Integrating Coastal Vulnerability Index (CVI), remote sensing and GIS for tsunami vulnerability assessment in rural Malaysian communities
The unexpected occurrence of tsunamis in various countries has highlighted their devastating impact on coastal communities. However, detailed assessments of physical vulnerability at the village level, particularly in developing countries, are still lacking. This research aimed to evaluate the level...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2025
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| Online Access: | http://journalarticle.ukm.my/26366/1/84617-298938-1-PB%20-.pdf http://journalarticle.ukm.my/26366/ http://ejournal.ukm.my/gmjss/index |
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| Summary: | The unexpected occurrence of tsunamis in various countries has highlighted their devastating impact on coastal communities. However, detailed assessments of physical vulnerability at the village level, particularly in developing countries, are still lacking. This research aimed to evaluate the level of physical vulnerability to tsunamis by combining the Coastal Vulnerability Index (CVI) with remote sensing and Geographic Information System (GIS) approaches in 12 coastal villages in Kuala Muda, Kedah, based on damage history and individual building characteristics. The results revealed that Kampung Kuala Muda experienced the highest historical damage, with a total of 381 buildings evaluated. About 97 buildings were classified as high vulnerability, 156 as moderate vulnerability and only 44 were in the very low vulnerability category. Overall, villages with a history of moderate to very high damage, such as Kampung Paya and Kampung Masjid, predominantly had moderately vulnerable buildings. This underscores the significance of geographical factors like elevation, proximity and slope in determining vulnerability levels. Furthermore, statistical analysis using multinomial logistic regression on five physical indicators such as elevation, inundation, land use, slope and proximity. The result indicated that slope was the most reliable factor influencing vulnerability. Inundation and elevation followed as significant contributors for high vulnerability, with a p-value of less than 0.05. Additionally, the distance factor demonstrated a significant negative effect, suggesting that locations farther away from major geographic features were at a lower risk. The findings of this research emphasize the need for mitigation strategies tailored to the vulnerability profile of each village, including strengthening building structures. |
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