Volume 44 Issue 4
Aug.  2025
Turn off MathJax
Article Contents
XU Chong,GAO Mingxing,XUE Zhiwen,et al. Column Review: Advancements in earthquake and geological disaster mitigation empowered by advanced technologies[J]. Bulletin of Geological Science and Technology,2025,44(4):16-22 doi: 10.19509/j.cnki.dzkq.tb20250004
Citation: XU Chong,GAO Mingxing,XUE Zhiwen,et al. Column Review: Advancements in earthquake and geological disaster mitigation empowered by advanced technologies[J]. Bulletin of Geological Science and Technology,2025,44(4):16-22 doi: 10.19509/j.cnki.dzkq.tb20250004

Column Review: Advancements in earthquake and geological disaster mitigation empowered by advanced technologies

doi: 10.19509/j.cnki.dzkq.tb20250004
More Information
  • Corresponding author: E-mail:xc11111111@126.com
  • Received Date: 26 Jun 2025
  • Accepted Date: 03 Jul 2025
  • Rev Recd Date: 01 Jul 2025
  • Available Online: 10 Jul 2025
  • Significance

    With continuous advances in high technologies such as remote sensing, the Internet of Things, artificial intelligence, big data, cloud computing, and more recently, large language models (LLMs), the field of earthquake and geological disaster research is shifting from traditional paradigms relying on single data sources and empirical models toward integrated systems driven by multi-source data fusion and intelligent decision support.

    Progress

    This article, based on the themed column “Applications of Advanced Technologies in Earthquake and Geological Hazard Research,” reviews recent progress across five key directions: physical simulation modeling, deep learning-based recognition, remote sensing integration, intelligent early warning techniques, and knowledge graph construction. These studies collectively demonstrate how cutting-edge technologies are being applied to hazard monitoring, mechanism analysis, and emergency response.

    Conclusions and Prospects

    On this basis, the article further identifies current technical bottlenecks, including challenges in multimodal data integration, disaster chain modeling, model generalization, and scenario adaptability, and explores the potential role of LLMs in this field, particularly in knowledge extraction, causal inference, and multi-scenario risk assessment.

     

  • loading
  • [1]
    XU C,XU X W,YAO X,et al. Three (nearly) complete inventories of landslides triggered by the May 12,2008 Wenchuan Mw 7.9 earthquake of China and their spatial distribution statistical analysis[J]. Landslides,2014,11(3):441-461. doi: 10.1007/s10346-013-0404-6
    [2]
    XU C. Preparation of earthquake-triggered landslide inventory maps using remote sensing and GIS technologies:Principles and case studies[J]. Geoscience Frontiers,2015,6(6):825-836. doi: 10.1016/j.gsf.2014.03.004
    [3]
    GIROTTO C D,PIADEH F,BKHTIARI V,et al. A critical review of digital technology innovations for early warning of water-related disease outbreaks associated with climatic hazards[J]. International Journal of Disaster Risk Reduction,2024,100:104151. doi: 10.1016/j.ijdrr.2023.104151
    [4]
    KRICHEN M,ABDALZAHER M S,ELWEKEIL M,et al. Managing natural disasters:An analysis of technological advancements,opportunities,and challenges[J]. Internet of Things and Cyber-Physical Systems,2024,4:99-109. doi: 10.1016/j.iotcps.2023.09.002
    [5]
    LIU J L,XU C,ZHAO B B,et al. Deformation slope extraction and influencing factor analysis using LT-1 satellite data:A case study of Chongqing and surrounding areas,China[J]. Remote Sensing,2025,17(1):156. doi: 10.3390/rs17010156
    [6]
    OUELLET S M,DETTMER J,LATO M J,et al. Previously hidden landslide processes revealed using distributed acoustic sensing with nanostrain-rate sensitivity[J]. Nature Communications,2024,15:6239. doi: 10.1038/s41467-024-50604-6
    [7]
    XIE T,ZHANG C C,SHI B,et al. Integrating distributed acoustic sensing and computer vision for real-time seismic location of landslides and rockfalls along linear infrastructure[J]. Landslides,2024,21(8):1941-1959. doi: 10.1007/s10346-024-02268-y
    [8]
    LV J C,ZHANG R,BAO X,et al. Time-series InSAR landslide three-dimensional deformation prediction method considering meteorological time-delay effects[J]. Engineering Geology,2025,350:107986. doi: 10.1016/j.enggeo.2025.107986
    [9]
    LINGARAJ K L,MALGHAN R L,RAO M C K,et al. Adaptive landslide monitoring in wireless sensor networks using FLPSO-based MIP systems[J]. Results in Engineering,2025,25:104329. doi: 10.1016/j.rineng.2025.104329
    [10]
    QI W W,WEI M F,YANG W T,et al. Automatic mapping of landslides by the ResU-net[J]. Remote Sensing,2020,12(15):2487. doi: 10.3390/rs12152487
    [11]
    XUE Z W,XU C,XU X W. Application of ChatGPT in natural disaster prevention and reduction[J]. Natural Hazards Research,2023,3(3):556-562. doi: 10.1016/j.nhres.2023.07.005
    [12]
    XIE C C,GAO H R,HUANG Y D,et al. Leveraging the DeepSeek large model:A framework for AI-assisted disaster prevention,mitigation,and emergency response systems[J]. Earthquake Research Advances,2025:100378.
    [13]
    肖子亢,许冲,李宏,等. 地质灾害物理仿真实验发展现状及趋势分析[J]. 地质科技通报,2025,44(4):23-47.

