Categorisation of urban open spaces for heat adaptation: A cluster based approach
In the context of climate change, adapting a city's open spaces to heat waves and extreme heat is crucial for mitigating the Urban Heat Island effect and ensuring the wellbeing of its inhabitants. However, the heat adaptation potential of open spaces varies within a city. This study develops an...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad del País Vasco |
| Repositorio: | Addi. Archivo Digital para la Docencia y la Investigación |
| OAI Identifier: | oai:addi.ehu.eus:10810/70325 |
| Acceso en línea: | http://hdl.handle.net/10810/70325 |
| Access Level: | acceso abierto |
| Palabra clave: | climate change urban categorisation heat wave adaptation clustering built environment |
| Sumario: | In the context of climate change, adapting a city's open spaces to heat waves and extreme heat is crucial for mitigating the Urban Heat Island effect and ensuring the wellbeing of its inhabitants. However, the heat adaptation potential of open spaces varies within a city. This study develops an objective and replicable method to categorise urban areas based on their open spaces' adaptive capacity and improvement potential to heat waves at the micro-scale. This is achieved using a clustering approach, eliminating manual operations, using openly available data, employing indicators suitable for every urban fabric type, and using the urban block as the analysis unit. The validation of the method in the case study of Bilbao (Spain) demonstrates its capacity to obtain meaningful insights regarding open space heat adaptation potential. An analysis of the resulting categories reveals significant open space improvement potential throughout the city and a varying adaptive capacity that depends on urban density. Categories with the lowest adaptive capacity have median open space ratios between 0.35 and 0.65 and median tree cover ratios between 0.07 and 0.15. Those with the highest adaptive capacity present median open space ratios between 0.8 and 1 and median tree cover ratios between 0.05 and 0.25. The method can aid local policymakers in identifying opportunity spots for hosting adaptation solutions and understanding the challenges the city may face in planning adaptation action. The method's replicability enables it to be applied in other cities, contributing to a broader exploration of climate change adaptation potential. |
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