in large urban environments. Moreover, the spatial resolution of most indicators may not be sufficient to support granular local public interventions. To face these issues, we propose a novel walkability indicator that provides a score of walkability for every one-meter street point, based on street conditions and accessibility to points of interest calculated with a Cumulative-Gaussian impedance function. Resorting to Linear and Geospatial Weighted Regressions, we evaluate the associations between walkability features and pedestrian flow data retrieved from mobile phone communication signals for a week in March 2022. The relationship between walkability features and pedestrian flow is stronger during workdays, in which accessibility to education, food amenities and government services are the most important predictors. On the weekend, the features with more explanatory power are accessibility to crosswalks and leisure amenities. Accessibility to public transport, sidewalk width and slope seem to impact pedestrian decisions independently of the day type, although the impact is stronger on weekends. This study provides policy makers and urban planners with a practical tool to effectively support the evaluation of current street conditions and access areas that are underserved, as well as plan and gauge new local interventions, while objectively understanding their impacts on pedestrian mobility.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNJardim, BrunoNeto, Miguel de CastroBarriguinha, André2023-06-12T22:19:50Z2023-092023-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article15application/pdfhttp://hdl.handle.net/10362/153862eng0198-9715PURE: 63539289https://doi.org/10.1016/j.compenvurbsys.2023.101993info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:36:20Zoai:run.unl.pt:10362/153862Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:55:24.678876Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow
title A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow
spellingShingle A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow
Jardim, Bruno
Walkability
Active mobility
Composite indicators
Mobile data
Sustainable regions
Urban planning
Geography, Planning and Development
Ecological Modelling
Environmental Science(all)
Urban Studies
SDG 11 - Sustainable Cities and Communities
title_short A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow
title_full A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow
title_fullStr A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow
title_full_unstemmed A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow
title_sort A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow
author Jardim, Bruno
author_facet Jardim, Bruno
Neto, Miguel de Castro
Barriguinha, André
author_role author
author2 Neto, Miguel de Castro
Barriguinha, André
author2_role author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Jardim, Bruno
Neto, Miguel de Castro
Barriguinha, André
dc.subject.por.fl_str_mv Walkability
Active mobility
Composite indicators
Mobile data
Sustainable regions
Urban planning
Geography, Planning and Development
Ecological Modelling
Environmental Science(all)
Urban Studies
SDG 11 - Sustainable Cities and Communities
topic Walkability
Active mobility
Composite indicators
Mobile data
Sustainable regions
Urban planning
Geography, Planning and Development
Ecological Modelling
Environmental Science(all)
Urban Studies
SDG 11 - Sustainable Cities and Communities
description Jardim, B., Neto, M. D. C., & Barriguinha, A. (2023). A street-point method to measure the spatiotemporal relationship between walkability and pedestrian flow. Computers, Environment and Urban Systems, 104(September), [101993]. https://doi.org/10.1016/j.compenvurbsys.2023.101993---This research was funded by the Project C-TECH—Climate Driven Technologies for Low Carbon Cities, grant number POCI-01-0247-FEDER-045919|LISBOA-01-0247-FEDER-045919, co-financed by the ERDF—European Regional Development Fund through the Operational Program for Competitiveness and Internationalization—COMPETE 2020, the Lisbon Portugal Regional Operational Program—LISBOA 2020 and by the Portuguese Foundation for Science and Technology—FCT under MIT Portugal Program. This work was also supported by Portuguese national funds through the Portuguese Foundation for Science and Technology—FCT under research grant FCT UIDB/04152/2020–Centro de Investigação em Gestão de Informação (MagIC).
publishDate 2023
dc.date.none.fl_str_mv 2023-06-12T22:19:50Z
2023-09
2023-09-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/153862
url http://hdl.handle.net/10362/153862
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0198-9715
PURE: 63539289
https://doi.org/10.1016/j.compenvurbsys.2023.101993
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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