Author(s): Hyeongjoo Lee; Jaehyeong Han; Gunhui Chung
Linked Author(s): JaeHyeong Han, GunHui Chung, HyeongJoo Lee
Keywords: Heavy snow damage climate change vulnerability analysis DPSIR risk grade multiple regression analysis
Abstract: According to the UN's 'World Disaster Report 2000-2019', the number of disasters increased by 1.7 times compared to the previous 20 years, and climate change was diagnosed as the main cause. Heavy snow damage is less frequent than other natural disasters, but the type of heavy snow damage is gradually becoming larger due to climate change. Heavy snow damage in Korea is characterized by local occurrence, and the pattern of heavy snow damage shows different trends by region. Therefore, this study conducted a vulnerability analysis using the DPSIR framework to develop a heavy snow damage risk grade and developed a technology to predict heavy snow damage amount by risk grade that reflects regional characteristics. The risk grades were divided into a total of four (Red zone, Orange zone, Yellow zone, Green zone), and the technology was developed using multiple regression analysis. Finally, the predictive power of the Basic Model developed without vulnerability analysis and the damage prediction technology by risk grade were compared, and it was confirmed that the accuracy of the prediction technology by risk grade that reflects regional characteristics was higher.
Year: 2025