한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제54권8호
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  • Pages.553-566
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  • 2021
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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RGB 항공 영상을 이용한 하천 합류부 전단층 추출법

Identification of shear layer at river confluence using (RGB) aerial imagery

  • 노효섭 (서울대학교 건설환경공학부) ;
  • 박용성 (서울대학교 건설환경공학부)
  • Noh, Hyoseob (Department of Civil and Environmental Engineering, Seoul National University) ;
  • Park, Yong Sung (Department of Civil and Environmental Engineering, Seoul National University)
  • 투고 : 2021.03.18
  • 심사 : 2021.06.02
  • 발행 : 2021.08.31
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초록

하천 합류부는 두 개의 수체가 만나 전단층을 이루고 전단층을 따라 강한 혼합양상을 보이는 특징이 있다. 자연하천에서 합류하는 대비되는 두 하천의 색은 전단층을 따라 구분될 수 있는데, 이는 위성 또는 무인항공체를 이용해 촬영된 항공영상을 통해 쉽게 관측할 수 있다. 본 연구에서는 취득 비용이 저렴한 RGB 항공 영상을 이용해 합류부에서 발생하는 전단층을 추출하고 전단층 주변의 기하학적 특성을 정량적으로 산정하는 방법을 제시한다. 본 방법은 네 단계로 구분된다. 첫 번째로, 합류부 흐름에서 전단층 추출을 위해 가우시안 혼합 모형을 바탕으로 한 영상 분할을 수행하여 본류와 지류가 포함된 픽셀을 추출해낸다. 다음으로 추출된 하천 수역에 자기조직화지도를 적용해 하천의유선을 1차원 곡선으로 단순화한다. 추출된 수체 영역과 1차원 곡선들을 이용해 본류와 지류의 수역을 이미지상 직교좌표계에서 곡선좌표계로 투영한 뒤, 마지막으로 전단층의 기하학적 특성을 산정한다. 결과적으로 개발된 전단층 추출법을 경상남도의 낙동강과 남강의 합류부가 촬영된 위성 영상에 적용하여 자연하천 합류부의 기하학적 특성인 합류각, 합류하는 두 하천의 상하류 하천 폭, 전단층의 길이, 그리고 전단층의 최대 두께를 각각 정량적으로 추출하는 데에 성공하였다.

River confluence is often characterized by shear layer and the associated strong mixing. In natural rivers, the main channel and its tributary can be separated by the shear layer using contrasting colors. The shear layer can be easily observed using aerial images from satellite or unmanned aerial vehicles. This study proposes a low-cost identification method extracting geographic features of the shear layer using RGB aerial image. The method consists of three stages. At first, in order to identify the shear layer, it performs image segmentation using a Gaussian mixture model and extracts the water bodies of the main channel and tributary. Next, the self-organizing map simplifies the flow line of the water bodies into the 1-dimensional curve grid. After that, the curvilinear coordinate transformation is performed using the water body pixels and the curve grid. As a result, the shear layer identification method was successfully applied to the confluence between Nakdong River and Nam River to extract geometric shear layer features (confluence angle, upstream- and downstream- channel widths, shear layer length, maximum shear layer thickness).

키워드

과제정보

본 연구는 과학기술정보통신부 및 국토교통부 "공공혁신 조달 연계 무인항공체 및 SW플랫폼 개발사업" (19DPIW-C153746-01)의 연구비 지원에 의해 수행되었으며 이에 감사드립니다.

