This study quantitatively analyzed the spatial characteristics and principal influencing factors of wildfire vulnerability in Gangneung, Gangwon Special Self-Governing Province, and evaluated the statistical significance of these factors by comparing them with actual wildfire occurrences. The analysis involved generating a 100-meter grid across the Gangneung area and constructing a GIS-based database encompassing 13 variables, including forest, topographical, socio-demographic, and infrastructure elements. All variables were normalized using the Min-Max method prior to analysis, and relationships and interactions between the variables and wildfire occurrences were assessed through Pearson correlation analysis, independent samples t-test, and chi-square test. The results revealed that topographic factors such as slope, elevation, and south-facing aspect, as well as forest type factors like coniferous forest and non-forest areas, were closely associated with wildfire occurrence. Areas adjacent to residential zones and agricultural areas exhibited heightened wildfire risk. Moreover, wildfire response infrastructure, including fire hydrant and civil defense shelter facilities, was found to have low density in areas where wildfires actually occurred, indicating structural vulnerability. Case analysis in Gangneung further showed that approximately 91% of wildfires over the past decade were attributed to anthropogenic causes, highlighting the need for wildfire response strategies in densely populated and forest-adjacent areas. This research provides a spatially explicit foundation for the development of region-specific and science-based wildfire response strategies through the assessment of spatial wildfire vulnerability factors.
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Abstract Introduction Materials and Methods Study site Data Method Selection of wildfire susceptibility factors Correlation analysis among wildfire susceptibility factors Significance testing based on wildfire occurrence locations Results and Discussion Correlation analysis among wildfire susceptibility factors Statistical validation based on wildfire occurrence locations Conclusion Acknowledgements References