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    • A spatiotemporal prior knowledge-driven method for real-time generation of direct impact knowledge of sudden surface anomalies

    • “The research team proposed a "spatiotemporal prior driven method for generating knowledge directly affected by sudden surface anomalies" and explored the topic of emergency remote sensing intelligent interpretation, providing a solution to the problem of high-resolution image loss before anomalies.”
      • role：First author第一作者
      • Affiliation：

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

      • Email：1615563421@qq.com
      • Introduction：向元柠，研究方向为遥感智能处理及应用。E-mail： 1615563421@qq.com

      XIANG Yuanning

      ,
      • Affiliation：

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

      YANG Kunyang

      ,
      • Affiliation：

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

      WANG Qiao

      ,
      • Affiliation：

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

      SONG Jinling

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

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

      • Email：tanghong@bnu.edu.cn
      • Introduction：唐宏，研究方向为人居环境遥感。E-mail： tanghong@bnu.edu.cn

      TANG Hong

      *
    • Pages: 1-21(2026)  

    • DOI：10.11834/jrs.20266019    

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