DOI QR코드

DOI QR Code

Development of the Topography Restoration Method for Debris Flow Area Using Airborne LiDAR Data

항공 라이다 자료를 이용한 토석류 발생지역의 지형복원기법 개발

  • Woo, Choong-Shik (Division of Forest Disaster Management, Korea Forest Research Institut) ;
  • Youn, Ho-Joong (Division of Forest Disaster Management, Korea Forest Research Institut) ;
  • Lee, Chang-Woo (Division of Forest Disaster Management, Korea Forest Research Institut) ;
  • Lee, Kyu-Sung (Department of Geoinformatic Engineering, Inha University)
  • 우충식 (국립산림과학원 산림방재연구과) ;
  • 윤호중 (국립산림과학원 산림방재연구과) ;
  • 이창우 (국립산림과학원 산림방재연구과) ;
  • 이규성 (인하대학교 지리정보공학과)
  • Received : 2011.07.16
  • Accepted : 2011.09.15
  • Published : 2011.09.30

Abstract

The flowed soil is able to be estimated from topographic data of before and after the debris flow. However, it is often difficult to obtain airborne LiDAR data before the debris flow area. Thus, this study tries to develop a topographic restoration method that can provide spatial distribution of flowed soil and reconstruct the topography before the debris flow using airborne LiDAR data. The topographic restoration method can express a numerical formula induced from a Gaussian mixture model after extracting the cross sections of linear or non-linear in debris flowed area. The topographic restoration method was verified by two ways using airborne LiDAR data of before and after the debris flow. First, each cross section extracted from the debris flow sites to restore the topography was compared with airborne LiDAR data of before the debris flow. Also, the topographic data produced after the topographic restoration method applied to the debris flow sites was verified by airborne LiDAR DEM. Verifying the results of the topographic restoration method, overall fitting accuracy showed high accuracy close to 0.5m.

항공 LiDAR 측량으로 토석류 발생 전 후의 지형자료를 취득하는 경우 토석류로 인하여 유출된 토사량을 알 수 있다. 그러나 토석류 발생지를 미리 예측하여 촬영하기가 힘들고, 토석류 발생 지역의 과거 항공 LiDAR 자료는 존재가능성이 낮아 토석류 발생이전 지형자료를 이용하는 것은 어렵다. 따라서 본 연구에서는 토석류 발생지역의 토사량 추정을 위해 발생전 지형을 복원하고, 토사유출의 공간적 범위를 파악할 수 있는 지형복원기법을 개발하였다. 지형복원기법은 토석류 발생지역에서 추출한 선형 및 비선형 횡단면을 가우시안혼합모델로 수식화하고 중심점 추정방법과 근사정확도로 근사결과를 평가하여 토석류 발생이전의 지형을 복원한다. 지형복원기법은 토석류 발생 전 후의 항공 LiDAR 자료를 이용하여 두 가지 방법으로 검증하였다. 먼저 토석류 발생구간에서 추출한 각 횡단면을 지형복원하여 발생전 항공 LiDAR 자료와 비교하였다. 또한 토석류 발생지역에 지형복원기법을 적용한 뒤 지형자료를 제작하여 토석류 발생전 항공 LiDAR DEM과 비교하여 검증하였다. 지형복원기법의 검증한 결과 전반적으로 근사정확도가 0.5m에 가까운 높은 정확도를 나타냈다.

