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2020 Vol.30, Issue 4 Preview Page

Research Article

Research on the Production of Risk Maps on Cut Slope Using Weather Information and Adaboost Model

기상정보와 Adaboost 모델을 이용한 깎기비탈면 위험도 지도 개발 연구

Yonghoon Woo1
,
Seung-Hyun Kim2*
,
Jin uk Kim2
,
GwangHae Park3
우 용훈1
,
김 승현2*
,
김 진욱2
,
박 광해3
1Research Specialist, Korea Institute of Civil Engineering and Building Technology
2Research Fellow, Korea Institute of Civil Engineering and Building Technology
3Researcher, Openmate
1한국건설기술연구원 전임연구원
2한국건설기술연구원 연구위원
3(주)오픈메이트 연구원
*Corresponding Author
31 December 2020. pp. 663-671
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Abstract

Recently, there have been many natural disasters in Korea, not only in forest areas but also in urban areas, and the national requirements for them are increasing. In particular, there is no pre-disaster information system that can systematically manage the collapse of the slope of the national highway. In this study, big data analysis was conducted on the factors causing slope collapse based on the detailed investigation report on the slope collapse of national roads in Gangwon-do and Gyeongsang-do areas managed by the Cut Slope Management System (CSMS) and the basic survey of slope failures. Based on the analysis results, a slope collapse risk prediction model was established through Adaboost, a classification-based machine learning model, reflecting the collapse slope location and weather information. It also developed a visualization map for the risk of slope collapse, which is a visualization program, to show that it can be used for preemptive disaster prevention measures by identifying the risk of slope due to changes in weather conditions.

Keywords
cut slope management system
big data analysis
collapse risk model
GIS map

최근 국내에서는 산림지역 뿐만 아니라 대도시지역에서도 자연재해가 많이 발생하고 있으며, 이에 대한 국가적인 요구사항은 증가하고 있다. 특히 국도 비탈면 붕괴에 대하여 체계적으로 관리할 수 있는 사전 재해정보 시스템은 전무한 실정이다. 본 연구에서는 CSMS(Cut Slope Management System)에서 관리하는 강원도와 경상도 지역의 국도 비탈면 붕괴 정밀조사 보고서와 비탈면 기초조사를 토대로 비탈면 붕괴 유발 인자에 대한 빅데이터 분석을 실시하였다. 분석 결과를 바탕으로 붕괴 비탈면 위치와 기상정보를 반영하여 분류 기반 머신러닝 모형인 Adaboost를 통한 비탈면 붕괴 위험도 예측모형을 구축하였다. 또한 시각화 프로그램인 비탈면 붕괴 위험도 시각화 지도를 개발하여 기상여건 변화에 따른 비탈면 위험도 파악을 통한 선제적 재해재난 예방대책에 활용할 수 있음을 보여주고 있다.

키워드
도로비탈면유지관리시스템
빅데이터 분석
위험도 모형
시각화 지도
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Information
  • Publisher :Korean Society of Engineering Geology
  • Publisher(Ko) :대한지질공학회
  • Journal Title :The Journal of Engineering Geology
  • Journal Title(Ko) :지질공학
  • Volume : 30
  • No :4
  • Pages :663-671
  • Received Date : 2020-12-02
  • Revised Date : 2020-12-10
  • Accepted Date : 2020-12-10
  • DOI :https://doi.org/10.9720/kseg.2020.4.663
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