Key points are not available for this paper at this time.
Amid global concerns regarding climate change and urbanization, understanding the interplay between land use/land cover (LULC) changes, the urban heat island (UHI) effect, and land surface temperatures (LST) is paramount. This study provides an in-depth exploration of these relationships in the context of the Kamrup Metropolitan District, Northeast India, over a period of 22 years (2000–2022) and forecasts the potential implications up to 2032. Employing a high-accuracy supervised machine learning algorithm for LULC analysis, significant transformations are revealed, including the considerable growth in urban built-up areas and the corresponding decline in cultivated land. Concurrently, a progressive rise in LST is observed, underlining the escalating UHI effect. This association is further substantiated through correlation studies involving the normalized difference built-up index (NDBI) and the normalized difference vegetation index (NDVI). The study further leverages the cellular automata–artificial neural network (CA-ANN) model to project the potential scenario in 2032, indicating a predicted intensification in LST, especially in regions undergoing rapid urban expansion. The findings underscore the environmental implications of unchecked urban growth, such as rising temperatures and the intensification of UHI effects. Consequently, this research stresses the critical need for sustainable land management and urban planning strategies, as well as proactive measures to mitigate adverse environmental changes. The results serve as a vital resource for policymakers, urban planners, and environmental scientists working towards harmonizing urban growth with environmental sustainability in the face of escalating global climate change.
Choudhury et al. (Mon,) studied this question.