Vol. 16 No. 2 (2025): (Regular Issue in Progress)
Review Article

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

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Nurhasanah Tika
Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia
Nagara Rakyan Paksi
Universitas Indonesia
Bio
Dimyati Muhammad
Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia
Bio
Bibliometric result for country scientific production and collaboration distribution map
DOI: https://doi.org/10.48088/ejg.n.tik.16.2.075.095
Categories

Published 2025-03-24

Keywords

  • Systematic Literature Review,
  • biblometric,
  • tsunami,
  • vulnerability,
  • geographic information system,
  • remote sensing
    • ...More
    Less

How to Cite

Tika, Nurhasanah, Nagara Rakyan Paksi, and Dimyati Muhammad. 2025. “Advancing Tsunami Vulnerability Modelling: A Systematic Review and Bibliometric Analysis of Remote Sensing and GIS Applications”. European Journal of Geography 16 (2):75-95. https://doi.org/10.48088/ejg.n.tik.16.2.075.095.

Copyright (c) 2025 Nurhasanah Tika, Nagara Rakyan Paksi, Dimyati Muhammad

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Received 2024-12-03
Accepted 2025-03-23
Published 2025-03-24

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.

Highlights:

  • Tsunamis cause significant damage to coastal regions, impacting lives and economies.
  • Remote sensing and GIS are essential tools for assessing tsunami vulnerability.
  • Geospatial technologies improve disaster preparedness and coastal resilience strategies.
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