Rajib Pegu, Tanisha Mazumder, Hrykpb Borah, Kuldeep Bora, Parishmita Hazarika
Rapid urbanization has substantially transformed land use/land cover (LULC) patterns and intensified urban thermal environments, particularly in rapidly expanding cities of the Global South. Understanding the relationship between LULC dynamics and land surface temperature (LST) is essential for sustainable urban planning and climate adaptation. This study investigates the spatio-temporal changes in LULC and LST in Guwahati, Assam, India, over a 30-year period (1995-2024) using multi-temporal Landsat imagery processed on the Google Earth Engine (GEE) platform. LULC maps were generated using the Random Forest (RF) classifier, while LST was retrieved from Landsat thermal bands using the radiative transfer approach with Normalized Difference Vegetation Index (NDVI)-based emissivity correction. Long-term temperature trends were evaluated using the Mann-Kendall (MK) test and Sen's slope estimator. In addition, Pearson's correlation, linear regression, and one-way ANOVA were employed to quantitatively examine the relationship between vegetation, LULC, and LST using 5000 randomly sampled pixels from the 2024 dataset. The results revealed that the mean LST increased from 28.27 °C in 1995 to 32.07 °C in 2024, coinciding with rapid urban expansion and a substantial decline in vegetation and agricultural land. Built-up areas exhibited the highest mean LST (36.11 °C), whereas water bodies recorded the lowest (27.29 °C). A statistically significant warming trend was confirmed by the MK test (p < 0.05). Pearson's correlation further demonstrated a significant inverse relationship between NDVI and LST (r = -0.492, p < 0.001), while linear regression indicated that vegetation explained approximately 24.2% of the spatial variability in LST (R2 = 0.2424). ANOVA also revealed significant differences in LST among LULC classes (p < 0.001). These findings demonstrate that urbanization-driven landscape transformation is a major driver of surface warming in Guwahati and underscore the importance of conserving urban vegetation, wetlands, and other natural landscapes. The study provides scientific evidence to support climate-responsive urban planning and contributes to Sustainable Development Goals (SDGs) 11 (Sustainable Cities and Communities), 13 (Climate Action), and 15 (Life on Land).