Exploring the drivers of urban expansion in a medium-class urban agglomeration in India using the remote sensing techniques and geographically weighted models

Abstract

Rapid urbanization urges the immediate attention of policymakers to ensure sustainable city development. Understanding the urban growth drivers is essential to address effective strategies for urbanization-related challenges. This work aims to study Raiganj’s urban development and the factors associated with this expansion. This study employed global logistic regression (LR) and geographical weighted logistic regression (GWLR) to explore the role of different factors. The results showed that the role of the central business district (covariate >-1), commercial market (covariate >-3), and police station (covariate >-4) were significant to the development of new built-up areas. In the second period, major roads (covariate >-2) and new infrastructures (covariate >-4) became more relevant, particularly in the eastern and southern areas. GWLR was more accurate in assessing the different factors’ impact than LR. The results obtained are essential to understanding urban expansion in India’s medium-class cities, which is critical to effective policies for sustainable urbanization.

Keywords

• Drivers
• Geographically weighted logistic regression (GWLR)
• Logistic regression
• LULC
• Urban growth