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13 p, 5.4 MB High-resolution crop yield and water productivity dataset generated using random forest and remote sensing / Cheng, Minghan (Yangzhou University) ; Jiao, Xiyun (Hohai University. College of Agricultural Science and Engineering) ; Shi, Lei (Chinese Academy of Agricultural Sciences) ; Peñuelas, Josep (Centre de Recerca Ecològica i d'Aplicacions Forestals) ; Kumar, Lalit (EastCoast Geospatial Consultants) ; Nie, Chenwei (Yangzhou University) ; Wu, Tianao (Hohai University. College of Agricultural Science and Engineering) ; Liu, Kaihua (Hohai University. College of Hydrology and Water Resources) ; Wu, Wenbin (Chinese Academy of Agricultural Sciences) ; Jin, Xiuliang (Chinese Academy of Agricultural Sciences)
Accurate and high-resolution crop yield and crop water productivity (CWP) datasets are required to understand and predict spatiotemporal variation in agricultural production capacity; however, datasets for maize and wheat, two key staple dryland crops in China, are currently lacking. [...]
2022 - 10.1038/s41597-022-01761-0
Scientific data, Vol. 9 (October 2022) , art. 641  
Detailed record - Creative Commons

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