Modelling urban vibrancy with mobile phone and OpenStreetMap data.

The concept of urban vibrancy has become increasingly important in the study of cities. A vibrant urban environment is an area of a city with high levels of human activity and interactions. Traditionally, studying our cities and what makes them vibrant has been very difficult, due to challenges in d...

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Autores principales:	Federico Botta, Mario Gutiérrez-Roig
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e769b6d2291d4dcdb67bd627607aafb9
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id	oai:doaj.org-article:e769b6d2291d4dcdb67bd627607aafb9
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spelling	oai:doaj.org-article:e769b6d2291d4dcdb67bd627607aafb92021-12-02T20:05:23ZModelling urban vibrancy with mobile phone and OpenStreetMap data.1932-620310.1371/journal.pone.0252015https://doaj.org/article/e769b6d2291d4dcdb67bd627607aafb92021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0252015https://doaj.org/toc/1932-6203The concept of urban vibrancy has become increasingly important in the study of cities. A vibrant urban environment is an area of a city with high levels of human activity and interactions. Traditionally, studying our cities and what makes them vibrant has been very difficult, due to challenges in data collection on urban environments and people's location and interactions. Here, we rely on novel sources of data to investigate how different features of our cities may relate to urban vibrancy. In particular, we explore whether there are any differences in which urban features make an environment vibrant for different age groups. We perform this quantitative analysis by extracting urban features from OpenStreetMap and the Italian census, and using them in spatial models to describe urban vibrancy. Our analysis shows a strong relationship between urban features and urban vibrancy, and particularly highlights the importance of third places, which are urban places offering opportunities for social interactions. Our findings provide evidence that a combination of mobile phone data with crowdsourced urban features can be used to better understand urban vibrancy.Federico BottaMario Gutiérrez-RoigPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 6, p e0252015 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Federico Botta Mario Gutiérrez-Roig Modelling urban vibrancy with mobile phone and OpenStreetMap data.
description	The concept of urban vibrancy has become increasingly important in the study of cities. A vibrant urban environment is an area of a city with high levels of human activity and interactions. Traditionally, studying our cities and what makes them vibrant has been very difficult, due to challenges in data collection on urban environments and people's location and interactions. Here, we rely on novel sources of data to investigate how different features of our cities may relate to urban vibrancy. In particular, we explore whether there are any differences in which urban features make an environment vibrant for different age groups. We perform this quantitative analysis by extracting urban features from OpenStreetMap and the Italian census, and using them in spatial models to describe urban vibrancy. Our analysis shows a strong relationship between urban features and urban vibrancy, and particularly highlights the importance of third places, which are urban places offering opportunities for social interactions. Our findings provide evidence that a combination of mobile phone data with crowdsourced urban features can be used to better understand urban vibrancy.
format	article
author	Federico Botta Mario Gutiérrez-Roig
author_facet	Federico Botta Mario Gutiérrez-Roig
author_sort	Federico Botta
title	Modelling urban vibrancy with mobile phone and OpenStreetMap data.
title_short	Modelling urban vibrancy with mobile phone and OpenStreetMap data.
title_full	Modelling urban vibrancy with mobile phone and OpenStreetMap data.
title_fullStr	Modelling urban vibrancy with mobile phone and OpenStreetMap data.
title_full_unstemmed	Modelling urban vibrancy with mobile phone and OpenStreetMap data.
title_sort	modelling urban vibrancy with mobile phone and openstreetmap data.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/e769b6d2291d4dcdb67bd627607aafb9
work_keys_str_mv	AT federicobotta modellingurbanvibrancywithmobilephoneandopenstreetmapdata AT mariogutierrezroig modellingurbanvibrancywithmobilephoneandopenstreetmapdata
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Modelling urban vibrancy with mobile phone and OpenStreetMap data.

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