Mapping hotspot clustering: An approach to study the spatial pattern of quality of living households in India

Ravichandrran, Venkatesh, Kantamaneni, Komali orcid iconORCID: 0000-0002-3852-4374, Singh, Aditya, Nair, Aishwarya, Janakiraman, A, Kumar, Sukumar Prem and Choudhury, Shubham Dhar (2023) Mapping hotspot clustering: An approach to study the spatial pattern of quality of living households in India. Remote Sensing Applications: Society and Environment, 31 .

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This study provides insight into the regional disparity of households’ quality of living standards in India through the selective indicators. A household quality of living index (HQI) which is called a composite index was developed by integrating four indices which are housing facility index (HFI-1), basic facility index (BFI-2), financial asset index (FAI-3) and human capital index (HCI-4). These four indices have been developed from 23 census indicators through entropy techniques. The research findings indicate that the central (Chhattisgarh, Madhya Pradesh, Uttar Pradesh), eastern (Odisha, Jharkhand), and northeastern region (Arunanchal Pradesh and Nagaland) have poor living standards, and these are highly influenced by the basic facility index and financial asset index. Further, the indicators like concrete materials, radio, computer, two-wheeler, four-wheeler and drainage systems are totally in the poor category for almost 95% of the districts of India. Accordingly, hotspot GIS maps were generated and these maps explored that the 24.6% (157 districts) of the study region covered by hotspot showing poor quality of living. Nearly 14 states covered by hotspots, in which Bihar has the highest hotspot district (29), followed by Odisha (24), Madhya Pradesh (22) and Jharkhand (20). Additionally, three set of hotspot clusters were created for the developmental purpose: Cluster 1: (Odisha, Chhattisgarh and Madhya Pradesh), cluster 2: (Bihar, Jharkhand and West Bengal) and cluster 3: (Assam and Meghalaya). Where cluster 1 needs immediate attention followed by cluster 2 and 3. The current study results certainly assists the regional and national policy and decision makers to implement the development plan in hotspot clusters to enhance the quality of living.

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