基于CiteSpace文献计量的滑坡预测研究可视化分析
Visual Analysis of Landslide Prediction Research Based on CiteSpace Bibliometrics
张克利 1张馨丹 2刘欢1
作者信息
- 1. 北京城建勘测设计研究院有限责任公司,北京 100101
- 2. 北京城建轨道交通建设工程有限公司,北京 101125
- 折叠
摘要
[目的]探讨滑坡预测研究的发展趋势,为滑坡灾害的防灾减灾提供参考.[方法]以Web of Science数据库为文献数据源,利用CiteSpace文献计量学软件分析了1991-2023年以滑坡预测为主题的学术论文,详细阐述其研究现状、热点和趋势.[结果]研究结果表明,滑坡预测研究在世界各国均是研究热点,其中以中国最为显著;该领域研究的关键词聚类中"machine learning"最为显著,这意味着机器学习等新型技术正在被广泛应用于滑坡预测领域.[结论]未来的滑坡预测研究将聚焦技术手段的智能化与自动化、监测范围的全面化与立体化、预测模型的精细化与动态化和滑坡风险评估的综合化等4方面.
Abstract
[Purposes]This paper aims to explore the future development trend of landslide prediction re-search and provide reference for disaster prevention and mitigation of landslide disasters.[Methods]Us-ing the Web of Science database as the literature data source,this study analyzed academic papers on landslide prediction from 1991 to 2023 by CiteSpace bibliometric software,and elaborated on their re-search status,hotspots,and trends in detail.[Findings]The research results indicate that landslide pre-diction research is a hot topic in various countries around the world,with China being the most signifi-cant;in the keyword clustering studied in this field,'machine learning' is the most significant,which means that new technologies such as machine learning are being widely applied in the field of landslide prediction.[Conclusions]Future landslide prediction research will focus on four aspects:the intelli-gence and automation of technical means,the comprehensiveness and three-dimension of monitoring scope,the refinement and dynamics of prediction models,and the integration of landslide risk assess-ment.
关键词
滑坡预测/文献计量/可视化分析/研究进展Key words
landslide prediction/bibliometrics/visual analysis/research progress引用本文复制引用
出版年
2024
NETL
NSTL
万方数据