A Quantitative Morphological Method for Mapping Local Climate Types

• Autor(a) principal: Maiullari, Daniela
• Data de Publicação: 2021
• Outros Autores: Pijpers-van Esch, Marjolein, Timmeren, Arjan van
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.17645/up.v6i3.4223
• topic: data-driven classification; microclimate; typologies; urban morphology

Morphological characteristics of cities significantly influence urban heat island intensities and thermal responses to heat waves. Form attributes such as density, compactness, and vegetation cover are commonly used to analyse the impact of urban morphology on overheating processes. However, the use of abstract large-scale classifications hinders a full understanding of the thermal trade-off between single buildings and their immediate surrounding microclimate. Without analytical tools able to capture the complexity of cities with a high resolution, the microspatial dimension of urban climate phenomena cannot be properly addressed. Therefore, this study develops a new method for numerical identification of types, based on geometrical characteristics of buildings and climate-related form attributes of their surroundings in a 25m and 50m radius. The method, applied to the city of Rotterdam, combines quantitative descriptors of urban form, mapping GIS procedures, and clustering techniques. The resulting typo-morphological classification is assessed by modelling temperature, wind, and humidity during a hot summer period, in ENVI-met. Significant correlations are found between the morphotypes’ characteristics and local climate phenomena, highlighting the differences in performative potential between the classified urban patterns. The study suggests that the method can be used to provide insight into the systemic relations between buildings, their context, and the risk of overheating in different urban settings. Finally, the study highlights the relevance of advanced mapping and modelling tools to inform spatial planning and mitigation strategies to reduce the risk of urban overheating.