Rapid determination of leaf water content for monitoring waterlogging in winter wheat based on hyperspectral parametersOACSCDCSTPCD
Rapid determination of leaf water content for monitoring waterlogging in winter wheat based on hyperspectral parameters
YANG Fei-fei;LIU Tao;WANG Qi-yuan;DU Ming-zhu;YANG Tian-le;LIU Da-zhong;LI Shi-juan;LIU Sheng-ping
Key Laboratory of Agri-information Service Technology, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.ChinaJiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Agricultural College, Yangzhou University, Yangzhou 225009, P.R.ChinaCollege of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing 100083, P.R.ChinaKey Laboratory of Agri-information Service Technology, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.ChinaJiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Agricultural College, Yangzhou University, Yangzhou 225009, P.R.ChinaKey Laboratory of Agri-information Service Technology, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.ChinaKey Laboratory of Agri-information Service Technology, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.ChinaKey Laboratory of Agri-information Service Technology, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China
winter wheathyperspectral remote sensingleaf water contentnew vegetation indexBP neural network
winter wheathyperspectral remote sensingleaf water contentnew vegetation indexBP neural network
《农业科学学报（英文）》 2021 (10)
2613-2626,14
This work was supported by the National Key Research and Development Program of China(2016YFD0200600,2016YFD0200601),the Key Research and Development Program of Hebei Province,China(19227407D)the Central Public-interest Scientific Institution Basal Research Fund(JBYW-AII-2020-29,JBYW-AII-2020-30)and the Technology Innovation Project Fund of Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2020-AII).
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