Machine learning algorithms improve MODIS GPP estimates in United States croplands

Introduction: Machine learning methods combined with satellite imagery have the potential to improve estimates of carbon uptake of terrestrial ecosystems, including croplands. Studying carbon uptake patterns across the U.S. using research networks, like the Long-Term Agroecosystem Research (LTAR) ne...

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Principais autores:	Dorothy Menefee, Trey O. Lee, K. Colton Flynn, Jiquan Chen, Michael Abraha, John Baker, Andy Suyker
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2023-11-01
Colecção:	Frontiers in Remote Sensing
Assuntos:	machine learning gross primary productivity eddy covariance agroecosystems remote sensing
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/frsen.2023.1240895/full
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