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    • The spatiotemporal dynamics monitoring of forest disturbance in Yunnan Province， China based on trend-cycle characteristic integration

    • “The research team has developed a forest disturbance analysis model that integrates trend decomposition and periodic correction. By extracting two-component features from Landsat satellite NDVI time series and coupling multidimensional constraint mechanisms, the disturbance detection accuracy is 85.41% and the type recognition accuracy is 86.64%, providing data support for forest carbon sink assessment.”
      • role：First author第一作者
      • Affiliation：

        Faculty of Geography, Yunnan Normal University, Kunming 650500, China

      • Email：hls_rs@163.com
      • Introduction：何林蒴，研究方向为植被遥感。E-mail：hls_rs@163.com

      HE Linshuo

      1,
      • Affiliation：

        Faculty of Geography, Yunnan Normal University, Kunming 650500, China

      ZHOU Zetong

      1,
      • Affiliation：

        Faculty of Geography, Yunnan Normal University, Kunming 650500, China

      WANG Jinliang

      1,
      • Affiliation：

        School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China

      WANG Cheng

      2,
      • Affiliation：

        Faculty of Geography, Yunnan Normal University, Kunming 650500, China

      HUANG Xiang

      1,
      • role：Corresponding author通信作者
      • Affiliation：

        Faculty of Geography, Yunnan Normal University, Kunming 650500, China

      • Email：chengfeng_rs@163.com
      • Introduction：程峰，研究方向为资源环境遥感。E-mail：chengfeng_rs@163.com

      CHENG Feng

      1 *
    • Vol. 30, Issue 9, Pages: 2674-2688(2026)  

    • DOI：10.11834/jrs.20265175    

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