A Machine Learning Algorithm to Convert Geostationary Satellite LST to Air Temperature Using In Situ Measurements: A Case Study in Rome and High-Resolution Spatio-Temporal UHI Analysis

Air temperature (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>T</mi><mi>a</mi></msub></semantics></math></inline-formula>) measurements are crucial for characterizing phenomena like the urban heat island (UHI), which can create critical condi...

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Auteurs principaux:	Andrea Cecilia, Giampietro Casasanta, Igor Petenko, Stefania Argentini
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2025-01-01
Collection:	Remote Sensing
Sujets:	urban heat island machine learning gradient boosting land surface temperature geostationary satellite air temperature
Accès en ligne:	https://www.mdpi.com/2072-4292/17/3/468
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