Dayan Munasinghe
A Review of the Disaster Risk Assessment Perspectives
Munasinghe, Dayan; Fernando, Terrance; Keraminiyage, Kaushal; Karunawardena, Asiri
Authors
Prof Terrence Fernando T.Fernando@salford.ac.uk
Professor
Prof Kaushal Keraminiyage K.P.Keraminiyage@salford.ac.uk
Professor
Asiri Karunawardena
Abstract
Researchers have explored different risk assessment approaches from the perspectives of different disciplines to capture urban risks, resulting in many risk assessment frameworks. In these frameworks, the risk environment is analysed using different quantitative and qualitative assessment methods, such as fuzzy set, probability theory, and evidence theory. While each approach has contributed to risk assessment, they suffer from a lack of consensus in defining and measuring the impact of risk in an urban environment.
Therefore, the study aims to conduct a literature survey to consolidate a common set of risk assessment perspectives and approaches for measuring these risks.
A structured review was carried out to achieve the aim of this research. The research question used for conducting the literature review was “What approaches are being used to define and measure the impact of hazard risks in an urban environment?”. The PICO (Population, Intervention, Compression Intervention, and Outcome) method was used to generate the search string for the literature review by considering the keywords in the research question. Initially, 206 research papers were selected through a search strategy, and by applying a screening method, 119 research articles were selected for the detailed review. The Nvivo software was supported for the review purpose; then, a mind map was developed, integrating all the risk assessment perspectives.
Risk assessments were summarised by considering the various researchers’ perspectives. Thirty-four risk perspectives were identified through the literature, and a mind map was developed to understand the connectivity. This mind map was converted into a network diagram, and future requirements of risk perspectives were identified based on the risk assessment network diagram. According to the analysis, risk communication, risk treatment, critical curve, judgment curve, and risk matrix could be identified as future research areas. The risk reduction measuring strategies were identified by considering the feedback loop of the network diagram. Thus, 14 risk reduction strategies could be identified through the analysis.
The risk assessment frameworks focused on holistic approaches, but most research studies did not adequately follow the risk perspectives. Therefore, research gaps were identified in the risk assessment process, and the areas were highlighted as state-of-the-art to conduct future research studies. The feedback loops of the network diagram emphasised the risk reduction strategies, which could be further researched through application to a case study.
Citation
Munasinghe, D., Fernando, T., Keraminiyage, K., & Karunawardena, A. (2023). A Review of the Disaster Risk Assessment Perspectives. In Progress in Landslide Research and Technology, Volume 2 Issue 2, 2023 (323-340). Springer. https://doi.org/10.1007/978-3-031-44296-4_18
Online Publication Date | Dec 29, 2023 |
---|---|
Publication Date | Dec 29, 2023 |
Deposit Date | Mar 25, 2024 |
Publicly Available Date | Apr 3, 2024 |
Publisher | Springer |
Pages | 323-340 |
Series Title | Progress in Landslide Research and Technology ((PLRT)) |
Book Title | Progress in Landslide Research and Technology, Volume 2 Issue 2, 2023 |
ISBN | 9783031442957 |
DOI | https://doi.org/10.1007/978-3-031-44296-4_18 |
Files
Published Version
(65.3 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
You might also like
A-Priori Framework for Community Transformation for Inclusive and Risk-Sensitive Urban Developments
(2022)
Presentation / Conference
Climate financing barriers and strategies : the case of Sri Lanka
(2022)
Journal Article
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search