Document details

Mapping the quality of life experience in Alfama: a case study in Lisbon, Portugal.

Author(s): Cruz, Pearl May delos Santos dela

Date: 2011

Persistent ID: http://hdl.handle.net/10362/5621

Origin: Repositório Institucional da UNL

Subject(s): Correlation; Geographical information systems; Ordinary kriging; Quality of life; Spatial prediction; Weighted sum


Description

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

This research maps the urban quality of life (QoL) in Alfama, Lisbon (Portugal) through objective and subjective measures. A survey of 69 respondents and locations of social services were gathered signifying the subjective and objective QoL respectively in the physical, economic, and social domain. The relationship between the two measures is examined using correlation analysis. It was determined that the association between them is weak and not significant, which could have been caused by the geographic scale and the sample size chosen. These two factors also affected the spatial autocorrelation check implemented to the 15 subjective indicators using the Moran’s I test. The results of this spatial autocorrelation check were the basis of the type of spatial prediction method used for each indicator. Out of 15, only 3 indicators were spatially autocorrelated. These 3 indicators were interpolated using Ordinary Kriging (OK). The rest is interpolated using the voronoi polygon. The 15 prediction maps were used to create the overall subjective QoL with the utilization of the Multi-Criteria Decision Analysis (MCDA) method called Weighted Sum. With all indicators grouped together, four maps are produced namely, physical, social, economic, and the overall QoL. Both physical and economic domains showed comparatively a below average QoL while the social domain with an average to above average result. The overall, which is the weighted sum of these three domains, generated a below average to an average assessment.

Document Type Master thesis
Language English
Advisor(s) Cabral, Pedro da Costa Brito; Mateu Mahiques, Jorge; Helle, Kristina; Granell-Canut, Carlos
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