참고문헌

  1. Ashworth, P.J., and Lewin, J. (2012). "How do big rivers come to be different?" Earth-Science Reviews, Vol. 114, No. 1-2, pp. 84-107. https://doi.org/10.1016/j.earscirev.2012.05.003
  2. Ban, Z., Liu, J., and Cao, L. (2018). "Superpixel segmentation using Gaussian mixture model." IEEE Transactions on Image Processing, Vol. 27, No. 8, pp. 4105-4117. https://doi.org/10.1109/TIP.2018.2836306
  3. Best, J.L. (1987). "Flow dynamics at river channel confluences: Implications for sediment transport and bed morphology." Edited by Ethridge, F.G., Flores, R.M., and Harvey, M.D., SEPM Special Publication 39, Recent Developments in Fluvial Sedimentology. Society of Economic Paleontologists and Mineralogists, Tulsa, OK, U.S., pp. 27-35.
  4. Best, J.L., and Ashworth, P.J. (1997). "Scour in large braided rivers and the recognition of sequence stratigraphic boundaries." Nature, Vol. 387, No. 6630, pp. 275-277. https://doi.org/10.1038/387275a0
  5. Bishop, C.M. (2006). Pattern recognition and machine learning. springer, Berlin, Germany.
  6. Brosinsky, A., Foerster, S., Segl, K., Lopez-Tarazon, J.A., Pique, G., and Bronstert, A. (2014). "Spectral fingerprinting: Characterizing suspended sediment sources by the use of VNIR-SWIR spectral information." Journal of Soils and Sediments, Vol. 14, No. 12, pp. 1965-1981. https://doi.org/10.1007/s11368-014-0927-z
  7. Constantinescu, G., Miyawaki, S., Rhoads, B., and Sukhodolov, A. (2012). "Numerical analysis of the effect of momentum ratio on the dynamics and sediment-entrainment capacity of coherent flow structures at a stream confluence." Journal of Geophysical Research: Earth Surface, Vol. 117, No. F4, F04028.
  8. Constantinescu, G., Miyawaki, S., Rhoads, B., and Sukhodolov, A. (2016). "Influence of planform geometry and momentum ratio on thermal mixing at a stream confluence with a concordant bed." Environmental Fluid Mechanics, Vol. 16, No. 4, pp. 845-873. https://doi.org/10.1007/s10652-016-9457-0
  9. De Serres, B., Roy, A.G., Biron, P.M., and Best, J.L. (1999). "Three-dimensional structure of flow at a confluence of river channels with discordant beds." Geomorphology, Vol. 26, No. 4, pp. 313-335. https://doi.org/10.1016/S0169-555X(98)00064-6
  10. Dempster, A.P., Laird, N.M., and Rubin, D.B. (1977). "Maximum likelihood from incomplete data via the EM algorithm." Journal of the Royal Statistical Society: Series B (Methodological), Vol. 39, No. 1, pp. 1-22. https://doi.org/10.2307/2347807
  11. Dixon, S.J., Sambrook Smith, G.H., Best, J.L., Nicholas, A.P., Bull, J.M., Vardy, M.E., Sarker, M.H., and Goodbred, S. (2018). "The planform mobility of river channel confluences: Insights from analysis of remotely sensed imagery." Earth-Science Reviews, Vol. 176, pp. 1-18. https://doi.org/10.1016/j.earscirev.2017.09.009
  12. Gaudet, J.M., and Roy, A.G. (1995). "Effect of bed morphology on flow mixing length at river confluences." Nature, Vol. 373, No. 6510, pp. 138-139. https://doi.org/10.1038/373138a0
  13. Gualtieri, C., Ianniruberto, M., and Filizola, N. (2019). "On the mixing of rivers with a difference in density: The case of the Negro/Solimoes confluence, Brazil." Journal of Hydrology, Vol. 578, 124029. https://doi.org/10.1016/j.jhydrol.2019.124029
  14. Hackney, C., and Carling, P. (2011). "The occurrence of obtuse junction angles and changes in channel width below tributaries along the Mekong River, South-east Asia." Earth Surface Processes and Landforms, Vol. 36, No. 12, pp. 1563-1576. https://doi.org/10.1002/esp.2165
  15. Ji, Z., Huang, Y., Xia, Y., and Zheng, Y. (2017). "A robust modified Gaussian mixture model with rough set for image segmentation." Neurocomputing, Vol. 266, pp. 550-565. https://doi.org/10.1016/j.neucom.2017.05.069
