Assessing Urban Transformation and Green Infrastructure in Bhilwara Through Machine Learning and Earth Observation

Abstract

This study critically examines the spatial dynamics of urban sprawl and land use changes in Bhilwara, Rajasthan, over the past three decades, utilizing advanced remote sensing and GIS methodologies. The primary objective is to elucidate the patterns of urban expansion and its consequential impacts on green infrastructure. The findings reveal a pronounced increase in built-up areas, with the most significant growth observed towards the north-northwest (NNW) and west-southwest (WSW) directions, driven by the presence of major transportation corridors and proximate urban centers. The LULC classification achieved high accuracy, with Producer’s accuracy ranging from 81 to 94.4%, User’s accuracy from 73.7 to 100%, and Overall accuracy between 84.5 and 93.8%, accompanied by a Kappa coefficient of 0.78 to 0.83. These results underscore the robust methodology employed and highlight the critical need for integrated urban planning approaches that prioritize sustainable development and green infrastructure preservation. The study’s conclusions offer substantial contributions to the academic discourse on urbanization, providing actionable insights for policymakers and urban planners to manage urban growth effectively and sustainably.