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    • An approach to estimate forest LAI with high resolution based on prior knowledge of model parameters

      • role:First author第一作者
      • Affiliation:

        State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China

        Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

      • Email:201621170031@mail.bnu.edu.cn
      • Introduction:张静宇,1993年生,女,硕士研究生,研究方向为定量遥感。E-mail: 201621170031@mail.bnu.edu.cn

      ZHANG Jingyu

      12,
      • role:Corresponding author通信作者
      • Affiliation:

        State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China

        Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

      • Email:wangjd@bnu.edu.cn
      • Introduction:王锦地,1955年生,女,教授,研究方向为遥感机理和应用。E-mail: wangjd@bnu.edu.cn

      WANG Jindi

      12 * ,
      • Affiliation:

        Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

      SHI Yuechan

      3
    • Vol. 24, Issue 11, Pages: 1342-1352(2020)  
    • DOI:10.11834/jrs.20208400    

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Related Institution

State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University
Beijing Engineering Research Center for Global Land Remote Sensing Products, Beijing Normal University
Aerospace Information Research Institute, Chinese Academy of Sciences
School of Geography,Beijing Normal University
State Key Laboratory of Remote Sensing Science,Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications of Chinese Academy of Sciences