Machine Learning to Retrieve Gap-Free Land Surface Temperature from Infrared Atmospheric Sounding Interferometer Observations

Machine Learning to Retrieve Gap-Free Land Surface Temperature from Infrared Atmospheric Sounding Interferometer Observations

Retrieving LST from infrared spectral observations is challenging because it needs separation from emissivity in surface radiation emission, which is feasible only when the state of the surface–atmosphere system is known. Thanks to its high spectral resolution, the Infrared Atmospheric Sounding Inte...

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Bibliographic Details
Main Authors: Fabio Della Rocca, Pamela Pasquariello, Guido Masiello, Carmine Serio, Italia De Feis
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Remote Sensing
Subjects:
land surface temperature
radiative
transfer
IASI
downscaling
machine learning
Online Access:https://www.mdpi.com/2072-4292/17/4/694
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