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City form and well-being: what makes London neighborhoods good places to live?

Venerandi, A; Quattrone, G; Capra, L; (2016) City form and well-being: what makes London neighborhoods good places to live? In: Ali, M and Newsam, S and Ravada, S and Renz, M and Trajcevski, G, (eds.) GIS '16: Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Association for Computing Machinery (ACM): New York, NY, USA. Green open access

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Abstract

What is the relationship between urban form and citizens’ well-being? In this paper, we propose a quantitative approach to help answer this question, inspired by theories developed within the fields of architecture and population health. The method extracts a rich set of metrics of urban form and well-being from openly accessible datasets. Using linear regression analysis, we identify a model which can explain 30% of the variance of well-being when applied to Greater London, UK. Outcomes of this research can inform the discussion on how to design cities which foster the wellbeing of their residents.

Type: Proceedings paper
Title: City form and well-being: what makes London neighborhoods good places to live?
Event: 24th ACM International Conference on Advances in Geographic Information Systems (GIS '16)
Location: San Francisco, CA
ISBN-13: 9781450345897
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/2996913.2997011
Publisher version: https://doi.org/10.1145/2996913.2997011
Language: English
Additional information: Copyright © 2016 ACM.
Keywords: Urban Form, Well-being, Quantitative Analysis, Open Data
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1514856
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