건축물 정보를 활용한 도시침수 취약성 진단방법 개발

Abstract

Unusual meteorological phenomena in urban areas are causes of life loss and economic damage. Flooding is the major cause of large economic damage among natural disasters that occurs in cities. Especially, localized torrential rains in urban areas cause substantial economic damage in only a short time. Although similar torrential rain falls occur in both the city and nature, the occurrence patterns for flooding are very different. Urbanization is one reason for flooding to exhibit different characteristics, which we refer to as urban characteristics. However, the vulnerabilities of flooding in urban areas to do urbanization are unclear. Thus, it is necessary to analyze and perform a vulnerability diagnosis of the characteristics of different areas and buildings that are repeatedly damaged by flooding. This study identified vulnerabilities using a modified spatial regression model (OLS) using big data for buildings in 2012 in Seoul, which was repeatedly flooded by heavy rains of more than 50 mm/hour since 2000. In addition, the vulnerability diagnosis model was applied to individual parcels containing buildings in Seoul in order to spatially derive and verify the probability distribution of buildings vulnerable to urban flooding.