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Smart Agriculture ›› 2023, Vol. 5 ›› Issue (2): 161-171.doi: 10.12133/j.smartag.SA202304013

• Overview Article • Previous Articles    

The Paradigm Theory and Judgment Conditions of Geophysical Parameter Retrieval Based on Artificial Intelligence

MAO Kebiao1,2,3(), ZHANG Chenyang4, SHI Jiancheng5, WANG Xuming2, GUO Zhonghua2, LI Chunshu2, DONG Lixin6, WU Menxin7, SUN Ruijing6, WU Shengli6, JI Dabin3, JIANG Lingmei8, ZHAO Tianjie3, QIU Yubao3, DU Yongming3, XU Tongren8   

  1. 1.State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    2.School of Physics and Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, China
    3.State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100094, China
    4.College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
    5.National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
    6.National Satellite Meteorological Center, Beijing 100081, China
    7.National Meteorological Center, Beijing 100101, China
    8.Department of Geographical Science, Beijing Normal University, Beijing 100875, China
  • Received:2023-04-24 Online:2023-06-30

Key words: artificial intelligence, deep learning, retrieval paradigm, physical logic derivation, explainable, agrometeorological remote sensing

CLC Number: