Deep learning estimation of northern hemisphere soil freeze-thaw dynamics using satellite multi-frequency microwave brightness temperature observations

Deep learning estimation of northern hemisphere soil freeze-thaw dynamics using satellite multi-frequency microwave brightness temperature observations

Satellite microwave sensors are well suited for monitoring landscape freeze-thaw (FT) transitions owing to the strong brightness temperature (TB) or backscatter response to changes in liquid water abundance between predominantly frozen and thawed conditions. The FT retrieval is also a sensitive clim...

Descrizione completa

Dettagli Bibliografici
Autori principali: Kellen Donahue, John S. Kimball, Jinyang Du, Fredrick Bunt, Andreas Colliander, Mahta Moghaddam, Jesse Johnson, Youngwook Kim, Michael A. Rawlins
Natura: Articolo
Lingua:English
Pubblicazione: Frontiers Media S.A. 2023-11-01
Serie:Frontiers in Big Data
Soggetti:
soil freeze-thaw
microwave
SMAP
AMSR
machine learning
neural network
Accesso online:https://www.frontiersin.org/articles/10.3389/fdata.2023.1243559/full

Accesso online

https://www.frontiersin.org/articles/10.3389/fdata.2023.1243559/full

Documenti analoghi