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Analysis of Life Quality in a Tropical Mountain City Using a Multi-Criteria Geospatial Technique: A Case Study of Kandy City, Sri Lanka

Author

Listed:
  • DMSLB Dissanayake

    (Department of Environmental Management, Faculty of Social Sciences and Humanities, Rajarata University of Sri Lanka, Mihintale 50300, Sri Lanka)

  • Takehiro Morimoto

    (Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-8572, Japan)

  • Yuji Murayama

    (Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-8572, Japan)

  • Manjula Ranagalage

    (Department of Environmental Management, Faculty of Social Sciences and Humanities, Rajarata University of Sri Lanka, Mihintale 50300, Sri Lanka
    Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-8572, Japan)

  • ENC Perera

    (Department of Regional Science and Planning, SANASA Campus, Kegalle 71000, Sri Lanka)

Abstract

The blooming of urban expansion has led to the improvement of urban life, but some of the negative externalities have affected the life quality of urban dwellers, both directly and indirectly. As a result of this, research related to the quality of life has gained much attention among multidisciplinary researchers around the world. A number of attempts have been made by previous researchers to identify, assess, quantify, and map quality of life or well-being under various kinds of perspectives. The objectives of this research were to create a life quality index (LQI) and identify the spatial distribution pattern of LQI in Kandy City, Sri Lanka. Multiple factors were decomposed, a hierarchy was constructed by the multi-criteria decision making (MCDM) method, and 13 factors were selected under two main criteria—environmental and socioeconomic. Pairwise comparison matrices were created, and the weight of each factor was determined by the analytic hierarchy process (AHP). Finally, gradient analysis was employed to examine the spatial distribution pattern of LQI from the city center to the periphery. The results show that socioeconomic factors affect the quality of life more strongly than environmental factors, and the most significant factor is transportation. The highest life quality zones (26% of the total area) were distributed around the city center, while the lowest zones represented only 9% of the whole area. As shown in the gradient analysis, more than 50% of the land in the first five kilometers from the city center comes under the highest life quality zone. This research will provide guidance for the residents and respective administrative bodies to make Kandy City a livable city. It the constructed model can be applied to any geographical area by conducting necessary data calibration.

Suggested Citation

  • DMSLB Dissanayake & Takehiro Morimoto & Yuji Murayama & Manjula Ranagalage & ENC Perera, 2020. "Analysis of Life Quality in a Tropical Mountain City Using a Multi-Criteria Geospatial Technique: A Case Study of Kandy City, Sri Lanka," Sustainability, MDPI, vol. 12(7), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2918-:d:342061
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    References listed on IDEAS

    as
    1. DMSLB Dissanayake & Takehiro Morimoto & Yuji Murayama & Manjula Ranagalage, 2019. "Impact of Landscape Structure on the Variation of Land Surface Temperature in Sub-Saharan Region: A Case Study of Addis Ababa using Landsat Data (1986–2016)," Sustainability, MDPI, vol. 11(8), pages 1-18, April.
    2. Eva Psatha & Alex Deffner & Yannis Psycharis, 2011. "Defining the quality of urban life: Which factors should be considered?," ERSA conference papers ersa11p785, European Regional Science Association.
    3. Worawej Onnom & Nitin Tripathi & Vilas Nitivattananon & Sarawut Ninsawat, 2018. "Development of a Liveable City Index (LCI) Using Multi Criteria Geospatial Modelling for Medium Class Cities in Developing Countries," Sustainability, MDPI, vol. 10(2), pages 1-19, February.
    4. Escobar, M. T. & Aguaron, J. & Moreno-Jimenez, J. M., 2004. "A note on AHP group consistency for the row geometric mean priorization procedure," European Journal of Operational Research, Elsevier, vol. 153(2), pages 318-322, March.
    5. Forman, Ernest & Peniwati, Kirti, 1998. "Aggregating individual judgments and priorities with the analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 108(1), pages 165-169, July.
    6. Thomas L. Saaty & Luis G. Vargas, 2012. "Models, Methods, Concepts & Applications of the Analytic Hierarchy Process," International Series in Operations Research and Management Science, Springer, edition 2, number 978-1-4614-3597-6, September.
    7. Manjula Ranagalage & Yuji Murayama & DMSLB Dissanayake & Matamyo Simwanda, 2019. "The Impacts of Landscape Changes on Annual Mean Land Surface Temperature in the Tropical Mountain City of Sri Lanka: A Case Study of Nuwara Eliya (1996–2017)," Sustainability, MDPI, vol. 11(19), pages 1-26, October.
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    1. Yuji Murayama & Matamyo Simwanda & Manjula Ranagalage, 2021. "Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries," Sustainability, MDPI, vol. 13(7), pages 1-5, March.

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