Rapid urbanisation across the globe has resulted in expanding cities beyond their boundaries, which is exerting pressure on the environment, resulting in a plethora of environmental issues, including degradation of ecosystems, loss of biodiversity, the emergence of urban heat islands, and changes in the climate. Changes in land use leading to landscape dynamics have altered the land surface temperature. This study explores linkages of land use dynamics with land surface temperature (LST) in Kerala, India, using a machine learning algorithm with temporal Remote Sensing (RS) data (2014–2023) of Landsat 8 OLI/TIRS and Landsat 9 OLI/TIRS. LST is computed through a Single window algorithm, and hotspots of urban heat islands are mapped using LST spatial data. Land use analyses revealed a reduction in the vegetation cover with an increase in the built-up area. The mean LST of the region has increased with an increase in impervious surfaces, such as built-up areas, etc. Lower LST were observed in land uses under forest cover and water bodies. The correlation analysis revealed that LST is negatively correlated with NDVI and positively correlated with NDBI. Hotspot analysis indicated that the urban hotspots have increased over time, and the highly urbanised areas have emerged as the new hotspot centres in the state. This study demonstrated that the increase in built-up, with land degradation and deforestation, has led to the decline of the natural land cover, which has contributed to a rise in the land surface temperature of the region. The findings from this study are important for urban land use planning and empower policymakers in informed decision-making with insights into the consequences of unplanned developmental activities and to take necessary actions for sustainable development and the conservation of the environment.