Spatial Analysis of Population Landscape: A Case Study of Scheduled Caste Population in Basti District

Abstract

The scheduled Caste (SC) population has significant importance and proportion in Indian society. They are unprivileged, marginalized, and backward, with a higher rural presence having significant regional disparities in terms of socio-economic indicators. Several studies have documented various socio-economic factors that influence these characteristics. In recent times, the effort of government initiatives to improve living conditions has influenced their distributional pattern with time. In 2011, the scheduled caste population was predominantly made up of 20.85 % of the total population of the Basti district. Most studies in the arena of population geography have exclusively focused on population distribution. This research investigates the geographical distribution and concentration of the Scheduled Caste (SC) people in several blocks of the Basti district in Uttar Pradesh, India. Most studies in the area of population studies have exclusively focused on the percentage of block population in the total population as a method to calculate the concentration of the population, which is a raw number alone and does not provide reliable information about the distribution. This study offers a novel approach for quantifying SC population distribution across different blocks of Basti District using the Location Quotient (LQ) method to analyze census data, which provides a relative measure of SC population concentration compared to the overall population distribution and reveals areas with a higher or lower SC population proportion compared to the district average. Upon analyzing the LQ values for the 2011 census data, it was seen that there had been a growing concentration of Scheduled Caste (SC) population in the core regions spanning from North to South and West to East. The concentration of the SC population in Basti district is found to be low in the northern and western parts, medium in the central part, and high in some parts of the eastern and south-eastern part. The above information will contribute to researchers, policymakers, and social activists in understanding the socio-economic inequalities of the district.