Due to climate change and urban heat islands, urban populations have been increasingly exposed to heat risks. To support the development of mitigation measures, this dissertation examined the impacts of urban surface characteristics and greening interventions on cooling demand, using Ho Chi Minh City as a case study.
Three interconnected components were addressed in this work. First, a scoping review highlighted the scarcity of research on the correlation between urbanization and thermal environments, despite the integration of urban sustainability into national climate policy. Second, analysis of statistical data and satellite imagery, supported by machine learning, indicated a strong contribution of urban expansion and densification to heat island intensity. Third, the evaluation of cooling measures using various methods indicated green walls as the most effective, followed by surface conversion and water integration, with wind dynamics enhancing their spatial distribution. Cooling effects were observed to be more pronounced in less dense areas.
Overall, by quantifying cooling demand and evaluating interventions, the findings offer actionable insights for urban planning and development, supporting long-term strategies for heat mitigation and climate resilience. The research approach also presents a transferable framework for employing open data and promoting artificial intelligence in urban heat dynamics studies.
Thi Le Kieu
Urbanization Heat Island Heat Dynamics Urban Climate Urban Physics Urban Surface Green City Green Infrastructure Cooling Demand Thermal Comfort Remote Sensing Thermodynamic Simulation Machine Learning Ho Chi Minh City Vietnam