    XIAO Z K,XU C,LI H,et al. Development status and trend analysis of physical simulation experiments for geological hazards[J]. Bulletin of Geological Science and Technology,2025,44(4):23-47. (in Chinese with English abstract
    [14]
    饶炜博,陈刚,邹崇尧,等. 基于历史样本增强的滑坡智能识别改进算法[J]. 地质科技通报,2025,44(4):48-61.

    RAO W B,CHEN G,ZOU C Y,et al. An improved algorithm for intelligent landslide identification based onhistorical sample enhancement[J]. Bulletin of Geological Science and Technology,2025,44(4):48-61. (in Chinese with English abstract
    [15]
    韦春豪,李为乐,吴章雷,等. 白鹤滩库区活动滑坡识别及形变影响因素分析[J]. 地质科技通报,2025,44(4):62-77.

    WEI C H,LI W L,WU Z L,et al. Identification of Active Landslides and Analysis of Deformation Influencing Factors in the Baihetan Reservoir Area[J]. Bulletin of Geological Science and Technology,2025,44(4):62-77. (in Chinese with English abstract
    [16]
    曹凯,卢渊,庞小龙,等. 基于微震事件频次的采空区沉陷变形智能预警方法[J]. 地质科技通报,2025,44(4):78-89.

    CAO K,LU Y,PANG X L,et al. Intelligent early warning method for subsidence and deformation in goafbased on the frequency of microseismic events[J]. Bulletin of Geological Science and Technology,2025,44(4):78-89. (in Chinese with English abstract
    [17]
    吴麒瑞,田苗,谢忠,等. 融合多模态数据的地震灾害知识图谱 构建及应用[J]. 地质科技通报,2025,44(4):90-106.

    WU Q R,TIAN M,XIE Z,et al. Construction and Application of Earthquake Disaster Knowledge Graph Fusing and Multimodal Data[J]. Bulletin of Geological Science and Technology,2025,44(4):90-106. (in Chinese with English abstract
    [18]
    HUANG Y D,XU C,ZHANG X J,et al. Bibliometric analysis of landslide research based on the WOS database[J]. Natural Hazards Research,2022,2(2):49-61. doi: 10.1016/j.nhres.2022.02.001
    [19]
    HUANG Y D,XU C,ZHANG X J,et al. Research in the field of natural hazards based on bibliometric analysis[J]. Natural Hazards Review,2023,24(2):04023012. doi: 10.1061/NHREFO.NHENG-1739
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article Views(468) PDF Downloads(228) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return