Abstract. Urbanization and climate change are rapidly transforming metropolitan environments, posing serious challenges to sustainable development, climate resilience, and disaster risk management, Among these challenges, concern, where built up areas experiences higher temperatures than surrounding rural regions due to increased impervious surfaces, vegetation loss and altered urban morphology. As UHI intensifies heatwave impacts and public health risks, advanced tools are required to monitor, simulate and mitigate urban heat dynamics. This Study analyses the spatio-temporal evolution of Land Surface temperature (LST) and UHI intensity in Bengaluru for 2004 to 2024 using multi-temporal Landsat data. Key surface indicators include, NDVI, NDBI, NDWI, albedo ad LULC were derived to assess thermal behaviour. Results indicate rapid built-up expansion and declining vegetation, leading to the regression predicts 1-2 °C increases in LST by 2023 in highly urbanized areas.To support urban climate decision making, a 3D Digital Twin platform was developed using CesiumJS, integrating geospatial analysis, remote sensing, and predictive simulations. The framework demonstrates the potential of Digital Twins as an effective decision-supportive tool for climate-adaptive and sustainable urban planning.
B et al. (Mon,) studied this question.