Development of Random Forest Model for Sewer-induced Sinkhole Susceptibility

Joonyoung Kim; Jae Mo Kang; Sung-Ha Baek

doi:10.7843/kgs.2021.37.12.117

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2021 Vol.37, Issue 12 Preview Page

Development of Random Forest Model for Sewer-induced Sinkhole Susceptibility 손상 하수관으로 인한 지반함몰의 위험도 평가를 위한 랜덤 포레스트 모델 개발

31 December 2021. pp. 117-125

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Abstract

The occurrence of ground subsidence and sinkhole in downtown areas, which threatens the safety of citizens, has been frequently reported. Among the various mechanisms of a sinkhole, soil erosion through the damaged part of the sewer pipe was found to be the main cause in Seoul. In this study, a random forest model for predicting the occurrence of sinkholes caused by damaged sewer pipes based on sewage pipe information was trained using the information on the sewage pipe and the locations of the sinkhole occurrence case in Seoul. The random forest model showed excellent performance in the prediction of sinkhole occurrence after the optimization of its hyperparameters. In addition, it was confirmed that the sewage pipe length, elevation above sea level, slope, depth of landfill, and the risk of ground subsidence were affected in the order of sewage pipe information used as input variables. The results of this study are expected to be used as basic data for the preparation of a sinkhole susceptibility map and the establishment of an underground cavity exploration plan and a sewage pipe maintenance plan.

Keywords

Prediction

Random forest

Sewer pipe

Sinkhole

Susceptibility

시민의 안전을 위협하는 지반재해 중 하나인 지반함몰이 최근 도심지에서 빈번하게 보고되고 있다. 다양한 지반함몰 발생 메커니즘 중, 하수관 손상부를 통한 토사 유실이 서울시에서 발생하는 지반함몰의 주요원인으로 나타났다. 본 연구에서는 서울시 하수관 정보와 지반함몰이 발생한 위치 정보를 기반으로 머신러닝 기법 중 하나인 랜덤 포레스트 알고리즘을 이용하여 하수관 정보로부터 손상 하수관으로 유발되는 지반함몰의 발생 여부를 예측하는 모델을 학습하였다. 모델 성능 평가 결과, 본 연구에서 도출한 모델이 지반함몰을 상당히 훌륭하게 예측할 수 있는 것으로 나타났다. 또한, 입력변수로 사용한 하수관 정보 중 하수관 길이, 해발고도, 경사, 매립 심도, 하수관 순서로 지반함몰 발생 위험에 영향을 미치는 것을 확인하였다. 본 연구의 결과는 지반함몰 위험도 지도 작성, 지하공동 탐사 계획 수립 및 하수관 정비 사업 계획 수립의 기초 자료로 활용될 수 있을 것으로 기대된다.

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Information

Publisher :The Korean Geotechnical Society
Publisher(Ko) :한국지반공학회
Journal Title :Journal of the Korean Geotechnical Society
Journal Title(Ko) :한국지반공학회 논문집
Volume : 37
No :12
Pages :117-125
Received Date : 2021-12-07
Revised Date : 2021-12-17
Accepted Date : 2021-12-17
DOI :https://doi.org/10.7843/kgs.2021.37.12.117

Journal of the Korean Geotechnical Society ISSN:1229-2427(Print) 2288-646X(Online) 한국지반공학회 논문집

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