Abstract
Urban heat islands (UHIs) pose significant risks to human health, energy consumption, and environmental sustainability. Digital twins (DTs) offer a promising approach to simulate, monitor, and mitigate UHI effects by integrating real-time data, predictive models, and stakeholder engagement. This paper reviews the state of the art in UHI mitigation strategies and digital twin technologies, synthesizing findings from 30 recent studies. We propose a conceptual framework for a UHI digital twin that incorporates multi-scale modeling (building, street, city), data fusion (remote sensing, IoT, citizen science), and decision support for mitigation measures such as green infrastructure, cool pavements, and urban morphology changes. Key challenges include data integration, model scalability, and equity considerations. The framework is illustrated through a hypothetical case study of a mid-sized city. Results indicate that DTs can reduce UHI intensity by up to 2–4°C when combined with targeted interventions. We conclude with recommendations for future research, including the need for standardized metrics, open-source platforms, and community participation.