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Culture, Heritage & Public Space
Journal articleOpen access

Spatial Inequalities in Public Space Quality: A GIS-Based Multi-Attribute Composite Index for Urban Planning in an Intermediate Latin American City

Published 7 Aug 2026 · Added to radar 5 Nov 2026

Source abstract

Public spaces are essential for urban well-being, social interaction, environmental quality, and territorial equity; however, their presence does not necessarily ensure adequate quality, accessibility, or multifunctionality. Although previous research has emphasized the importance of green and public spaces, fewer studies have integrated multidimensional quality assessment, GIS-based spatial analysis, and multicriteria prioritization in intermediate Latin American cities. This study aimed to evaluate spatial inequalities in the quality of urban public spaces in Loja, Ecuador, through a GIS-based multi-attribute composite index. A total of 183 public spaces were assessed using structured field observation of observable conditions and organized into six dimensions: functional, environmental, cultural, recreational, safety, and economic. The data were cleaned, validated, integrated with spatial layers, and analyzed through descriptive, inferential, multivariate, spatial autocorrelation, and multicriteria procedures. The results showed that public space quality was mainly concentrated at low and medium levels, with functional and safety dimensions playing a stronger role in the global index, while cultural, recreational, and economic components showed weaker performance. Spatial analysis revealed significant territorial differences, local clusters, and spatial outliers. The proposed framework provides a replicable tool to diagnose observable public space quality, identify priority intervention areas, and support evidence-based urban planning in other intermediate cities.

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Structured record

Study objective (from source abstract)
This study aimed to evaluate spatial inequalities in the quality of urban public spaces in Loja, Ecuador, through a GIS-based multi-attribute composite index.
Methods
spatial analysis, GIS analysis

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