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    • FSC-Mask2Former: A forest panoptic segmentation method based on UAV imagery

    • “The visible light and shadow images of unmanned aerial vehicles provide data support for fine scale forest monitoring. Researchers have proposed an end-to-end panoramic segmentation model FSC-Mask2Former, which effectively overcomes the problem of tree species confusion in complex forest scenes through frequency domain texture perception and contrastive learning strategies, providing a low-cost and efficient technical solution for achieving fine mapping of all elements of forests.”
      • role:First author第一作者
      • Affiliation:

        State Key Laboratory of Efficient Production of Forest Resources, College of Forestry, Beijing Forestry University, Beijing 100083, China

        Beijing Key Laboratory of Precision Forestry, College of Forestry, Beijing Forestry University, Beijing 100083, China

        Key Laboratory of Forest Cultivation and Protection, Ministry of Education, Beijing Forestry University, Beijing 100083, China

      • Email:yangzhen2023@bjfu.edu.cn
      • Introduction:杨振,研究方向为森林树种识别。E-mail:yangzhen2023@bjfu.edu.cn

      YANG Zhen

      ,
      • Affiliation:

        State Key Laboratory of Efficient Production of Forest Resources, College of Forestry, Beijing Forestry University, Beijing 100083, China

        Beijing Key Laboratory of Precision Forestry, College of Forestry, Beijing Forestry University, Beijing 100083, China

        Key Laboratory of Forest Cultivation and Protection, Ministry of Education, Beijing Forestry University, Beijing 100083, China

      YAO Zongqi

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

        State Key Laboratory of Efficient Production of Forest Resources, College of Forestry, Beijing Forestry University, Beijing 100083, China

        Beijing Key Laboratory of Precision Forestry, College of Forestry, Beijing Forestry University, Beijing 100083, China

        Key Laboratory of Forest Cultivation and Protection, Ministry of Education, Beijing Forestry University, Beijing 100083, China

      • Email:zhangxl@bjfu.edu.cn
      • Introduction:张晓丽,研究方向为资源环境遥感。E-mail:zhangxl@bjfu.edu.cn

      ZHANG Xiaoli

      *
    • Vol. 30, Issue 9, Pages: 2701-2721(2026)  
    • DOI:10.11834/jrs.20266167    

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