Multidimensional Quality of Life in Cauvery River Basin, India
Description
Quality of Life (QoL) is a multidimensional concept which includes the physical, social, economic, and environmental well-being of humans. This research maps the multidimensional QoL over the administrative districts in southern India's Cauvery River basin. It quantifies QoL considering four main indices, i.e., Health, Education, Living Standard, and Environment, and 66 sub-indices. The data on the sub-indices have been collected, extracted, and compiled from different local, regional, national, and international sources. Remote Sensing data and geospatial techniques have been used for better mapping and analysis. The tabulation and normalization of the data were done in MS Excel Software. As the variables had different units, they were normalized using the standard formula. The normalized variables were then checked for correlation, using Spearman correlation in R studio. The redundant variable was then removed from the further analysis. The study finds that Kozhikode (Kerala), Bengaluru (Karnataka), and Coimbatore (Tamil Nadu) have the highest scores in the QoL index, whereas Chamarajanagar (Karnataka), Chikkaballapura and Ariyalur (Tamil Nadu) have the lowest scores. In addition, the high correlation of the sanitation sub-index (0.78) and household latrine indicator (0.78) with the QoL index showed credence over the relation and importance of the sanitation facility concerning QoL. Also, a high correlation with drinking water availability emphasizes developing and managing drinking water accessibility and sanitation facilities for better livability. Furthermore, the dimension of the living standard showed highly correlated and variance-holding subindexes (Sanitation - 0.78; Household Cooking and Fuel - 0.66; Occupancy-0.59 correlation and -0.37, 0.36, 0.38 variance score respectively). Dimension-wise, Kerala scored highest in health (0.71) and environmental quality (0.76), whereas Tamil Nadu and Puducherry scored highest in education quality (0.65) and living standards (0.56) respectively. The dataset can be used for further research and analysis related to QoL in the Cauvery River Basin. It will help in better planning and policy-making to improve the QoL in the region.
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At first data for the 66 sub-indices were collected from the following sources - 1. Population and Household related data was taken from the Census of India website (censusindia.gov.in). 2. Household Drinking data were collected from NITI Ayog DLHS- (2012-13) report. 3. Crime-related data were collected from National Crime Record Bureau (ncrb.gov.in) 4. Heritage and cultural site locations were collected from Bhuban NRSC (nrsc.gov.in). 5. Road network data were collected from the OpenStreetMap portal. 6. Health-related data were collected from the National Health Mission Report 2018-19. 7. Covid cases, deaths, and bed allocation data were collected from the State Covid Daily Bulletin (05 May 2021). 8. Covid vaccination data were collected from the CoWIN portal. 9. Women and child health-related data were collected from the National Family Health Survey Report (NFHS-5, March 2021). 10. Elementary education-related data were collected from the District report card report 2016-17 (udise.in). 11. Elevation and slope data were collected from the SRTM Global 30m DEM dataset (www.usgs.gov). 12. Urban heat island data were extracted from the NASA SEDAC Global Urban Heat Island dataset. 13. Forest cover-related data were collected from the Forest Survey of India 2019 report. 14. The land use land cover map was extracted from the ESRI Land Cover 2020 dataset. 15. Groundwater availability data were extracted from the IWRIS Groundwater portal (indiawris.gov.in/wris). The tabulation and normalization of the data were done in MS Excel Software. As the variables had different units, they were normalized using the standard formula. The normalized variables were then checked for correlation, using Spearman correlation in R studio. The redundant variable was then removed from the further analysis.