Abstract

The global climate is under threat from increasing extreme heat, evidenced by rising temperatures and a surge in hot days. Heat waves are intensifying worldwide, impacting cities and residents, as demonstrated by the record-breaking heat experienced in the UK in 2022, which resulted in over 4500 deaths. Urban heat islands (UHIs) exacerbate these heat waves, making city residents more vulnerable to heat-related deaths. UHIs occur when temperatures in urban areas exceed those in surrounding rural areas due to the heat-absorbing properties of urban structures. Implementing mitigation strategies, such as green infrastructure, is crucial for enhancing urban resilience and reducing vulnerability to UHIs.Effectively addressing UHIs requires a systematic approach, including developing risk maps to prioritise areas for UHI mitigation strategies. Using remote sensing, GIS, and SPSS correlational analysis, the research aims to develop and assess a Heat Risk Index (HRI). This index integrates UHI spatial intensity, current green cover, and population density at the district level to develop the risk index. This study stands out for its novel approach to developing the HRI, focusing on the localised impact of the UHI in Manchester City, identifying high-risk heat-vulnerable districts, and prioritising implementing effective UHI mitigation strategies.The findings highlight the importance of this approach, revealing that approximately 30 % of Manchester City is affected by UHI effects, with areas near the city centre, characterised by higher population density and reduced green cover, being particularly vulnerable. Furthermore, the study suggests that applying HRIs at a more localised level, such as the neighbourhood level rather than the district level, would provide more relevant and targeted insights for mitigating UHI. A more localised index would offer tailored insights into the unique conditions of each neighbourhood within the districts, enabling more effective mitigation strategies. The HRI developed in this paper serves as a test for a more nuanced and comprehensive index, considering additional variables related to population vulnerability and city urban structure.

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