Three decades of glacial lake research: a bibliometric and visual analysis of glacial lake identification - Liu, Zhengquan; Yang, Zhiquan; He, Na; Wei, Lai; Zhu, Yingyan; Jiao, Wenqi; Wang, Zhengxian; Zhang, Tao; Zhang, Jiantao; Zou, Xiang (Frontiers in Ecology and Evolution, 2023)
As a vital component within glacier systems, the occurrences of glacial lake disasters in high mountain regions have progressively emerged as one of the most destructive natural calamities amid the backdrop of global warming. The swift advancement of glacial lake identification techniques offers a pivotal perspective for forecasting and mitigating the perils of glacial lake outburst disasters. To evaluate the thematic evolution, research focal points, and forthcoming directions within the glacier identification domain, a comprehensive bibliometric analysis was conducted on glacial lake identification-related literature from 1991 to 2023 in the Web of Science Core Collection database. The results are as follows:1) The United States, the United Kingdom, and China stand as principal nations propelling the field's advancement. The Chinese Academy of Sciences demonstrates the highest activity in terms of article publications and international collaborations. 2) Climate change, compilation of glacial lake inventories, methodologies for risk assessment, glacial lake outburst floods, comprehensive disaster management strategies, and hydrodynamic models constitute the domain's research hotspots. It is a typical multidisciplinary field. 3) Persistently high-impact topics over an extended period include "hazard", "Late Pleistocene", "environmental change", "ice sheet", and "lake sediments". Keywords indicating the present cutting-edge research encompass "inventory", "glacial lake outburst flood", "risk", "dynamics", "Tibetan Plateau", "evolution", and "high mountain Asia". This paper delves into the current status and pivotal concerns of glacial lake identification techniques, methodologies, and the This is a provisional file, not the final typeset article scale of identification research themes. Further Research should concentrate on avenues like "recognition methods grounded in machine learning and deep learning", "multisource data fusion datasets", "novel algorithms and technologies adaptable to scale transformation and data expansion", as well as "enhancing spatiotemporal data resolution". This will ultimately enable precise, prolonged, and multiscalar identification of glacial lakes. This study provides valuable guidance and reference for future research in the field of glacial lake identification.