Towards Climate Adaptive Urban Planning: Minimum Urban Units-Based Adaptation Strategies to Mitigate UHI with AI Support

The Urban Heat Island (UHI) effect poses an increasingly significant challenge to urban areas in the context of climate change, necessitating innovative and sustainable planning strategies. This chapter introduces a methodological framework that integrates the concept of minimum urban units (MUUs) to delineate and characterise the physical and environmental aspects of cities. This integration allows for more detailed and responsive urban management, combining socio-demographic, urban mobility, and urban health information. By adopting a multidisciplinary perspective, this study examines urban morphology and MUUs to further tailor adaptive strategies to LCZs, thereby offering a better understanding of UHI’s spatial variability and pinpointing optimal locations and techniques for intervention. This study aims to facilitate the strategic implementation of interventions, supported by an integrated LCZ and MUU approach, and enhance not only urban climate adaptability but also thermal comfort, thereby addressing the broader health challenges posed by climate change to urban inhabitants. This chapter details the procedure for selecting and classifying adaptive solutions and introduces the prospective development of an AI-driven decision support tool. This envisaged tool by employing machine learning algorithms, aims to predict the efficacy of interventions in specific urban contexts, thereby enabling a refined and forward-looking assessment of their microclimatic impact. The contributions of this research are manifold: it establishes a comprehensive framework for the technical selection and decision-making processes regarding UHI mitigation strategies underpinned by LCZ and MUUs analysis. Furthermore, it heralds the potential integration of AI and machine learning to bolster urban planning decision-making. The overarching goal is to advance sustainable urban planning practices that not only counteract the UHI effect but also promote thermal comfort, thus addressing the wider health challenges posed by climate change to urban inhabitants. This research establishes groundwork for subsequent investigations intended to broaden the scope of identifying adaptive measures and their integration with LCZs and MUUs. It envisages the creation of an artificial intelligence (AI)-based tool designed to enhance the selection process of the most suitable.