Journal of Korean Society of Forest Science (한국산림과학회지)

Korean Society of Forest Science (한국산림과학회)
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Prediction and Evaluation of Landslide Hazard Based on Regional Forest Environment

지역산림환경을 기반으로 한 산사태 발생 위험성의 예측 및 평가

  • Ma, Ho-Seop (Department of Forest Environmental Resources, Gyeongsang National University (Institute of Agriculture Life Science)) ;
  • Kang, Won-Seok (Department of Forest Environmental Resources, Gyeongsang National University (Institute of Agriculture Life Science)) ;
  • Lee, Sung-Jae (University Forest, Seoul National University)
  • 마호섭 (경상대학교 산림환경자원학과(농업생명과학연구원)) ;
  • 강원석 (경상대학교 산림환경자원학과(농업생명과학연구원)) ;
  • 이성재 (서울대학교 학술림)
  • Received : 2013.11.06
  • Accepted : 2014.05.08
  • Published : 2014.06.30
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Abstract

This study was carried out to propose the criteria for the prediction of landslide occurrence through analysis the influence of each factor by using the quantification theory. The results obtained from this study are summarized as follows. From a stepwise regression analysis between the landslide area($m^2$) and environmental factors, the factors strongly affecting the landslide sediment($m^2$) were the Parents rock (igneous), cross slope(complex), coniferous forests (forest type) and slope gradient ($21{\sim}30^{\circ}$). According to the range, it was shown in order of Cross slope (0.2922), Parents rock (0.2691), Forest type (0.2631) and Slope gradient (0.2312). The range of prediction score of landslide occurrence has been distributed between score 0 and score 1.0556, the median value was score 0.5278. The prediction for class I was over 0.7818, for class II was 0.5279 to 0.7917, for class III 0.2694 to 0.5278 and for class IV was below 0.2693. The prediction on landslide occurrence appeared relatively high accuracy rate as 72% for class I and II. Therefore, this score table for landslide will be very useful for judgement of dangerous slope.

본 연구는 지역산림지역을 중심으로 수량화이론을 이용하여 산사태 발생면적에 영향을 미치는 인자를 도출하여 각 인자의 기여도 분석을 통해 산사태 발생 위험성에 대한 예측기준을 마련하고, 그 기준을 평가하였다. 산사태 발생지 붕괴면적에 영향을 미치는 인자는 모암(화성암), 횡단사면(복합), 침엽수림(임상), 사면경사($21{\sim}30^{\circ}$ 이상)이었다. 각 인자의 Range를 추정한 결과, 횡단사면 (0.2922)이 가장 높게 나타났고, 다음으로는 모암(0.2691), 임상(0.2631), 사면경사(0.2312)순으로 나타났다. 산사태 발생 위험도 판정표를 기준으로 4개 인자의 category별 점수를 계산한 추정치 범위는 0 점에서 1.0556 점 사이에 분포하고 있으며, 중앙값은 0.5278 점이었다. I 등급의 점수는 0.7818 이상, II 등급은 0.5279~7917, III 등급은 0.2694~0.5278, IV 등급은 0.2693 이하로 나타났다. 1 등급 및 2 등급에서 산사태 발생 비율이 72%로서 비교적 높은 적중률을 보였다. 따라서 본 판정표는 산사태 위험도 판정에 활용 가능한 것으로 판단된다.

