온열질환자 발생가능성의 격자 기반 대시메트릭 매핑

초록

This study predicts the spatial distribution of heat-related illness occurrences at high resolution using a land cover-based dasymetric mapping technique. To address the limitations of conventional administrative unit-based analyses, we combined detailed land cover maps with location-specific heat illness occurrence data to calculate the Heat Illness Occurrence Possibility Index (HIOPI) at the grid level. Hotspot analysis of the grid-level HIOPI values revealed that high-risk areas were closely aligned with the actual patient distributions. By enabling fine-scale spatial analysis beyond administrative boundaries, this methodology effectively identifies heat-vulnerable areas and demonstrates its potential to support more efficient heatwave response policy development and resource allocation.

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