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dc.contributor.authorCruz Sandoval, Marco Antonio
dc.contributor.authorRoca Bosch, Elisabet
dc.contributor.authorOrtego Martínez, María Isabel
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Sostenibilitat
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.coverage.spatialeast=-103.3496092; north=20.65969879999999; name=Guadalajara, Jal., Mèxic
dc.date.accessioned2020-06-02T12:29:35Z
dc.date.available2020-06-02T12:29:35Z
dc.date.issued2020-05-24
dc.identifier.citationCruz, M.; Roca, E.; Ortego, M.I. Compositional data analysis approach in the measurement of social-spatial segregation: towards a sustainable and inclusive city. "Sustainability", 24 Maig 2020, p. 12104293-1-12104293-19.
dc.identifier.issn2071-1050
dc.identifier.urihttp://hdl.handle.net/2117/189733
dc.description.abstractThe location and context in which people live influences and conditions their opportunities in life. This becomes relevant in a world subject to rapid urban and demographic growth, in which different economic, social, and political forces generate and accentuate disparities in cities. The foregoing generates an unequal distribution of the different social groups in the territory known as socio-spatial segregation. The study of this phenomenon incorporates a large number of variables belonging to different dimensions. Nonetheless, few studies have addressed socio-spatial segregation with a multivariate analysis approach. In addition, the existing studies may have obtained misleading outcomes by not acknowledging the inherent compositional nature of their variables. The objective of the present study is twofold: (i) To assess whether the phenomenon of socio-spatial segregation in Guadalajara, Mexico exists; and (ii) to introduce and stress the use of compositional techniques for the study of socio-spatial segregation. The study applied principal component analysis and cluster analysis considering the compositional nature of census variables, particularly from economic and educative indicators. In addition, the study used geographical information tools to depict and interpret the results. The results are intended to serve in the fulfillment of the Sustainable Development Goals towards inclusive and sustainable cities.
dc.language.isoeng
dc.rightsAttribution 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Desenvolupament humà i sostenible::Desenvolupament sostenible
dc.subject.lcshMarginality, Social--Mèxico
dc.subject.lcshSocial integration--Mexico
dc.subject.otherSocio-spatial segregation
dc.subject.otherInequality
dc.subject.otherSocial exclusion
dc.subject.otherInclusive city
dc.subject.otherCompositional data analysis
dc.subject.otherLog-ratio
dc.subject.otherGuadalajara (México)
dc.titleCompositional data analysis approach in the measurement of social-spatial segregation: towards a sustainable and inclusive city
dc.typeArticle
dc.subject.lemacMarginació social -- Mèxic
dc.subject.lemacIntegració social-- Mèxic
dc.contributor.groupUniversitat Politècnica de Catalunya. LESEC - Laboratori d'Estudis Socials de l'Enginyeria Civil
dc.contributor.groupUniversitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis
dc.identifier.doi10.3390/su12104293
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.mdpi.com/2071-1050/12/10/4293
dc.rights.accessOpen Access
local.identifier.drac28508207
dc.description.versionPostprint (published version)
local.citation.authorCruz, M.; Roca, E.; Ortego, M.I.
local.citation.publicationNameSustainability
local.citation.startingPage12104293-1
local.citation.endingPage12104293-19


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