Journal of the Korean Association of Geographic Information Studies (한국지리정보학회지)

The Korean Association of Geographic Information Studies (한국지리정보학회)
권호 표지
DOI QR코드

DOI QR Code

Estimation of channel morphology using RGB orthomosaic images from drone - focusing on the Naesung stream -

드론 RGB 정사영상 기반 하도 지형 공간 추정 방법 - 내성천 중심으로 -

  • Woo-Chul, KANG (Korea Institute of Civil Engineering and Building Technology, Department of Land, Water and Environment Research) ;
  • Kyng-Su, LEE (Korea Institute of Civil Engineering and Building Technology, Department of Land, Water and Environment Research) ;
  • Eun-Kyung, JANG (Korea Institute of Civil Engineering and Building Technology, Department of Land, Water and Environment Research)
  • 강우철 (한국건설기술연구원 수자원하천연구본부) ;
  • 이경수 (한국건설기술연구원 수자원하천연구본부) ;
  • 장은경 (한국건설기술연구원 수자원하천연구본부)
  • Received : 2022.11.21
  • Accepted : 2022.12.09
  • Published : 2022.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

In this study, a comparative review was conducted on how to use RGB images to obtain river topographic information, which is one of the most essential data for eco-friendly river management and flood level analysis. In terms of the topographic information of river zone, to obtain the topographic information of flow section is one of the difficult topic, therefore, this study focused on estimating the river topographic information of flow section through RGB images. For this study, the river topography surveying was directly conducted using ADCP and RTK-GPS, and at the same time, and orthomosiac image were created using high-resolution images obtained by drone photography. And then, the existing developed regression equations were applied to the result of channel topography surveying by ADCP and the band values of the RGB images, and the channel bathymetry in the study area was estimated using the regression equation that showed the best predictability. In addition, CCHE2D flow modeling was simulated to perform comparative verification of the topographical informations. The modeling result with the image-based topographical information provided better water depth and current velocity simulation results, when it compared to the directly measured topographical information for which measurement of the sub-section was not performed. It is concluded that river topographic information could be obtained from RGB images, and if additional research was conducted, it could be used as a method of obtaining efficient river topographic information for river management.

본 연구는 하천 관리 및 홍수위 분석에 있어 필수적인 자료 중 하나인 하천 지형정보를 얻기 위해 RGB 영상을 활용하는 방법에 대한 비교 검토가 이루어졌다. 하천 구역의 지형정보를 얻는 데 있어 흐름 구간 즉 하도 지형정보를 얻는 것이 가장 어려운 분야 중 하나이기에 본 연구에서는 RGB 영상 기반으로 하도 지형정보를 추정하는 것에 집중하였다. 이를 위해 Acoustic Doppler Current Profiler(ADCP)와 RTK-GPS(Real Time Kinematic-GPS)를 이용하여 하도 지형을 직접 계측하였으며, 동시에 드론 촬영을 통해 획득한 고해상도 이미지를 이용하여 정사 영상을 생성하였다. 이후 수심 계측 결과와 RGB 정사 영상의 밴드 값들을 이용하여 수심 예측을 위한 기존에 개발된 회귀식들을 적용하였으며, 가장 뛰어난 예측력을 보여준 회귀식을 이용하여 연구 대상 지역의 하도 지형을 추정하였다. 흐름 구간 이외 지역의 경우 항공 라이다로부터 생성된 DEM을 이용하여 하천 구간 전체에 대한 지형정보를 구축하였다. 추가로 드론 촬영이 이루어진 동일한 시간 동안 직접 계측한 자료를 이용하여 생성된 지형정보와 드론 정사 영상 기반으로 생성된 하도 지형정보의 비교 검증을 수행하기 위해 CCHE2D 모형을 활용하여 흐름 모델링을 모의하였으며, 일부 구간에 대한 계측이 이루어지지 못한 직접 계측한 지형정보와 비교하여 영상 기반의 지형정보는 보다 나은 수심, 유속 모의 결과를 보여주었다. 본 연구 결과를 통해 RGB 영상으로부터 하도 지형정보를 획득할 수 있는 것을 확인하였으며, 추가적인 연구가 수행된다면 하천 관리를 위한 효율적인 하천 지형정보를 얻는 방법으로 활용할 가능성을 확인하였다.

