Cities in Southeast Asia (SEA) face dual challenges from climate change and urban heat island (UHI) effects. Despite governmental efforts to mitigate UHI and promote sustainable urban development, significant policy gaps persist including the absence of UHI-specific regulations, insufficient integration of green infrastructure and low public awareness. This research aims to analyse UHI dynamics and their relationship with Land use land cover (LULC) and Local Climate Zone (LCZ) by taking Kuala Lumpur as the case study using an integrated system of remote sensing, geospatial analysis and climate modeling to establish a communication framework between science, policy and action in combating the UHI effects. Specifically, satellite data is utilized to analyze spatial and temporal UHI patterns, correlating with changes in LULC and LCZ. Machine learning classifier will generate LCZ maps and conduct an accuracy assessment. Statistical methods like regression and correlation analysis will explore the relationships between LULC, LCZ, and UHI. Additionally, the study adopts climate modeling incorporating the latest urban canopy model, for a comprehensive understanding of the urban thermal environment. By examining the interactions between climate dynamics, LCZ variations, and UHI drivers, this research will offer insights into effective urban management and contribute to the understanding of the urban thermal environment and its drivers for urban management in SEA.