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    • A relationship-mapping-driven method for instantaneous knowledge generation on multi-dimensional indirect impacts of earth surface anomalies

    • “Remote sensing technology can quickly identify direct physical damage caused by surface anomalies, but it is still difficult to perceive and quantify the secondary and chain indirect effects caused by such damage in real time. This article introduces its research progress in the field of disaster indirect impact assessment. The research team has established an indirect impact knowledge generation framework that integrates multi-source remote sensing proxy variables and causal relationship mapping, providing a solution to the problem of quantifying the indirect impact of surface anomaly events.”
      • role:First author第一作者
      • Affiliation:

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

        State Key Laboratory of Remote Sensing and Digital Earth, Beijing Normal University, Beijing 100875, China

      • Email:zhouxy017@mail.bnu.edu.cn
      • Introduction:周笑语,研究方向为农业遥感。E-mail: zhouxy017@mail.bnu.edu.cn

      ZHOU Xiaoyu

      12,
      • Affiliation:

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

        State Key Laboratory of Remote Sensing and Digital Earth, Beijing Normal University, Beijing 100875, China

      ZU Zhenyi

      12,
      • Affiliation:

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

        State Key Laboratory of Remote Sensing and Digital Earth, Beijing Normal University, Beijing 100875, China

      REN Jiahui

      12,
      • Affiliation:

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

        State Key Laboratory of Remote Sensing and Digital Earth, Beijing Normal University, Beijing 100875, China

      DU Yaoyao

      12,
      • Affiliation:

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

        State Key Laboratory of Remote Sensing and Digital Earth, Beijing Normal University, Beijing 100875, China

      YANG Kunyang

      12,
      • Affiliation:

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

        Advanced Interdisciplinary Institute of Satellite Applications, Beijing Normal University, Beijing 100875, China

      WANG Qiao

      13,
      • Affiliation:

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

      TANG Ping

      4,
      • Affiliation:

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

        State Key Laboratory of Remote Sensing and Digital Earth, Beijing Normal University, Beijing 100875, China

      TANG Hong

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

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

        State Key Laboratory of Remote Sensing and Digital Earth, Beijing Normal University, Beijing 100875, China

      • Email:songjl@bnu.edu.cn
      • Introduction:宋金玲,研究方向为植被遥感。E-mail: songjl@bnu.edu.cn

      SONG Jinling

      12 *
    • Pages: 1-15(2026)  
    • DOI:10.11834/jrs.20266015    

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