  16. Jung, S.H., Seo, I.W., Kim, Y.D., and Park, I. (2019). "Feasibility of velocity-based method for transverse mixing coefficients in river mixing analysis." Journal of Hydraulic Engineering, Vol. 145, No. 11, 04019040. https://doi.org/10.1061/(asce)hy.1943-7900.0001638
  17. Kohonen, T. (1990). "The self-organizing map." Proceedings of the IEEE, Vol. 78, No. 9, pp. 1464-1480. https://doi.org/10.1109/5.58325
  18. Kohonen, T. (2001). Self-organizing maps (3rd ed.), Springer, Berlin-Heidelberg, Germany.
  19. Konsoer, K.M., and Rhoads, B.L. (2014). "Spatial - temporal structure of mixing interface turbulence at two large river confluences." Environmental Fluid Mechanics, Vol. 14, No. 5, pp. 1043-1070. https://doi.org/10.1007/s10652-013-9304-5
  20. Kwon, S., Seo, I. W., and Beak, D. (2021). "Development of suspended solid concentration measurement technique based on multi-spectral satellite imagery in Nakdong River using machine learning model." Journal of Korea Water Resources Association, Vol. 54, No. 2, pp. 121-133.
  21. Lewin, J., and Ashworth, P.J. (2014). "Defining large river channel patterns: Alluvial exchange and plurality." Geomorphology, Vol. 215, pp. 83-98. https://doi.org/10.1016/j.geomorph.2013.02.024
  22. Lewis, Q.W., and Rhoads, B.L. (2018). "LSPIV measurements of two-dimensional flow structure in streams using small unmanned aerial systems: 2. Hydrodynamic mapping at river confluences." Water Resources Research, Vol. 54, No. 10, pp. 7981-7999. https://doi.org/10.1029/2018wr022551
  23. Mount, N.J., Tate, N.J., Sarker, M.H., and Thorne, C.R. (2013). "Evolutionary, multi-scale analysis of river bank line retreat using continuous wavelet transforms: Jamuna River, Bangladesh." Geomorphology, Vol. 183, pp. 82-95. https://doi.org/10.1016/j.geomorph.2012.07.017
  24. Nikou, C., Galatsanos, N.P., and Likas, A.C. (2007). "A class-adaptive spatially variant mixture model for image segmentation." IEEE Transactions on Image Processing, Vol. 16, No. 4, pp. 1121-1130. https://doi.org/10.1109/TIP.2007.891771
  25. Novo, E.M.M., Hansom, J.D., and Curran, P.J. (1989). "The effect of sediment type on the relationship between reflectance and suspended sediment concentration." Remote Sensing, Vol. 10, No. 7, pp. 1283-1289. https://doi.org/10.1080/01431168908903967
  26. Permuter, H., Francos, J., and Jermyn, I. (2006). "A study of Gaussian mixture models of color and texture features for image classification and segmentation." Pattern Recognition, Vol. 39, No. 4, pp. 695-706. https://doi.org/10.1016/j.patcog.2005.10.028
  27. Pham, Q.V., Ha, N.T.T., Pahlevan, N., Oanh, L.T., Nguyen, T.B., and Nguyen, N.T. (2018). "Using landsat-8 images for quantifying suspended sediment concentration in red river (Northern Vietnam)." Remote Sensing, Vol. 10, No. 11, 1841. https://doi.org/10.3390/rs10111841
  28. Ramon, C.L., Hoyer, A.B., Armengol, J., Dolz, J., and Rueda, F.J. (2013). "Mixing and circulation at the confluence of two rivers entering a meandering reservoir." Water Resources Research, Vol. 49, No. 3, pp. 1429-1445. https://doi.org/10.1002/wrcr.20131
  29. Rhoads, B.L. (1987). "Changes in stream channel characteristics at tributary junctions." Physical Geography, Vol. 8, No. 4, pp. 346-361. https://doi.org/10.1080/02723646.1987.10642333
  30. Rhoads, B.L. (1996). "Mean structure of transport-effective flows at an asymmetrical confluence when the main stream is dominant." Coherent Flow Structures in Open Channels, Edited by Ashworth, P., Bennett, S.J., Best, J.L., and McLelland, S.J., Wiley, Chichester, U.K., pp. 491-517.
  31. Rhoads, B.L., and Sukhodolov, A.N. (2001). "Field investigation of three-dimensional flow structure at stream confluences: 1. Thermal mixing and time-averaged velocities." Water Resources Research, Vol. 37, No. 9, pp. 2393-2410. https://doi.org/10.1029/2001WR000316
