High-resolution crop yield and water productivity dataset generated using random forest and remote sensing

Affiliations

Minghan Cheng: Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College, Yangzhou University
Xiyun Jiao: College of Agricultural Science and Engineering, Hohai University
Lei Shi: Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture
Josep Penuelas: CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra
Lalit Kumar: EastCoast Geospatial Consultants
Chenwei Nie: Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College, Yangzhou University
Tianao Wu: College of Agricultural Science and Engineering, Hohai University
Kaihua Liu: College of Hydrology and Water Resources, Hohai University
Wenbin Wu: Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences
Xiuliang Jin: Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture

Abstract

Measurement(s) crop yield and crop water productivity Technology Type(s) remote sensing and machine learning