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    • Intelligent modeling of surface anomaly trends driven by grid-based dynamics simulation： theoretical methods and practical applications

    • “In response to the demand for early warning of sudden surface abnormal events, the research team has established a grid dynamics intelligent modeling framework of "ground training satellite inference". By using a universal grid dynamics model across solid liquid gas phases, a physically consistent dataset is generated, and a lightweight BiLSTM CNN spatiotemporal fusion network is designed for satellite deployment, providing technical support for real-time in orbit early warning of surface anomalies.”
      • role：First author第一作者
      • Affiliation：

        Faculty of Geographical Science/State Key Laboratory of Remote Sensing Science and Digital Earth, Beijing Normal University, Beijing 100875, China

      • Email：202421051242@mail.bnu.edu.cn
      • Introduction：卜令琛，研究方向为辐射反演与预报、地表异常趋势模拟。E-mail： 202421051242@mail.bnu.edu.cn

      BU Lingchen

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

        Faculty of Geographical Science/State Key Laboratory of Remote Sensing Science and Digital Earth, Beijing Normal University, Beijing 100875, China

      • Email：xtngzhang@bnu.edu.cn
      • Introduction：张晓通，研究方向为地表辐射收支与能量平衡。E-mail： xtngzhang@bnu.edu.cn

      ZHANG Xiaotong

      1 * ,
      • Affiliation：

        Faculty of Geographical Science/Frontier Interdisciplinary Institute of Satellite Applications, Beijing Normal University, Beijing 100875, China

      ZHAO Wenzhi

      2,
      • Affiliation：

        Faculty of Geographical Science/State Key Laboratory of Remote Sensing Science and Digital Earth, Beijing Normal University, Beijing 100875, China

      JIA Run

      1,
      • Affiliation：

        Faculty of Geographical Science/State Key Laboratory of Remote Sensing Science and Digital Earth, Beijing Normal University, Beijing 100875, China

      DUAN Yanjun

      1,
      • Affiliation：

        Faculty of Geographical Science/State Key Laboratory of Remote Sensing Science and Digital Earth, Beijing Normal University, Beijing 100875, China

      LV Lingfeng

      1,
      • Affiliation：

        Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

      TANG Ping

      3,
      • Affiliation：

        Faculty of Geographical Science/Frontier Interdisciplinary Institute of Satellite Applications, Beijing Normal University, Beijing 100875, China

      WANG Qiao

      2
    • Pages: 1-23(2026)  

    • DOI：10.11834/jrs.20266096    

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