Prediction of Ground Subsidence Hazard Area Using GIS and Probability Model near Abandoned Underground Coal Mine

GIS 및 확률모델을 이용한 폐탄광 지역의 지반침하 위험 예측

  • Choi, Jong-Kuk (Department of Earth System Sciences, Yonsei University) ;
  • Kim, Ki-Dong (Geohazard information Laboratory, Department of Geoinformation Engineering Sejong University) ;
  • Lee, Sa-Ro (National Geoscience Information Center Korea Institute of Geoscience and Mineral Resources) ;
  • Kim, Il-Soo (Korea National Oil Corporation) ;
  • Won, Joong-Sun (Department of Earth System Sciences, Yonsei University)
  • 최종국 (연세대학교 지구시스템과학과) ;
  • 김기동 (세종대학교 지구정보공학과 지질재해정보연구실) ;
  • 이사로 (한국지질자원연구원 지질자원정보센터) ;
  • 김일수 (한국석유공사) ;
  • 원중선 (연세대학교 지구시스템과학과)
  • Published : 2007.06.28

Abstract

In this study, we predicted areas vulnerable to ground subsidence near abandoned underground coal mine at Sam-cheok City in Korea using a probability (frequency ratio) model with Geographic Information System (GIS). To extract the factors related to ground subsidence, a spatial database was constructed from a topographical map, geo-logical map, mining tunnel map, land characteristic map, and borehole data on the study area including subsidence sites surveyed in 2000. Eight major factors were extracted from the spatial analysis and the probability analysis of the surveyed ground subsidence sites. We have calculated the decision coefficient ($R^2$) to find out the relationship between eight factors and the occurrence of ground subsidence. The frequency ratio model was applied to deter-mine each factor's relative rating, then the ratings were overlaid for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with the surveyed ground subsidence sites. The results of verification showed high accuracy of 96.05% between the predicted hazard map and the actual ground subsidence sites. Therefore, the quantitative analysis of ground subsidence near abandoned underground coal mine would be possible with a frequency ratio model and a GIS.

본 연구에서는 확률기법인 빈도비 모델 (frequency ratio model) 및 지리정보시스템 (Geographic Information System: GIS)의 공간분석기법을 이용하여 강원도 삼척지역 폐탄광 주변의 지반침하 발생 취약지역을 예측하였다. 지반침하에 영향을 주는 요인들을 추출하기 위해 지형도, 지질도, 갱내도, 토지특성도, 시추공 자료, 기 관측된 침하지 자료 등으로부터 공간자료를 구축하였다. GIS 공간분석과 확률기법을 이용하여 지반침하의 주 요인이 되는 8개의 인자를 추출하였고 관측된 침하지역과 8개 인자와의 연관성을 알아보기 위하여 각각의 결정계수($R^2$)를 계산하였다. 빈도비 모델을 적용하여 각인자의 등급별 가중치를 결정한 후, 이를 중첩 분석하여 지반침하 위험 예측도를 작성하였다. 지반침하 위험 예측도를 기존 침하지 위치와 비교 검증한 결과 96.05%의 높은 예측정확도를 나타냈다. 이를 통해 폐탄광 지역에서 GIS와 빈도비 모델을 이용하여 지반침하 위험지역을 정량적으로 예측하는 것이 가능하다고 판단된다.

Keywords

References

  1. Choi, S.W. (2004) Development of the techniques for reducing the national disaster caused by ground subsidence, KIGAM, report, KR-04-13-5, p. 197-253
  2. Coal Industry Promotion Board (2000) Investigation report of the stability test for Dokye. v00-08, p.543
  3. Coal Industry Promotion Board (2004) A completion report of Abandoned Coal Mine GIS. 2004-04, p.172-173
  4. Geological Society of Koreaa (1999) Geology of Korea, p. 550-556
  5. Goel, S.C. and Page, C.H (1982) An Empirical Method for Predicting the Probability of Chimney Cave Occurrence over a Mining Area. Int. J. Rock Mech. Min, Sci. & Geomech. Abstr., v. 19, p. 325-337 https://doi.org/10.1016/0148-9062(82)91367-5
  6. Kim, K.D. (2005) Estimation of Ground Subsidence Near an Abandoned Underground Coal Mine using GIS and Neural Network. International Geoscience and Remote Sensing Symposium, Seoul, Korea, p. 5283-5285
  7. Lee, S.R., Lee, M.J. and Woon, J.S. (2004) Study on Landslide using GIS and Remote Sensing at the Kangneung Area(II) - Landslide Susceptibility Mapping and Corss-Validation using the Probability Technique. Econ. Environ. Geol. v. 37, no. 5, p. 521-532
  8. Lee, J.I. and Moon, H.G. (1997) A study on the Mechanism of subsidence over abandoned mine area and the Construction method of subsidence prevention, Coal Industry Promoton Board, 1997, v97-06, p. 1-67
  9. National Coal Board (1975) Subsidence Engineer's Handbook, National Coal Board Mining Department, London, p. 111
  10. Sheorey, P.R. (2000) Ground subsidence observations and a modified influence function method for complete subsidence prediction, Int. J. Rock Mech. Min. Sci. v37, p. 801-818 https://doi.org/10.1016/S1365-1609(00)00023-X
  11. Waltham, AC (1989) Ground subsidence, Blackie & Son Ltd, New York, p. 49-97