S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Civil & Environmental Engineering (건설환경공학부) Theses (Master's Degree_건설환경공학부)
Susceptibility Model for Sinkholes Caused by Damaged Sewer Pipes Based on Logistic Regression
로지스틱 회귀 분석 기반 손상된 하수관에 의해 발생하는 지반함몰 위험도 예측 모델
- 공과대학 건설환경공학부
- Issue Date
- 서울대학교 대학원
- 학위논문 (석사)-- 서울대학교 대학원 : 공과대학 건설환경공학부, 2018. 2. 정충기.
- The occurrence of anthropogenic sinkholes in urban area can cause serious social losses. A damaged and aged sewer pipes beneath the road contribute to occur such a phenomenon. This study used the best subsets regression method to develop a logistic regression model that calculate the susceptibility for sinkholes induced by damaged sewer pipes. The model was developed by analyzing both the sewer pipe network and cases of sinkholes in Seoul. Among numerous sewer pipe characteristics were analyzed as explanatory variables, the length, age, elevation, burial depth, size, slope, and materials of the sewer pipe were found to influence the occurrence of sinkhole. The proposed model reasonably estimated the sinkhole susceptibility in the area studied, with an area value under the receiver operating characteristics curve of 0.753. The proposed methodology will serve as a useful tool that can help local governments choose a cavity inspection regime and prevent sinkholes induced by damaged sewer pipes.