Mapping the Quality of Life Experience in Alfama: A Case Study in Lisbon, Portugal

  • Pearl May dela Cruz
  • Pedro Cabral
  • Jorge Mateu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6782)


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 suggesting the subjective and objective QoL respectively in the physical, economic, and social domains. 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. These two factors also affected the spatial autocorrelation check implemented to the 15 subjective indicators using the Moran’s I test. 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. All 15 prediction maps were used to create the overall subjective QoL using Weighted Sum procedure.


Spatial Prediction Methods Ordinary Kriging Weighted Sum Voronoi Polygon Moran’s I Test Quality of Life 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Campbell, A., Converse, P., Rodgers, W.: The Quality of American Life: Perceptions, Evaluations and Satisfaction. Russel Sage Foundation, New York (1976)Google Scholar
  2. 2.
    Rogerson, R.: Quality of life and city competitiveness. Urban Studies 36(5), 969–985 (1999)CrossRefGoogle Scholar
  3. 3.
    Tuan Seik, F.: Subjective assessment of urban quality of life in Singapore (1997-1998). Habitat International 24(1), 31–49 (2000)CrossRefGoogle Scholar
  4. 4.
    Costanza, R., Fisher, B., Ali, S., Beer, C., Bond, L., et al.: Quality of lif: An approach integrating opportunities, human needs, and subjective well-being. Ecological Economics 61(2-3), 267–276 (2007)CrossRefGoogle Scholar
  5. 5.
    Bonnes, M., Uzzell, D., Carrus, G., Kelay, T.: Inhabitants’ and experts’ assessments of environmental quality for urban sustainability. Journal of Social Issues 63(1), 59–78 (2007)CrossRefGoogle Scholar
  6. 6.
    Das, D.: Urban quality of life: A case study of Guwahati. Social Indicators Research 88(2), 297–310 (2007)CrossRefGoogle Scholar
  7. 7.
    Tesfazghi, E., Martinez, J., Verplanke, J.: Variability of quality of life at small scales: Addis Ababa, Kirkos sub-city. Social Indicators Research 98(1), 73–88 (2010)CrossRefGoogle Scholar
  8. 8.
    Bowling, A.: Measuring Health: A Review of Quality of Life Measurement Scales, American Journal of Physics, Berkshire, UK (2005)Google Scholar
  9. 9.
    Paler-Calmorin, L., Calmorin, M.: Statistics in Education and the Sciences: With Application to Research, Rex Bookstore Inc., Quezon City (1997)Google Scholar
  10. 10.
    Olsson, U., Drasgow, F., Dorans, N.: The polyserial correlation coefficient. Psychometrika 47(3), 337–347 (1982)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Upton, G., Fingleton, B.: Spatial Data Analysis by Example: Point Pattern and Quantitative Data. Wiley, University of Michigan (1985)zbMATHGoogle Scholar
  12. 12.
    Bivand, R., Pebesma, E., Gomez-Rubio, V.: Applied Spatial Data Analysis with R. Springer, Heidelberg (2008)zbMATHGoogle Scholar
  13. 13.
    Hengl, T.: A practical Guide to Geostatistical Mapping, Office for Official Publications of the European Communities, Luxembourg (2009)Google Scholar
  14. 14.
    Okabe, A., Boots, B., Sugihara, K.: Spatial Tessellations: Concepts and Applications of Voronoi Diagrams. John Wiley & Sons, Chichester (1992)zbMATHGoogle Scholar
  15. 15.
    Kim, I.Y., de Weck, L.: Adaptive weighted sum method for multiobjective optimization: a new method for Pareto front generation. Structural and Multidisciplinary Optimization 31(2), 105–116 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Altman, D., Bland, J.: Statistics notes: Absence of evidence is not evidence of absence. BMJ 311, 485 (1995)CrossRefGoogle Scholar
  17. 17.
    Veenhoven, R.: Why social policy needs subjective indicators. Social Indicators Research, 33–45 (2004)Google Scholar
  18. 18.
    Cummins, R.: Objective and subjective quality of life: An interactive model. Social Indicators Research 52(1), 55–72 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pearl May dela Cruz
    • 1
    • 2
  • Pedro Cabral
    • 1
    • 2
  • Jorge Mateu
    • 1
    • 2
  1. 1.Instituto Superior de Estatística e Gestão de Informação, ISEGIUniversidade Nova de LisboaLisboaPortugal
  2. 2.Departament de MatemàtiquesUniversitat Jaume ISpain

Personalised recommendations