Modelling urban future: integrating CA-ANN model for comprehensive understanding of land use, land cover changes, and temperature dynamics in Lucknow City, India
Danish Khan, Nizamuddin Khan
Abstract
Rapid urbanization and associated land use/land cover (LULC) changes significantly affect urban environments, intensifying urban heat islands (UHIs) and environmental challenges. This study presents a spatiotemporal analysis of LULC and land surface temperature (LST) changes in Lucknow City, India, from 2001 to 2021, and predicts scenarios for 2031. Using Landsat imagery and support vector machine classification, results reveal that built-up areas expanded from 10.93% (127.82 km²) to 25.47% (297.74 km²), while vegetation declined from 71.55% (836.43 km²) to 45.33% (530.04 km²). Mean LST increased from 25.3°C to 29.8°C, with 51.75% of the area reaching 30–35°C in 2021. Cellular automata–artificial neural network (CA-ANN) models predict built-up areas to reach 29.99% (350.51 km²) and vegetation to drop to 42.62% (498.10 km²) by 2031. The ANN model further forecasts UHI intensification, with 58.95% of the city experiencing LSTs above 30°C, reaching a maximum of 42.7°C. The findings emphasize the urgent need for sustainable urban planning to mitigate environmental degradation and maintain ecological balance amid ongoing urban expansion in Lucknow.