  32. Rhoads, B.L., and Sukhodolov, A.N. (2004). "Spatial and temporal structure of shear layer turbulence at a stream confluence." Water Resources Research, Vol. 40, No. 6.
  33. Rhoads, B.L., and Sukhodolov, A.N. (2008). "Lateral momentum flux and the spatial evolution of flow within a confluence mixing interface." Water Resources Research, Vol. 44, No. 8.
  34. Seo, I.W., and Park, I. (2013). "Determination of ecological flow at the confluence of Nakdong River and Gumho River using river2D." Journal of The Korean Society of Civil Engineers, Vol. 33, No. 3, pp. 947-956. https://doi.org/10.12652/Ksce.2013.33.3.947
  35. Shi, X., Li, Y., and Zhao, Q. (2020). "Flexible hierarchical Gaussian mixture model for high-resolution remote sensing image segmentation." Remote Sensing, Vol. 12, No. 7, 1219. https://doi.org/10.3390/rs12071219
  36. Son, G., Kim, D., Kwak, S., Kim, Y.D., and Lyu, S. (2021). "Characterizing three-dimensional mixing process in river confluence using acoustical backscatter as surrogate of suspended sediment." Journal of Korea Water Resources Association, Vol. 54, No. 3, pp. 167-179. https://doi.org/10.3741/JKWRA.2021.54.3.167
  37. Sukhodolov, A.N., and Rhoads, B.L. (2001). "Field investigation of three-dimensional flow structure at stream confluences: 2. Turbulence." Water Resources Research, Vol. 37, No. 9, pp. 2411-2424. https://doi.org/10.1029/2001WR000317
  38. Sukhodolov, A.N., Krick, J., Sukhodolova, T.A., Cheng, Z., Rhoads, B.L., and Constantinescu, G.S. (2017). "Turbulent flow structure at a discordant river confluence: Asymmetric jet dynamics with implications for channel morphology." Journal of Geophysical Research: Earth Surface, Vol. 122, No. 6, pp. 1278-1293. https://doi.org/10.1002/2016JF004126
  39. Sukhodolov, A.N., Schnauder, I., and Uijttewaal, W.S. (2010). "Dynamics of shallow lateral shear layers: Experimental study in a river with a sandy bed." Water Resources Research, Vol. 46, No. 11.
  40. Trigg, M.A., Bates, P.D., Wilson, M.D., Schumann, G., and Baugh, C. (2012). "Floodplain channel morphology and networks of the middle Amazon River." Water Resources Research, Vol. 48, No. 10.
  41. Ullah, M.S., Bhattacharya, J.P., and Dupre, W.R. (2015). "Confluence scours versus incised valleys: Examples from the cretaceous Ferron Notom Delta, Southeastern Utah, U.S.A." Journal of Sedimentary Research, Vol. 85, No. 5, pp. 445-458. https://doi.org/10.2110/jsr.2015.34
  42. Umar, M., Rhoads, B.L., and Greenberg, J.A. (2018). "Use of multispectral satellite remote sensing to assess mixing of suspended sediment downstream of large river confluences." Journal of Hydrology, Vol. 556, pp. 325-338. https://doi.org/10.1016/j.jhydrol.2017.11.026
  43. Winant, C.D., and Browand, F.K. (1974). "Vortex pairing: The mechanism of turbulent mixing-layer growth at moderate Reynolds number." Journal of Fluid Mechanics, Vol. 63, No. 2, pp. 237-255. https://doi.org/10.1017/S0022112074001121
  44. Yuan, S., Tang, H., Xiao, Y., Qiu, X., and Xia, Y. (2018). "Water flow and sediment transport at open-channel confluences: An experimental study." Journal of Hydraulic Research, Vol. 56, No. 3, pp. 333-350. https://doi.org/10.1080/00221686.2017.1354932
  45. Yuan, S., Tang, H., Xiao, Y., Qiu, X., Zhang, H., and Yu, D. (2016). "Turbulent flow structure at a 90-degree open channel confluence: Accounting for the distortion of the shear layer." Journal of Hydro-environment Research, Vol. 12, pp. 130-147. https://doi.org/10.1016/j.jher.2016.05.006
  46. Zhang, Y., Brady, M., and Smith, S. (2001). "Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm." IEEE Transactions on Medical Imaging, Vol. 20, No. 1, pp. 45-57. https://doi.org/10.1109/42.906424