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

The Korean Association of Geographic Information Studies (한국지리정보학회)
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Predictive Flooded Area Susceptibility and Verification Using GIS and Frequency Ratio

빈도비 모델과 GIS을 이용한 침수 취약 지역 예측 기법 개발 및 검증

  • Lee, Moung-Jin (Korea Adaptation Center for Climate Change, Korea Environment Institute) ;
  • Kang, Jung-Eun (Korea Adaptation Center for Climate Change, Korea Environment Institute)
  • 이명진 (한국환경정책.평가연구원 국가기후변화적응센터) ;
  • 강정은 (한국환경정책.평가연구원 국가기후변화적응센터)
  • Received : 2012.04.06
  • Accepted : 2012.06.04
  • Published : 2012.06.30
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Abstract

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.

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.

Keywords

Acknowledgement

Grant : 기후변화 적응형 도시 리뉴얼 전략 수립: 그린인프라의 방재효과 및 적용방안

Supported by : 한국환경정책.평가연구원

References

  1. 강정은, 이명진, 구유성, 조광우, 이재욱. 2011. 기후변화 적응형 도시 리뉴얼 전략수립: 그린인프라의 방재효과 및 적용방안. 한국환경정책평가연구원. 218쪽.
  2. 김현주. 2010. 방재를 고려한 도시계획. 방재 연구 12:15-24.
  3. 녹색성장위원회, 기상청. 2010. 2010 이상기후 특별보고서. 기상청. 84쪽.
  4. 박은진, 강규이, 이현정. 2007. 물순환을 고려한 도시녹지 기능제고 방안. 경기개발연구원 기본연구 11:3-9.
  5. 배덕효, 이종태. 2007. 중량천 도시홍수 시험 유역의 운영과 활용. 물과 미래 40(6):54-61.
  6. 백경혜, 이명진, 강병진. GIS를 활용한 KMA-RCM의 규모 상세화 기법 개발 및 검증. 한국지리정보학회지 14:136-149.
  7. 소방방재청, 서울시정개발연구원, 서경대학교. 2006. 자연재해피해저감기술개발-통합내배수침수방어기술개발.
  8. 손태석, 강동호, 장종경, 신현석. 2010. SWMM을 이용한 도시지역 내수침수 취약성 평가. 한국방재학회논문집 10(4):105-17.
  9. 안태진. 2010. 재난환경변화에 따른 도시방재 패러다임 변화. 방재연구 11:2-5.
  10. 오현주. 2010. GIS와 인공신경망을 이용한 금-은 광물 부존적지 선정 및 검증. 한국지리정보학회지13(3):1-13.
  11. 이명진, 이정호. 2011. GIS를 이용한 기후변화 연동 지하수 함양량 산정 모델 개발 및 검증. 한국지리정보학회지 14(3):36-51.
  12. 정일원, 이병주, 김광천, 배덕효. 2008. 기후변화에 따른 홍수피해 취약성 평가. 한국수자원학회 학술발표 논문집. 289-293쪽.
  13. 한건연. 2006. 내배수 침수재해 저감기술 개발. 소방방재청.
  14. Beatley, T. and K. Manning. 1997. The Ecology of Place: Planning for Environment, Economy and Community. Island press, Washington, D.C. 209pp.
  15. Biswajeet, P., S. Lee and M.F. Buchroithner. 2009. Use of geospatial data and fuzzy algebraic operators to landslide-hazard mapping. Applied Geomatics 1:3-15. https://doi.org/10.1007/s12518-009-0001-5
  16. Bonham-Carter, G.F., F.P. Agterberg and D.F. Wright. 1989. Weights of evidence modeling: A new approach to mapping mineral potential. In: Agterberg, F.P. and G.F. Bonham-Carter(Eds.). Statistical Applications in the Earth Sciences. Geological Survey of Canada, 989:171-183.
  17. Brody, S.D., S. Zahran, P. Maghelal, G. Grover and W.E. Highfield. 2007a. The rising costs of floods: examining the impact of planning and development decisions on property damage in Florida. Journal of the American Planning Association 73(3):330-345. https://doi.org/10.1080/01944360708977981
  18. Brody, S.D., S. Zahran, W.E. Highfield, G. Grover and A. Vedlitz. 2007b. Identifying the impact of the built environment on flood damage in Texas. Disasters 32(1):1-18.
  19. Brody, S.D., W.E. Highfield and J.E. Kang. 2011. Rising Waters: The Causes and Consequences of Flooding In the United States. Cambridge University Press. New York. 120pp.
  20. Burby, R.J. 1998. Cooperating with Nature: Confronting Natural Hazards with Land Use Planning for Sustainable Communities. Joseph Henry Press. Washington DC. pp. 220.
  21. Hardin, P.J. and R.R. Jensen. 2007. The effect of urban leaf area on summertime urban surface kinetic temperatures: a Terre Haute case study. Urban Forestry and Urban Greening 6(2):63-72. https://doi.org/10.1016/j.ufug.2007.01.005
  22. Highfield, W.E. and S.D. Brody. 2006. The price of permit: measuring the economic impacts of wetland development on flood damage in Florida. Natural Hazard Review 7(3):123-130. https://doi.org/10.1061/(ASCE)1527-6988(2006)7:3(123)
  23. Kang, J.E. 2009. Mitigating Flood Loss through Local Comprehensive Planning in Florida. Ph.D. Thisis, Texas A&M University, Texas, USA.
  24. Lee, M.J., J.W Lee, H.J Oh, J.S Won and S. Lee. 2011. Ensemble-based landslide susceptibility maps in Jinbu area, Korea. Environmental Earth Sciences doi:10.1007/s12665-011-1477-y.
  25. Lee, S., J.H. Ryu and I.S. Kim. 2007. Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea. Landslides 4(4):327-338. https://doi.org/10.1007/s10346-007-0088-x
  26. Lee, S., J.H. Ryu, M.J. Lee and J.S. Won. 2003. Use of an artificial neural network for analysis the susceptibility to Landslide at Boun, Korea. Environmental Geology 44(7):820-833. https://doi.org/10.1007/s00254-003-0825-y
  27. Lee, S., J.H. Ryu, M.J. Lee and J.S. Won. 2006. The application of artificial Neural networks to landslide susceptibility mapping at Janghung, Korea. Mathematical Geology 38(2):119-220.
  28. Lee, S. and N.T. Dan. 2005. Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides. Environmental Geology 48(6):778-787. https://doi.org/10.1007/s00254-005-0019-x
  29. Pielke, R.A. and M.W. Downton. 2000. Precipitation and damaging floods: trends in the United States, 1932-97. Journal of Climate 13(20):3625-3637. https://doi.org/10.1175/1520-0442(2000)013<3625:PADFTI>2.0.CO;2
  30. Randolph, J. 2004. Environmental Land Use Planning and Management. Island press. Washington, D.C. pp.163-172.
  31. USDA. 1986. Urban Hydrology for Small Watersheds. Technical Release 55. 26pp.

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