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Scalable machine learning for urban thermal morphology classification: clustering high-resolution microclimate and dynamic mapping of radiant temperature

Crossref DOI link: https://doi.org/10.1007/s43762-026-00278-1

Published Online: 2026-07-22

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Baia, Michele https://orcid.org/0009-0001-6010-5811
Balocco, Carla https://orcid.org/0000-0002-8698-2097
Bagnoli, Franco https://orcid.org/0000-0002-6293-0305
Funding

Funding for this research was provided by:

EU Project, LIFE Energy + LIFE Climate - LIFE23-CCA-IT-LIFE ESCAPOS (EU Project)

EU Project, LIFE Energy + LIFE Climate - LIFE23-CCA-IT-LIFE ESCAPOS (101157553)
License Information

Text and Data Mining valid from 2026-07-22

Version of Record valid from 2026-07-22
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Article History

Received: 8 April 2026

Revised: 22 June 2026

Accepted: 11 July 2026

First Online: 22 July 2026

Declarations

Competing interests: The authors declare no conflicts of interest and that they have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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