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Mapping heatwave vulnerability in Korea
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DOI：10.1007/s11069-017-2951-y.png)
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Due to the inevitable increase in temperatures that are attributable to significant climate variability and notable shifts in climate under increasing greenhouse gases, heat waves are becoming a major natural disaster. They lead to elevating incidences of human mortality, health risks, and damage to the economy, agriculture, and natural ecosystems. As a precautionary foresight to mitigate detrimental impacts of this disaster, a better understanding of regional vulnerability to heat waves is essential. This study has investigated the cumulative role of the social and climatic factors on heatwave-related deaths across the 232 administrative counties in Korea. Correlation and clustering analyses performed on heatwave-related deaths and social and climatic factors indicated that the number of heatwave days, tropical nights, elderly living alone, and agricultural workers had a significant relationship with the number of heatwave-related deaths. In order to demonstrate the practicality of this approach for heatwave analysis, a spatial heatwave vulnerability map was created to identify the distribution of heatwave risk by compositing the four most significant vulnerability factors identified with regression method. Among the several available regression methods that are applied on countable data, this study has utilized zero-inflated Poisson regression because the available data on heatwave-related deaths included many zeros. The heatwave vulnerability map depicted well the actual distribution of heatwave-related deaths, particularly for counties with a large number of heatwave deaths. In light of this evidence, it is postulated that the heatwave vulnerability map can be used as a useful decision-making tool that can help facilitate efficient utilization of various disaster management resources at the national level and also to identify emphatically the heatwave-related risk over spatial scales to aid in the establishment of customized health risk precautionary measures.
Keyword:
Mapping heatwave vulnerability
Zero-inflated Poisson regression analysis
Spatial heatwave risk
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