Remote Sensing Monitoring of Forest and Grassland Carbon Sinks | Views:923Downloads:3550CSCD:2
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    • Mapping forest type and tree species fractions in China’s cold-temperate forests based on synthetically mixed data and random forest regression

      • role:First author第一作者
      • Affiliation:

        College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China

        College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China

      • Email:wangmy1002@gmail.com
      • Introduction:王梦雨,研究方向为森林碳循环监测。E-mail: wangmy1002@gmail.com

      WANG Mengyu

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

        College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China

      • Email:fzhao@ccnu.edu.cn
      • Introduction:赵峰,研究方向为森林生态系统动态变化及碳循环模拟。E-mail: fzhao@ccnu.edu.cn

      ZHAO Feng

      2 * ,
      • Affiliation:

        Insitute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China

        Key Laboratory of Forestry Remote Sensing and Information Technology, National Forestry and Grassland Administration, Beijing 100091, China

      PANG Yong

      34,
      • Affiliation:

        College of Resources & Environment, Huazhong Agricultural University, Wuhan 430070, China

      MENG Ran

      5,
      • Affiliation:

        Insitute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China

        Key Laboratory of Forestry Remote Sensing and Information Technology, National Forestry and Grassland Administration, Beijing 100091, China

      JIA Wen

      34,
      • Affiliation:

        College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China

        Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China

      YUE Chao

      16
    • Vol. 29, Issue 1, Pages: 118-133(2025)  
    • DOI:10.11834/jrs.20233103    

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