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)

Data:	2022
Resum:	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. In this study, we generated and evaluated a long-term data series, at 1-km resolution of crop yield and CWP for maize and wheat across China, based on the multiple remotely sensed indicators and random forest algorithm. Results showed that MOD16 products are an accurate alternative to eddy covariance flux tower data to describe crop evapotranspiration (maize and wheat RMSE: 4. 42 and 3. 81 mm/8d, respectively) and the proposed yield estimation model showed accuracy at local (maize and wheat rRMSE: 26. 81 and 21. 80%, respectively) and regional (maize and wheat rRMSE: 15. 36 and 17. 17%, respectively) scales. Our analyses, which showed spatiotemporal patterns of maize and wheat yields and CWP across China, can be used to optimize agricultural production strategies in the context of maintaining food security.
Ajuts:	Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-1005 Agència de Gestió d'Ajuts Universitaris i de Recerca 2020/PANDE-00117 Agencia Estatal de Investigación CGL2016-79835-P
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Hydrology ; Agroecology
Publicat a:	Scientific data, Vol. 9 (October 2022) , art. 641, ISSN 2052-4463

DOI: 10.1038/s41597-022-01761-0
PMID: 36271097

13 p, 5.4 MB

El registre apareix a les col·leccions:
Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències > CREAF (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Articles > Articles de recerca
Articles > Articles publicats