Assessing seasonal building thermal adaptation through the acclimatization distance: a GIS-based machine learning framework

IntroductionEnhancing the capacity of residential buildings for maintaining thermal comfort under changing climate conditions is crucial to reducing energy demand and increasing urban resilience. While extensive research has been conducted on energy efficiency at the building scale, less attention h...

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Hlavní autoři:	Daniel Jato-Espino, Francisco Requena-Crespo, Fabio Capra-Ribeiro, Vanessa Moscardó, Maysel Castillo-García
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Frontiers Media S.A. 2026-04-01
Edice:	Frontiers in Sustainable Cities
Témata:	acclimatization distance building thermal performance climate-adaptive design geographic information system machine learning seasonal asymmetry
On-line přístup:	https://www.frontiersin.org/articles/10.3389/frsc.2026.1771368/full
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