Keywords

References

  1. 구자흥, 김진경, 박진호, 박헌진, 이재준, 전홍석, 황진수, 2000. 통계학. 자유아카데미. 225-313쪽.
  2. 윤호중, 이창우, 우충식, 정용호, 이천용, 2009. 토석류 발생특성과 피해규모 예측기법 개발. 국립산림과학원. 1-2쪽.
  3. 한학용, 2005. 패턴인식개론. 한빛미디어. 570쪽.
  4. Ai, T. and J. Li. 2010. A DEM generalization by minor valley branch detection and grid filling. ISPRS Journal of Photogrammetry and Remote Sensing 65:198-207. https://doi.org/10.1016/j.isprsjprs.2009.11.001
  5. Anders, N.S., A.C. Seijmonsbergen and W. Bouten. 2009. Modelling channel incision and alpine hillslope development using laser altimetry data. Geomorphology 113:35-46. https://doi.org/10.1016/j.geomorph.2009.03.022
  6. Evans, M. and J. Lindsay. 2010. High resolution quantification of gully erosion in upland peatlands at the landscape scale. Earth Surface Processes and Landforms 35:876-886. https://doi.org/10.1002/esp.1918
  7. Harbor, J.M. and D.A. Wheeler. 1992. On the mathematical description of glacial valley cross sections. Earth Surface Processes and Landforms 17:477-485. https://doi.org/10.1002/esp.3290170507
  8. Hirano, M. and M. Aniya. 1988. A rational explanation of cross-profile morphology for glacial valleys and glacial valley development. Earth Surface Processes and Landforms 13:707-716. https://doi.org/10.1002/esp.3290130805
  9. James, L.A. 1996. Polynomoal and power functions for glacial valley crosssection morphology. Earth Surface Processes and Landforms 21:413-432. https://doi.org/10.1002/(SICI)1096-9837(199605)21:5<413::AID-ESP570>3.0.CO;2-S
  10. Matsuoka, A., T. Yamakoshi, K. Tamura, Y. Nagai, J. Maruyama, T. Kotake, K. Ogawa and S. Tagata. 2009. Sediment dynamics in the mountainous watersheds based on differentiation of multitemporal LiDAR survey data sets. Journal of the Japan Society of Erosion Control Engineering 62:60-65.
  11. O'Brien, J.S., P.Y. Julienand W.T. Fullerton. 1993. Two dimensional water flood and mudflow simulation. Journal of Hydraulic Engineering 119:244-259. https://doi.org/10.1061/(ASCE)0733-9429(1993)119:2(244)
  12. Schappi, B., P. Peronaa, P. Schneiderb and P. Burlando. 2010. Grating river cross section measurements with digital terrain models for improved flow modelling applications. Computers & Geosciences 36:707-716. https://doi.org/10.1016/j.cageo.2009.12.004
  13. Schtott, L., G. Hufschmidt, M. Hankammer, T. Hoffmann and T. Dikau. 2003. Spatial distribution of sediment storage types and quantification of valley fill deposits in an alpine basin, Reintal, Bavarian Alps, Germany. Geomorphology 55:45-63. https://doi.org/10.1016/S0169-555X(03)00131-4
  14. Su, J. and E. Bork. 2006. Influence of vegetation, slope, and LiDAR sampling angle on DEM Accuracy. Photogrammetric Engineering and Remote Sensing 72: 1265-1274. https://doi.org/10.14358/PERS.72.11.1265
  15. Svensson, H. 1959. Is the cross-section of a glacial valley a parabola?. Journal of Glaciology 3:362-363.
  16. Veyrat-Charvillon1, S. and M. Memier. 2006. Stereophotogrammetry of archive data and topographic approaches to debris-flow torrent measurements : calculation of channel-sediment states and a partial sediment budget for Manival torrent (Isere, France). Earth Surface Processes and Landforms 31:201-219. https://doi.org/10.1002/esp.1322
  17. Wheeler, D.A. 1984. Using parabolas to describe the cross-sections of glaciated valleys. Earth Surf. Processes Landforms 9:391-394. https://doi.org/10.1002/esp.3290090412

Cited by

  1. Evaluation for Earthwork Slope Safety Using Terrestrial LiDAR vol.17, pp.3, 2014, https://doi.org/10.11108/kagis.2014.17.3.082
  2. Analysis of Debris Flow Deposition based on Topographic Characteristics of Debris Flow Path vol.31, pp.6_1, 2013, https://doi.org/10.7848/ksgpc.2013.31.6-1.471