An exploratory multivariate statistical analysis to assess urban diversity

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• dc.contributor.author Salazar Llano, Lorena
• dc.contributor.author Rosas Casals, Martí
• dc.contributor.author Ortego, Maria Isabel
• dc.date.accessioned 2020-07-24T06:20:50Z
• dc.date.available 2020-07-24T06:20:50Z
• dc.date.issued 2019
• dc.description.abstract Understanding diversity in complex urban systems is fundamental in facing current and future sustainability challenges. In this article, we apply an exploratory multivariate statistical analysis (i.e., Principal Component Analysis (PCA) and Multiple Factor Analysis (MFA)) to an urban system’s abstraction of the city’s functioning. Specifically, we relate the environmental, economical, and social characters of the city in a multivariate system of indicators by collecting measurements of those variables at the district scale. Statistical methods are applied to reduce the dimensionality of the multivariate dataset, such that, hidden relationships between the districts of the city are exposed. The methodology has been mainly designed to display diversity, being understood as differentiated attributes of the districts in their dimensionally-reduced description, and to measure it with Euclidean distances. Differentiated characters and distinctive functions of districts are identifiable in the exploratory analysis of a case study of Barcelona (Spain). The distances allow for the identification of clustered districts, as well as those that are separated, exemplifying dissimilarity. Moreover, the temporal dependency of the dataset reveals information about the district’s differentiation or homogenization trends between 2003 and 2015.
• dc.format.mimetype application/pdf
• dc.identifier.citation Salazar-Llano L, Rosas-Casals M, Ortego MI. An exploratory multivariate statistical analysis to assess urban diversity. Sustainability. 2019; 11(14):3812. DOI: 10.3390/su11143812
• dc.identifier.doi http://dx.doi.org/10.3390/su11143812
• dc.identifier.issn 2071-1050
• dc.identifier.uri http://hdl.handle.net/10230/45181
• dc.language.iso eng
• dc.publisher MDPI
• dc.relation.ispartof Sustainability. 2019; 11(14):3812
• dc.rights © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Urban diversity
• dc.subject.keyword Urban resilience
• dc.subject.keyword Urban sustainability
• dc.subject.keyword Sustainability indicators
• dc.subject.keyword Principal Component Analysis (PCA)
• dc.subject.keyword Multiple Factor Analysis (MFA)
• dc.subject.keyword Biplot
• dc.subject.keyword Barcelona
• dc.title An exploratory multivariate statistical analysis to assess urban diversity
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion