Multi-criteria approach to geographically visualize the quality of life in India. Issue 6 (1st November 2016)

• Record Type: Journal Article
• Authors: Prakash, Mridu; Shukla, Roopam; Chakraborty, Anusheema; Joshi, P. K.
• Is Part Of: International journal of sustainable development and world ecology. Volume 23:Issue 6(2016)
• Page Start: 469
• Page End: 481
• Publication Date: 2016-11-01
• Subjects: Quality of life -- census -- remote sensing -- GIS -- data integration -- AHP; Sustainable development -- Periodicals; Ecology -- Periodicals; Economic development -- Environmental aspects -- Periodicals; Ecologie; Duurzame ontwikkeling; Ecology; Economic development -- Environmental aspects; Sustainable development; Periodicals; Electronic journals; 338.72
• DOI: 10.1080/13504509.2016.1141119
• Languages: English
• ISSNs: 1745-2627

Abstract

ABSTRACT: Quality of Life (QoL) is the description and evaluation of coincidences among social, economic and ecological conditions in a particular community, locality, region or a country. By categorising regions according to their QoL, one can examine and assess not only the possible impacts of development programmes, but also the pressure from environmental degradation processes. This study maps QoL at the sub-national level (districts) in India, conceptualized under three pillars of sustainable development. The assessment uses 10 sub-indices constructed using 54 indicators (49 from Census of India database and 5 remote sensing inputs). Recognising that not every indicator is of equal importance, analytical hierarchy process (AHP) was used to assign weights to the indicators and sub-indices. Furthermore, geostatistical Moran's I clustering was done to assign priority to QoL classes. Distribution of high QoL shows correspondence with the network of national highways throughout the country. Significant dependence of QoL was observed with urban population (r 2 ~ 0.75–0.95), rural population (r 2 ~ 0.75–0.98) and Human Development Index (HDI) (r 2 > 0.7) for different states. The geostatistical analysis identifies clusters of districts which can significantly improve the living conditions with priority actions, and where interventions and long-term planning would be required. The results of this study can serve as the basis for targeting prioritization efforts, and policy interventions at district level for improving QoL and, perhaps, achieving Sustainable Development Goals (SDGs) as well.