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UAV Aerial Photogrammetry for Cross Sectional Extraction and Slope Stability Analysis in Forest Area

UAV 항공사진을 이용한 산림지 횡단면도 추출 및 사면안정성 평가

  • Kim, Taejin (Department of Rural Systems Engineering, Seoul National University) ;
  • Son, Younghwan (Department of Rural Systems Engineering and Research Institute for Agriculture and Life Sciences, Seoul National University) ;
  • Park, Jaesung (Division of Environmental Science & Technology, Graduate School of Agriculture, Kyoto University) ;
  • Kim, Donggeun (Department of Rural Systems Engineering, Seoul National University)
  • Received : 2017.10.24
  • Accepted : 2017.12.04
  • Published : 2018.01.31

Abstract

The objective of this study is to extract the shape of the slope from the images acquired using UAV and evaluate its suitability and reliability when applied to slope stability analysis. UAV is relatively inexpensive and simple, and it is possible to make terrain survey by generating point clouds. However, the image acquired from UAV can not be directly photographed by the forest canopy due to the influence of trees, resulting in severe distortion of the terrain. In this study, therefore, the effects of forest canopy were verified and the slope stability analysis was performed. Images acquired in winter and summer were used, because summer images are heavily influenced by the forest canopy and winter images are not. As a result of the study, the winter image is suitable for the extraction of slope shape, but severe terrain distortion occurs in the summer image. Therefore, slope stability analysis using slope shape extracted from summer image is impossible, so it should be modified for slope stability analysis. The modified slope did not completely eliminate the distortion of the terrain, but it could express the approximate shape of the slope. As a result of the slope stability analysis, the location and shape of the failure surface are the same, and the error of the safety factor is less than 0.2, which is close to the actual slope.

Keywords

References

  1. Cho, Y. S., 2015. Construction of 3D spatial information and development of site management system using UAV. Ph.D. diss., Cheongju, Korea.: Chungbuk National University (in Korean).
  2. Dorren, L. K., B. Maier, and A. C. Seijmonsbergen, 2003. Improved Landsat-based forest mapping in steep mountainous terrain using object-based classification. Forest Ecology and Management, 183(1): 31-46. doi:10.1016/S0378-1127(03)00113-0
  3. Henricsson, O. and E. P. Baltsavias, 1997. 3-D building reconstruction with ARUBA. Automatic extraction of man-made objects from aerial and space images (II), 65-76. doi:10.3929/ethz-a-004334529
  4. Jo, M. H. and Y. W. Jo, 2009. Developing forecast technique of landslide hazard area by integrating meteorological observation data and topographical data-a case study of Uljin area. Journal of the Korean Association of Geographic Information Studies, 12(2):1-10.
  5. Jung, S. H., H. M. Lim, and J. K Lee, 2010. Acquisition of 3D spatial information using UAV photogrammetric method. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 28(1): 161-168.
  6. Kim, D. I., Y. S. Song, G. Kim, and C. W. Kim, 2014. A study on the application of UAV for Korean land monitoring. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 32(1): 29-38. doi:10.7848/ksgpc.2014.32.1.29
  7. Kim, J. G., 2007, A study on the relational features between the bands' characteristics of color aerial photos and the accuracy of the extracted DEM. Ph.D. diss., Seoul, Korea.: Seoul National University (in Korean).
  8. Kim, S. S., J. H. Jung, E. M. Kim, H. H. Yoo, and H. G. Sohn, 2008. Geocoding of low altitude UAV imagery using affine transformation model. Journal of Korean Society for Geospatial Information System, 16(4): 79-87.
  9. Lee, G. S. and Y. W. Choi, 2015. Landslide hazard evaluation using geospatial information based on UAV and infinite slope stability model. Journal of cadastre and land informatix, 45(2): 161-173. https://doi.org/10.22640/LXSIRI.2015.45.2.161
  10. Lee, I. S., J. O. Lee, S. J. Kim, and S. H. Hong, 2013. Orhtophoto accuracy assessment of ultra-light fixed wing UAV photogrammetry techniques. Journal of the Korean Society of Civil Engineers, 33(6): 2593-2600. doi:10.12652/Ksce.2013.33.6.2593
  11. Lee, K. H., 2000. A study on 3-D spatial information analysis and application using satellite image, 34-72. Seoul, Korea : Sogang University
  12. Lee, W. H., J. O. Kim, K. Y. Yu, and Y. I. Kim, 2004. A study on the 3-dimensional modeling of buildings in urban areas using digital maps and LiDAR data. Journal of The Korean Society of Civil Engineers, 24(2D): 311-318.
  13. Lim, S. B., C. W. Seo, and H. C. Yun, 2015. Digital map updates with UAV photogrammetric methods. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 33(5): 397-405. doi:10.7848/ksgpc.2015.33.5.397
  14. Nagai, M., T. Chen, R. Shibasaki, H. Kumagai, and A. Ahmed, 2009. UAV-borne 3-D mapping system by multisensor integration. IEEE Transactions on Geoscience and Remote Sensing, 47(3): 701-708. doi:10.1109/TGRS.2008.2010314
  15. Niethammer, U., S. Rothmund, U. Schwaderer, J. Zeman, and M. Joswig, 2011. Open source image-processing tools for lowcost UAV-based landslide investigations. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 38(1), C22.
  16. Park, J. H. and W. H. Lee, 2016. Orthophoto and DEM generation in small slope areas using low specification UAV. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 34(3): 283-290. doi:10.7848/ksgpc.2016.34.3.283
  17. Park, J. S., 2017, Soil classification and characterization using unmanned aerial vehicle and digital image processing. Ph.D. diss., Seoul, Korea.: Seoul National University (in Korean).
  18. St-Onge, B., F. A. Audet, and J. Begin, 2015. Characterizing the height structure and composition of a boreal forest using an individual tree crown approach applied to photogrammetric point clouds. Forests, 6(11): 3899-3922. doi:10.3390/f6113899
  19. White, J. C., C. Stepper, P. Tompalski, N. C. Coops, and M. A. Wulder, 2015. Comparing ALS and image-based point cloud metrics and modelled forest inventory attributes in a complex coastal forest environment. Forests, 6(10): 3704-3732. doi: 10.3390/f6103704
  20. White, J. C., M. A. Wulder, M. Vastaranta, N. C. Coops, D. Pitt, and M. Woods, 2013. The utility of image-based point clouds for forest inventory: A comparison with airborne laser scanning. Forests, 4(3): 518-536. doi:10.3390/f4030518
  21. Yoo, H. H., J. W. Park, J. H. Shim, and S. S. Kim, 2006. Image map generation using low-altitude photogrammetric UAV. Journal of Korean Society for Geospatial Information System, 14(1): 37-47.
  22. Zhu, X. and D. Liu, 2014. Accurate mapping of forest types using dense seasonal Landsat time-series. ISPRS Journal of Photogrammetry and Remote Sensing, 96: 1-11. doi:10.1016/j.isprsjprs.2014.06.012
  23. Zongjian, L. I. N. 2008. UAV for mapping-low altitude photogrammetric survey. International Archives of Photogrammetry and Remote Sensing, Beijing, China, 37: 1183-1186.