ISSN 1003-8035 CN 11-2852/P
    辜超颖,王新刚. 基于CiteSpace可视化分析的滑坡滑带土研究现状与发展趋势[J]. 中国地质灾害与防治学报,2024,35(0): 1-18. DOI: 10.16031/j.cnki.issn.1003-8035.2022.0000-00
    引用本文: 辜超颖,王新刚. 基于CiteSpace可视化分析的滑坡滑带土研究现状与发展趋势[J]. 中国地质灾害与防治学报,2024,35(0): 1-18. DOI: 10.16031/j.cnki.issn.1003-8035.2022.0000-00
    GU Chaoying,WANG Xingang. Research status and development trend of landslide slip zone soil based on CiteSpace visual analysis[J]. The Chinese Journal of Geological Hazard and Control,2024,35(0): 1-18. DOI: 10.16031/j.cnki.issn.1003-8035.2022.0000-00
    Citation: GU Chaoying,WANG Xingang. Research status and development trend of landslide slip zone soil based on CiteSpace visual analysis[J]. The Chinese Journal of Geological Hazard and Control,2024,35(0): 1-18. DOI: 10.16031/j.cnki.issn.1003-8035.2022.0000-00

    基于CiteSpace可视化分析的滑坡滑带土研究现状与发展趋势

    Research status and development trend of landslide slip zone soil based on CiteSpace visual analysis

    • 摘要: 我国是世界上滑坡灾害频发的国家之一,对滑坡的研究一直是防灾减灾的重点。滑带土是滑坡的重要组成部分,对滑带土展开研究不仅有助于深化对滑坡机理的认识,也可为预测滑坡的发生提供有力的支撑和依据。本文首先利用CiteSpace软件对我国近十二年来的滑坡滑带土相关研究进行关键词的图谱分析,归纳了近年来有关滑坡滑带土的主要研究方向;然后重点从滑带土的力学特性以及其在滑带演化过程中起到的关键作用进行文献梳理分析,最后对未来滑坡滑带土研究可能遇到的机遇与挑战进行了展望,提出了从滑坡的预警预报和韧性防控角度出发,结合多学科交叉方法,通过大数据挖掘、人工智能等新技术,对滑坡滑带土进行多尺度(巨-宏-细-微)、全方位、多时序的科学研究将是未来的主要方向。

       

      Abstract: China ranks among the nations globally that are prone to frequent landslide disasters. The investigation and research of landslide has always been key focuses of disaster prevention and mitigation. Slide zone soil is a crucial component of landslides. Studying slip zone soils not only deepens the understanding of landslide mechanisms but also provides strong support for predicting landslide occurrences. This paper uses citespace software to analyze keywords and graphs of landslide soil in recent 12 years, summarizing the main research directions in recent years. It then reviews and analyzes the mechanical characteristics of slip zone soils and their key role in the evolution of slip zones. Finally, the paper explores the opportunities and challenges that may be encountered in the study of slip zone soil in future, proposing that from the perspectives of landslide early warning and resilience control, combining multidisciplinary methods and leveraging new technologies such as big data mining and artificial intelligence for multi-scale (macro-micro-nano), comprehensive, and multi-temporal scientific research on landslide slip zone soils will be the main direction in the future.

       

    /

    返回文章
    返回