Multi-scale analysis of rural and urban areas: A case study of Indian districts

TL;DR

This study applies allometric urban scaling laws to Indian districts, revealing that socio-economic indicators scale predictably with population size across different urbanization levels, with variations over time and class.

Contribution

It extends urban scaling analysis to district-level data in India, including rural and semi-urban areas, and examines changes over a decade.

Findings

Scaling laws are valid at district level for most socio-economic indicators.

High goodness-of-fit (R^2 > 0.8) for many indicators across classes.

Some indicators exhibit super-linear or sub-linear scaling behaviors.

Abstract

This paper explores the extension of the idea of allometric urban scaling law to study the scaling behaviour of Indian districts, with both the urban and rural population. To proceed, we have chosen districts (both rural and urban) of India, a relatively larger local administrative units, which are more or less independently functional within a country. This interdisciplinary work focus on the scaling analysis of various socio-economic indicators (SEIs) corresponding to the size (population) of four distinct urbanization classes, namely rural, semi-rural, semi-urban and urban districts. The scaling exponents were estimated for each classes for the years 2001 and 2011 along with their goodness-of-fit measured by the $R^2$ values. Our rigorous statistical analysis indicates that the scaling laws indeed exist even at the district level for most of the SEIs considered, related to education, employment, housing, health, etc.; the $R^2$ values obtained for these SEIs are very high (often greater than 0.8 or 0.9) in both the the years. Moreover, linearity of the scaling factors have been statistically tested and it has been found, at 95% level of confidence, that not all the SEIs behave linearly; some of them are characterized by super-linear behaviour and some behave sub-linearly. Statistical hypothesis tests have also been performed to test the equality of two scaling factors corresponding to two distinct classes and two different years to understand the differences in scaling relationships among increasing urbanisation classes and their changes over time.