A quality of life index for the rural periphery of Sri Lanka using GIS multi-criteria decision analysis techniques.
Neel Chaminda Withanage, Kalpani Lakmali Gunathilaka, Prabuddh Kumar Mishra, Kamal Abdelrahman, Dilnu Chanuwan Wijesinghe, Vishal Mishra, Sumita Tripathi, Mohammed S Fnais
Author Information
Neel Chaminda Withanage: Faculty of Humanities and Social Sciences, Department of Geography, University of Ruhuna, Matara, Sri Lanka.
Kalpani Lakmali Gunathilaka: Faculty of Arts, Department of Geography, University of Colombo, Colombo, Sri Lanka.
Prabuddh Kumar Mishra: Department of Geography, Shivaji College, University of Delhi, New Delhi, India. ORCID
Kamal Abdelrahman: Department of Geology and Geophysics, College of Science, King Saud University, Riyadh, Saudi Arabia.
Dilnu Chanuwan Wijesinghe: Faculty of Humanities and Social Sciences, Department of Geography, University of Ruhuna, Matara, Sri Lanka.
Vishal Mishra: Helmholtz Centre Potsdam, Remote Sensing and Geoinformatics section, GFZ German Research Centre for Geosciences, Telegrafenberg, Potsdam, Germany.
Sumita Tripathi: Department of Environment Studies, Shri Lal Bahadur Shastri National Sanskrit University, New Delhi, India.
Mohammed S Fnais: Department of Geology and Geophysics, College of Science, King Saud University, Riyadh, Saudi Arabia.
Spatial evaluation of the region is associated with the assessment of the Quality of Life (QoL). Despite numerous research endeavoring to define, measure, quantify, and map the quality of life, there exists a consistent fault in Sri Lanka. Hence, the objective of this study was to construct a QoL index and determine the spatial disparities of QoL from the Polpitigma town to its periphery. The assessment was conducted by employing 20 geographical factors that quantify QoL using the Geographic Information Systems (GIS). The evaluation assigned weights to each criterion based on the assessments of both local residents and experts, utilizing the Multi-Criteria Decision Analysis (MCDA) and the Analytical Hierarchy Process (AHP). The findings indicated that cultural factors made a greater contribution compared to the environment,service functions,security and socioeconomic factors. Within the study area, the region with a higher quality of life (HQoL) only covered 4.5% (17.3 km2), whilst the lower QoL zone encompassed 63.8% (252 km2). And also, the distance from the town is a crucial factor in determining the spatial variations in QoL. The derived model can serve as a road map for local-level planning, as it has been validated and shown to have an accuracy of 74% through the Receiver operating characteristic (ROC) curve. Considering the lack of previous research in this field, this study offers a crucial contribution in enhancing the QoL for underprivileged communities in the study area by improving employment, income, and accessibility to physical infrastructure, public utility services, and cultural and recreational facilities. Especially the findings of this study can efficiently guide decisions for the distribution of financial resources to enhance the QoL in impoverished rural communities on the rural periphery of DS.
References
Health Qual Life Outcomes. 2016 Jan 12;14:7
[PMID: 26758624]