Determining region of urban expansion based on urban growth pattern and intensity as a driving factor using regression modelling approach in Salem, India

In the context of increasing urbanisation, it is vital to understand the factors driving urban expansion to ensure balanced and sustainable urban growth. However, obtaining precise data on the factors influencing urban expansion is difficult. Nonetheless, studying the patterns and intensities of urban growth can indirectly provide valuable insights. Hence, this study investigates urban growth patterns and intensities in Salem, India, over the last three decades by examining infill, sprawl, scattered, and ribbon development patterns through spatial analysis. The research addresses two critical gaps: the need for a simplified predictive model for urban growth in limited data scenarios and an appropriate methodology to map ribbon development in the Indian context. The results revealed a significant increase in built-up areas between 2011 and 2020, with ribbon development emerging as the most common type of pattern. The findings further demonstrate increasing urban growth on the city’s periphery, impacting agricultural land and damaging the local economy. The study also found that neighbouring towns like Omalur, Rasipuram, Sankari, and Vazhapadi influence Salem’s urban growth patterns. These changes are due to the dynamic interaction of population expansion, accessibility, agricultural land, and urban development issues. Urban Expansion Intensity Index (UEII) quantifies the intensity and provides additional information on the expansion rate. The study classifies growth rate into five categories: very slow, slow, medium, high, and very high. Between 2001 and 2011, high-intensity values were most common in the core regions of Salem and Omalur. However, these values dispersed over the subsequent decade, becoming more common in suburban areas. The study provides a new model for predicting growth based on patterns and intensity. A unique buffer tool for creating regions surrounding existing buildings generated areas with an error margin of less than 0.1 sq. km. This resulted in a spatial agreement of 74.11% with the predictions made by the CA-Markov model. The research presents a new model for predicting urban growth with limited variables, demonstrating high spatial agreement with existing models. Assessing the intensity of urban expansion provides a detailed framework for understanding urban growth dynamics. The encroachment of agricultural land and its economic consequences emphasise the need for sustainable urban development strategies. The study underscores the significance of regional and integrated planning and collaborative development strategies by examining the impact of neighbouring cities on Salem’s urban growth.