Quantifying spatiotemporal land use land cover change and urban expansion using geospatial modelling and shannon’s entropy in a coastal city of India

This study quantitively examines spatiotemporal Land Use and Land Cover (LULC) changes in Thoothukudi Municipal Corporation from 2010 to 2024, employing advanced remote sensing and Geographic Information System (GIS) techniques integrated with multivariate statistical methods to derive meaningful insights into urban transformation dynamics. For multi-temporal LULC classification, Landsat satellite images were obtained from the USGS Earth Explorer platform, including Landsat-7 ETM + (March 2010) and Landsat-8 OLI/TIRS (January 2015, April 2020, and May 2024). The novelty of this work lies in integrating entropy and regression analyses to link LULC transitions with industrial expansion, revealing accelerated urban sprawl and ecological stress. The analysis reveals significant urban transformation in the study area from 2010 to 2024, primarily driven by large-scale industrial expansion. Built-up areas expanding by 283.5% (15.34–58.81 km2), shrubland declining by 95.7% (29.64–1.27 km2), and water bodies decreased by 21.3% (19.27–15.17 km2). The reliability of the accuracy assessment results was assessed using Kappa statistics. Classification accuracy ranged from 86 to 92%, with Kappa coefficients between 0.82 and 0.90. Shannon’s entropy peaked at 2.46 in 2015, indicating maximum landscape heterogeneity, but declined to 2.11 by 2024, reflecting increasing homogeneity. Linear regression analysis supports this, showing strong positive trends in settlement (slope = + 11.44, R2 = 0.94) and cultivated land (slope = + 3.98, R2 = 0.84), indicating urban and agricultural expansion. These changes highlight rapid urban sprawl, increased ecological pressure, and the need for sustainable urban planning to mitigate future socio-environmental challenges.