- English
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.
- English
