Upscaling net ecosystem CO2 exchanges in croplands: The application of integrating object-based image analysis and machine learning approaches

Accurately estimating the net ecosystem exchange of CO2 (NEE) in cropland ecosystems is essential for understanding the impacts of agricultural practices and climate conditions. However, significant uncertainties persist in the estimation of regional cropland NEE due to landscape heterogeneity and v...

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Veröffentlicht in:	The Science of the total environment Jg. 944; S. 173887
Hauptverfasser:	Gao, Dexiang, Yao, Jingyu, Gao, Zhongming, Yuan, Wenping, He, Yingzhe, Wang, Bojun, Li, Lei, Ma, Yulong, Russell, Eric, Pressley, Shelley N., Zou, Xudong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 20.09.2024
Schlagworte:	algorithms carbon dioxide Carbon flux upscaling climate cropland Eddy covariance environment image analysis Machine learning Net ecosystem exchange Object-oriented image analysis phenology prediction soil water temperature Net ecosystem exchange Eddy covariance Carbon flux upscaling Object-oriented image analysis Machine learning
ISSN:	0048-9697, 1879-1026, 1879-1026
Online-Zugang:	Volltext
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