Advancing Tsunami Vulnerability Modelling: A Systematic Review and Bibliometric Analysis of Remote Sensing and GIS Applications

Abstract

This study conducts a systematic review and bibliometric analysis of tsunami vulnerability modelling using remote sensing and Geographic Information Systems (GIS) to assess research trends, methodologies, and challenges in disaster risk assessment. Sixty-six articles published between 2014 and 2024 were analyzed from the Scopus database, revealing an increasing reliance on geospatial technologies for tsunami hazard mapping, vulnerability assessment, and risk mitigation. The findings highlight the dominance of GIS-based spatial analysis and numerical modelling techniques, with remote sensing providing critical data for hazard simulations. The study also identifies a growing trend in integrating machine learning with GIS to enhance tsunami risk prediction and improve early warning systems. Despite technological advancements, challenges persist, particularly in ensuring data accessibility, standardizing vulnerability assessment frameworks, and addressing socio-economic disparities in disaster resilience. The review emphasizes the need for interdisciplinary collaboration to develop adaptive and inclusive approaches, particularly in regions with limited technical capacity. Furthermore, multi-hazard vulnerability frameworks are gaining prominence, incorporating tsunami risks alongside coastal hazards such as storm surges and sea-level rise. This study underscores the critical role of remote sensing and GIS in advancing tsunami vulnerability modelling while highlighting existing research gaps. Future research should improve model accuracy, integrate real-time environmental data, and develop innovative solutions to enhance community preparedness and coastal resilience. By synthesizing recent studies and analyzing emerging trends, this paper provides valuable insights for researchers, policymakers, and disaster management practitioners working to mitigate tsunami risks in vulnerable coastal areas.