Assessing the influence of urbanization on the historic city of Paithan, India: a case study focusing on the urban core

Aishwarya Kasture and Nakul Dhagat

International Journal of Urban Sciences, 2025, vol. 29, issue 1, 221-246

Abstract: Historic cities around the world have been experiencing continuous threats to their cultural heritage due to the multifaceted pressures of urbanization, with historic cities being increasingly threatened by factors beyond population migration, such as changes in land use, degradation of historic character, urban decay, lack of socio-economic development and challenges to sustainable urbanization, Historic City reestablishment becomes vital, as this would promote sustainable growth. Analysing the impacts and extent of urbanization in historic cities is essential to determine how one might help mitigate it. This study investigates the impact of urbanization on the cultural heritage of the historic city of Paithan, Aiming to answer two key questions: how does urbanization alter the physical and sociocultural fabric of Paithan’s urban historic core, and what factors drive these changes, with the primary objective focussing on assessing the extent of urbanization-led changes and identifying key socio-economic and physical variables influencing this transformation. Four ML models – K-Nearest Neighbour (kNN), Support Vector Machines (SVM), Logistic Regression, and the Random Forest Method were applied to analyse urbanization data. A set of 11 predictor variables was identified, and the findings reveal the rising land values and changing building use as primary drivers of transformation, leading to a decline in traditional architectural elements. The RFM model emerged as the most accurate model, with an accuracy of 89.3%, providing the most accurate insights into the non-linear relationships between the variables. The study concludes with a call for inclusive growth, balancing sustainable development and modern needs. The ML models chosen for this study use open-source data as well as field surveys.

Date: 2025
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DOI: 10.1080/12265934.2025.2452513

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