한국지리정보학회지 (Journal of the Korean Association of Geographic Information Studies)

  • 제15권2호
  • /
  • Pages.86-102
  • /
  • 2012
  • /
  • 1226-9719(pISSN)
  • /
  • 2287-6952(eISSN)
한국지리정보학회 (The Korean Association of Geographic Information Studies)
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빈도비 모델과 GIS을 이용한 침수 취약 지역 예측 기법 개발 및 검증

Predictive Flooded Area Susceptibility and Verification Using GIS and Frequency Ratio

  • 이명진 (한국환경정책.평가연구원 국가기후변화적응센터) ;
  • 강정은 (한국환경정책.평가연구원 국가기후변화적응센터)
  • Lee, Moung-Jin (Korea Adaptation Center for Climate Change, Korea Environment Institute) ;
  • Kang, Jung-Eun (Korea Adaptation Center for Climate Change, Korea Environment Institute)
  • 투고 : 2012.04.06
  • 심사 : 2012.06.04
  • 발행 : 2012.06.30
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초록

본 연구에서는 지리정보시스템(GIS)과 빈도비 모델(frequency ratio model)을 이용하여 부산 남구 및 연제구 지역의 침수 지역 예측 기법을 적용하여 취약성도를 작성 및 검증하고자 한다. 침수 피해와 관련된 요인으로는 지질도, 지형도(경사도, 표고, 곡률 및 하천), 토양도(토양 배수, 유효토심 및 토성), 임상도(경급, 영급, 소밀도 및 수종) 및 토지이용(불투수층 및 그린인프라) 등의 자료를 선정하여 GIS 기반의 공간 데이터베이스로 구축하였다. 2009년 160개소의 침수지역 중 50%(80개소)는 침수 관련 항목들간의 상관관계를 분석하는데 활용되었고, 50%(80개소)는 작성된 검증을 위하여 사용하였다. 침수 관련 항목들간의 상관관계는 불투수층 지역에서는 교통지역이 가장 높았으며, 경사도 $11{\sim}15^{\circ}$및 표고 15m 등에서 높았다. 분석된 상관관계를 GIS 중첩분석을 수행하여 침수 취약성도를 작성하였다. 계산된 침수 취약성은 기존 침수 관련 항목들 간의 관계를 정량적으로 설명하고 표현하여 취약성 지수가 높을수록 향후 침수피해가 많은 것을 의미한다. 침수 취약성도는 관련된 재해를 줄이고, 토지이용 및 건설과 같은 도시계획 분야에서 사용될 수 있다.

For predictive flooded area susceptibility mapping, this study applied and verified probability model and the frequency ratio using a geographic information system (GIS) and frequency raio. Flooded areas were identified in the study area of field surveys, For predictive flooded area susceptibility mapping, this study applied and verified probability model and the frequency ratio using a geographic information system (GIS) and frequency raio. Flooded areas were identified in the study area of field surveys, and maps of the topography, geology, landcover and green infrastructure were constructed for a spatial database. The factors that influence flooded areas occurrence, such as slope gradient, slope, aspect and curvature of topography and distance from darinage, were calculated from the topographic database. Lithology and distance from fault were extracted and calculated from the geology database. The frequency ratio coefficient is overlaid for flooded areas susceptibility mapping as each factor's ratings. Then the flooded areas susceptibility map was verified and compared using the existing flooded areas. As the verification results, the frequency ratio model showed 82% in prediction accuracy. The method can be used to reduce hazards associated with flooded areas and to plan land use.

키워드

과제정보

연구 과제번호 : 기후변화 적응형 도시 리뉴얼 전략 수립: 그린인프라의 방재효과 및 적용방안

연구 과제 주관 기관 : 한국환경정책.평가연구원

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  8. Risk Assessment of Heavy Snowfall Considering Climate Change: Focusing on Damage to Roads and Buildings vol.19, pp.2, 2019, https://doi.org/10.9798/kosham.2019.19.2.57
  9. Flood Detection and Susceptibility Mapping Using Sentinel-1 Time Series, Alternating Decision Trees, and Bag-ADTree Models vol.2020, pp.None, 2020, https://doi.org/10.1155/2020/4271376
  10. Seismic Vulnerability Assessment and Mapping of Gyeongju, South Korea Using Frequency Ratio, Decision Tree, and Random Forest vol.12, pp.18, 2012, https://doi.org/10.3390/su12187787