Integrated multi-hazard risk assessment under compound disasters using analytical hierarchy process (AHP)
Understanding multi-hazard risk is crucial for disaster preparedness, as different hazards can interact, amplifying their impacts and requiring integrated mitigation strategies. It frequently experiences multiple natural hazards, including floods, landslides, and fires, which pose recurring threats...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025015543 |
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| Summary: | Understanding multi-hazard risk is crucial for disaster preparedness, as different hazards can interact, amplifying their impacts and requiring integrated mitigation strategies. It frequently experiences multiple natural hazards, including floods, landslides, and fires, which pose recurring threats to communities, infrastructure, and local economies. These hazards pose significant threats to society, including loss of life and property damage. Despite existing mitigation efforts, a comprehensive and integrated risk assessment remains necessary to support disaster resilience planning. This study aims to develop a multi-hazard risk assessment framework by utilizing Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) to assess the vulnerability of buildings in Odiongan, Romblon. A multi-hazard map was created to analyze risk levels by integrating hazard exposure, building vulnerability, and spatial distribution of risks. Given the heterogeneous distribution of structures in Odiongan, a systematic multicriteria approach was applied to quantify risk levels. The study classifies 4043 buildings based on their risk exposure, with 659 categorized as very low risk, 569 as low risk, 1340 as moderate risk, 666 as high risk, and 809 as very high risk. The results indicate spatial variations in hazard susceptibility, with certain barangays exhibiting a higher concentration of high-risk structures. This study contributes to a data-driven multi-hazard risk management strategy, providing scientifically grounded insights for local government units (LGUs), urban planners, and policymakers. The multi-hazard maps can assist in prioritizing mitigation areas, developing structural reinforcement programs, and strengthening community awareness initiatives. Furthermore, this research enhances the understanding of integrated risk assessments. It is a foundational reference for future studies aiming to reduce multi-hazard risks and improve structural resilience in disaster-prone areas. |
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| ISSN: | 2405-8440 |