Research progress and trend analysis of geological disaster chains based on bibliometrics

In the context of intensifying global climate change, the escalating threat posed by geological disaster chains has become increasingly severe. However, there remains a lack of a comprehensive and systematic quantitative review of the development of this research field. Therefore, a thorough synthesis of existing literature is imperative to elucidate the current state of knowledge and to clarify the research landscape surrounding these emerging and complex challenges under the new circumstances.

Utilizing bibliometric methodologies, this study analyzes 784 relevant publications indexed in the Web of Science core collection from 1989 to 2024. It constructs a four-dimensional analytical framework that systematically examines publication trends, collaborative networks among countries and institutions, the influence of academic journals, and the evolution of research themes.

The principal findings are summarized as follows. ① The evolution of research exhibits a distinct three-phase trajectory: an initial phase (1989–2000), a development phase (2001–2012), and a rapid growth phase (2013–2024). This progression is driven by a combination of technology empowerment and case-based validation. Major disaster events provide critical empirical scenarios, while breakthroughs in observational and predictive technologies, such as light detection and ranging (LiDAR), interferometric synthetic aperture radar (InSAR), and artificial intelligence (AI), fundamentally shape the depth, scope, and timing of research development. ② China leads the field with 449 publications, which is approximately nine times the output of the second-ranked United States. The Chinese Academy of Sciences serves as the core and most productive institution. International collaboration has formed a multi-centered network, mainly involving China, the United States, and the United Kingdom. ③ Landslides, Natural Hazards, and Engineering Geology are the most influential core journals in this field, as evidenced by metrics such as the h-index and citation impact. ④ A profound paradigm shift is observed: from single-hazard analysis to multi-hazard couplings, from static susceptibility assessments to dynamic process simulations of chain evolution, and from empirical description to integrated “data-driven + physics-constrained” intelligent prediction modelling. Looking forward, future research endeavors should prioritize two key directions. First, methodological and technological innovations are needed, including the development of hybrid intelligent systems that integrate data-driven approaches with physical mechanisms, integrated “full-chain” observation systems combining remote sensing and ground-based sensors, and digital twin platforms for scenario simulation and risk projection. Second, increased attention should be directed towards the mechanisms and risk assessment of region-specific typical disaster chains under different triggering contexts, such as long-term post-seismic chains (earthquake−landslide clusters−river damming−outburst floods−debris flows), disaster chains in alpine/permafrost regions (freeze-thaw cycles−thaw settlement/thermal erosion slumps−debris flows/outburst floods), interactions between wildfires and subsequent geological hazards (forest fire−soil hydrophobicity−erosion−shallow landslides−debris flows), chains in karst and dissolution-prone areas (collapse−ground fissures−landslides/subsidence−water contamination), and chains induced by reservoir operations or engineering activities (water level fluctuation−bank slope instability−surge waves−secondary disasters). This study systematically reveals the developmental trajectory and paradigm shift in geological disaster chains. The insights derived from this study provide a robust empirical basis for better understanding the development of the field and offer strategic guidance for future research priorities and international collaborative initiatives.