China Safety Science Journal ›› 2022, Vol. 32 ›› Issue (7): 172-179.doi: 10.16265/j.cnki.issn1003-3033.2022.07.2766

• Technology and engineering of disaster prevention and mitigation • Previous Articles     Next Articles

Visual analysis of bibliometric research on landslide monitoring in China

CHENG Gang1,2,3(), WANG Zhenxue1, LI Gangqiang4,**(), NI Yufei2, XU Liang2   

  1. 1 School of Computer Science, North China Institute of Science and Technology, Langfang Hebei 065201, China
    2 School of Earth Sciences and Engineering, Nanjing University, Nanjing Jiangsu 210023, China
    3 Nanjing University High-Tech Institute at Suzhou, Suzhou Jiangsu 215123, China
    4 School of Safety Supervision, North China Institute of Science and Technology, Langfang Hebei 065201, China
  • Received:2022-02-24 Revised:2022-05-11 Online:2022-08-12 Published:2023-01-28
  • Contact: LI Gangqiang

Abstract:

In order to reduce the frequency and degree of landslide disasters effectively, this paper made a visual analysis of the bibliometric research of landslide monitoring based on CNKI and Web of Science database. The research progress of landslide monitoring was described in detail from the perspectives of the number of papers, research hotspots, research institutions, researchers, and journal distribution. The VOSviewer software was used to analyze the high-frequency keywords and their correlation degree of landslide monitoring. The research hotspots and development trends were obtained through classification statistics and quantification. The results show that the decrease in the number of landslide disasters is positively correlated with the increase in the amount of research literature. In terms of monitoring technology, Integrated Monitoring System (IMS) and 3S are becoming more and more mature. Multi-method integrated monitoring such as Interferometric Synthetic Aperture Radar (InSAR), Distributed Fiber Optic Sensing (DFOS) and Terrestrial Laser Scanning (TLS) has become the new mainstream. The integrated multi-dimensional intelligent monitoring and early warning cloud platform will become an important direction for landslide disaster prevention and control.

Key words: landslide monitoring, visual analysis, bibliometrics, China national knowledge infrastructure(CNKI)database, Web of Science