Trends and Developments in the Use of Machine Learning for Disaster Management: A Bibliometric Analysis

Part 1: Emerging Technologies Adoption International audience The frequency of the occurrence of disasters, and the severity of their effects have both been significantly rising over the past few decades across the world. Recognizing the potential of Artificial Intelligence (AI), particularly its subset, Machine Learning (ML), this study delves into its application in disaster management. More specifically, this study adopted the bibliometric analysis methodology to examine the most active authors, countries, and institutions in research related to the use of ML in disaster management and to investigate the trending themes associated with ML use in disaster management. Based on the results, it can be concluded that the citation networks demonstrate the close collaboration between the USA, India, China, and Australia. India had the most articles cited with 1672 citations, despite China having the largest production of research related to the use of ML in disaster management. Furthermore, besides “disaster management” and “machine learning” which were expected to be part of the key drivers in this research area, “remote sensing” also emerged as a trending topic. Based on the thematic analysis of the various articles retrieved in this study, future research must include fourth industrial revolution (4IR) technologies, as they are crucial to disaster management.