Explaining Street-Level Thermal Variability Through Semantic Segmentation and Explainable AI: Toward Climate-Responsive Building and Urban Design

Understanding outdoor thermal environments at fine spatial scales is essential for developing climate-responsive urban and building design strategies. This study investigates the determinants of local air temperature deviations in Seoul, Korea, using high-resolution in situ sensor data integrated wi...

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Detalhes bibliográficos

Principais autores:	Yuseok Lee, Minjun Kim, Eunkyo Seo
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2025-12-01
Colecção:	Atmosphere
Assuntos:	thermal environment semantic segmentation explainable artificial intelligence (XAI) climate-responsive design
Acesso em linha:	https://www.mdpi.com/2073-4433/16/12/1413
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