Keywords

References

  1. Changsugun. 2006. Report of Flood Rehabilitation Propulsion Situation. pp. 1-4.
  2. Cho, C.H. 2011. The Cause and Prospect of Climate Change. National Foresty Cooperative Federation San. pp. 74-77.
  3. Choi, E.Y. 2010. Korea landslide interpretation using. Master Dissertation Kongju National University Korea.
  4. Choi, K. 1986. Landslides occurrence and its prediction in Korea. Doctor of Philosophy Dissertation Kangwon National University Korea.
  5. Jeong, K.W. 2010. Studies on the causal characteristics of landslide and the development of hazard prediction map for landslide in Gyeongsangbuk-Do Province, Korea. Doctor of Philosophy Dissertation Kyungpook National University, Korea.
  6. Jo, M.H. and Jo, Y.W. 2009. Developing Forecast Technique of Landslide Hazard Area by Integrating Meteorological Observation Data and Topographical Data - A Case Study of Uljin Area -. The Korean Association of Geographic Information Studies 12(2): 1-10.
  7. Kang, J.T., Jung, S.Y., Ma, H.S., and Chung, Y. G. 1999. Analysis of the Forest-land Conservation Function by the GIS. Research Bulletin of Experiment Forests, Gyeongsang National University 9: 63-70.
  8. Kang, W.P., Hiroshi, M., Hiroshi, O., and Ma, H.S. 1986. On the determination of slope stability to landslide by quantification(II). Journal Korean Forestry Society 75: 32-37.
  9. Kim, G.H., Won, S.Y., Youn, J.H., and Song, Y.S. 2008. Hazard Risk Assessment for National Roads in Gangneung Journal of the Korean Society for Geo-Spatial Information System 16(4): 33-39.
  10. Kim, Y.J., Kim, Y.S., and Jo, W.C. 2010. Landslide Prediction and Warning Systems Construction in Dalsung Area of Daegu. Jornal of Korean Geotechnical Society 26(5): 10-18.
  11. Korea Forest Service. 2012. Spot Manual for Prevention and Response on Landslide. pp. 114.
  12. Korea Forest Service. 2014. Expert Workshop for Landslide Prevention in Korea. pp. 94.
  13. Lee, S.H. 2005. Application of physically based hydrologic model to the prediction of shallow landslide potential area using GIS. Doctor of Philosophy Dissertation Chungbuk University Korea.
  14. Lee, S.R. 2001. Application of Regional Landslide Susceptibility, Possibility, and Risk Assessment Techniques Using GIS. The Korean Society of Economic and Environmental Geology, Economic and Environmental Geology 34(4): 385-394.
  15. Ma, H.S. 1990. Studies on landslide and debris flow in Mt. Chiri district. Research Bulletin of Experiment Forests Gyeongsang National University 1: 13-25.
  16. Ma, H.S. 1992. Studies on Landslides and debris flow in Mt. Chiri district(II). Research Bulletin of Experiment Forests Gyeongsang National University 2: 17-28.
  17. Ma, H.S. 1994. Studies on development of prediction model of landslide hazard and its utilization. Journal of Korean Forestry Society 83: 175-190.
  18. Ma, H.S. 2001. Landslide Characteristics and Recovery Direction in Korean National Parks. Journal of National Park Research 27: 17-21.
  19. Ma, H.S. and Jeong, W.O. 2007. Analysis of landslides characteristics in Korean National Parks. Journal of Korean Forestry Society 6: 611-619.
  20. Ma, H.S., Jeong, W.O., and Park, J.W. 2008. Development of technique of landslide hazard area in Korea National Parks. Journal of Korean Forestry Society 97: 326-331.
  21. Ministry of Science and Technology. 2006. Developmenet of QRA system and damage mitigation technology of landslides. pp. 360.
  22. National Emergency Management Agency. 2008. Development of Prediction and Reduction Technology in Landslide.
  23. Oh, C.Y., Jun, K.W., Jang, C.D., and Jun, B.H. 2011. Verifying of Soil Water Index for Sediment Disaster Triggering in Mountainous Area. Korean Review of Crisis & Emergency Management. 7(4): 167-176.
  24. Toshio Shimizu. 1977. Statistical Analysis on Hazard Stability in Granite area. Journal of Japanese Forestry Society 59: 186-190.
  25. Toshio Shimizu. 1978. Discrimination of Dangerous Slope in Landslide - Theory and Technology -. Forest Techniques 439: 23-26.
  26. Woo, C.S., Lee, C.W., and Jeong, Y.H. 2008. Study on Application of Topographic Position Index for Prediction of the Landslide Occurrence. Journal of the Korea Society of Environmental Restoration Tecnology 11(2): 1-9.

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