Keywords

Acknowledgement

본 결과물은 환경부의 재원으로 한국환경산업기술원의 물관리연구사업의 지원을 받아 연구되었습니다. (1615012820)

References

  1. Fausch, K.D., Torgersen, C.E., Baxter, C.V. and Li, H.W. 2002. Landscapes to riverscapes: bridging the gap between research and conservation of stream fishes: a continuous view of the river is needed to understansd how processes interacting among scales set the context for stream fishes and their habitat. BioScience 52(6):483-498. https://doi.org/10.1641/0006-3568(2002)052[0483:LTRBTG]2.0.CO;2
  2. Flener, C. 2013. Estimating deep water radiance in shallow water: Adapting optical bathymetry modelling to shallow river environments. Roreal Environment Research 15:488-8502.
  3. Jung, Y. and Kang, S. 2002. Measuring water depth by using a combination of GPS/Echosounder. Korean Journal of Geomatics 20(4):375-381
  4. Kang, W., Choe, H., Jang, E., Ko, D., Kang, J and Yeo, H. 2021b. Determination of Stream Reach for River Environment Assessment System Using Satellite Image. Ecology and Resilient Infrastructure 8(4):179-193 https://doi.org/10.17820/ERI.2021.8.4.179
  5. Kang, W., Jang, E.K., Yang, C.Y. and Julien, P.Y. 2021a. Geospatial analysis and model development for specific degradation in South Korea using model tree data mining. Catena 200:105142.
  6. Kang, W., Lee, K. and Jang, E.K. 2022b. Evaluation and Validation of Estimated Sediment Yield and Transport Model Developed with Model Tree Technique. Applied Sciences, 12(3):1119.
  7. Kang, W., Lee, K. and Kim, J. 2022a. Prediction of Suspended Sediment Concentration Based on the Turbidity-Concentration Relationship Determined via Underwater Image Analysis. Applied Sciences 12(12):6125.
  8. Kang, W., Yang, C.Y., Lee, J. and Julien, P.Y. 2019. Sediment yield for ungauged watersheds in South Korea. KSCE Journal of Civil Engineering 23(12):5109-5120. https://doi.org/10.1007/s12205-019-0085-3
  9. Kasvi, E., Salmela, J., Lotsari, E., Kumpula, T. and Lane, S.N. 2019. Comparison of remote sensing based approaches for mapping bathymetry of shallow, clear water rivers. Geomorphology 333:180-197. https://doi.org/10.1016/j.geomorph.2019.02.017
  10. Kim, S. and Lee, Y., 2018. Present Status and Future Prospect of Satellite Image Uses in Water Resources Area. Korean Journal of Ecology and Environment 51(1):105-123 https://doi.org/10.11614/KSL.2018.51.1.105
  11. Lee, C., Go, D, Kim, D. and Choi, H. 2022. Quantitative Analysis on the Lateral Migration of an Alluvial River-Case Study- on Gopyeong Site of Naeseong Stream-.  Journal of the Korean Geomorphological Association 29(2):25-39 https://doi.org/10.16968/JKGA.29.2.25
  12. Lee, C., Kim, D.G., Hwang, S.Y., Kim, Y., Jeong, S., Kim, S. and Cho, H. 2019. Dataset of long-term investigation on change in hydrology, channel Morphology, landscape and vegetation along the Naeseong Stream (II). Ecology and Resilient Infrastructure 6(1):34-48 https://doi.org/10.17820/ERI.2019.6.1.034
  13. Lee, G.R. 2022. Changes of Riverbed Relief and Channel Landscape in Naeseongcheon River before and after Construction of Yeongju Dam. Journal of the Korean Geomorphological Association 29(1):31-44  https://doi.org/10.16968/JKGA.29.1.31
  14. Lee, G.S., and Lee, H.S. 2012. Evaluation of possibility for the classification of river habitat using imagery information. Journal of the Korean Association of Geographic Information Studies 15(3):91-102 https://doi.org/10.11108/kagis.2012.15.3.091
  15. Lee, J.B., Kim, H.J., Kim, J.H. and Wie, G.J. 2021. Water Depth and Riverbed Surveying Using Airborne Bathymetric LiDAR System-A Case Study at the Gokgyo River. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography 39(4):235-243
  16. Lee, J.O., Choi, H.W., Yun, B.Y. and Park, C.Y. 2014. Integrated geospatial information construction of ocean and terrain using multibeam echo sounder data and airborne Lidar data. Journal of the Korean Association of Geographic Information Studies 17(4): 28-39 https://doi.org/10.11108/kagis.2014.17.4.028
  17. Lee, J.W., Lee, M.S., Jung, I.K., Park, G., and Kim, S.J. 2011. Stream type classification and 2-dimensional hydraulic characteristics and bed change in Anseongcheon streams and tributaries. Journal of The Korean Association of Geographic Information Studies 14(4):77-91
  18. Lyzenga, D.R. 1978. Passive remote sensing techniques for mapping water depth and bottom features. Applied optics 17(3):379-383 https://doi.org/10.1364/AO.17.000379
  19. Moon, H.T., Lee, J.H., Yuk, J.M. and Moon, Y.I. 2020. Estimation of river water depth using UAV-assisted RGB imagery and multiple linear regression analysis. Journal of Korea Water Resources Association 53(12):1059-1070 
  20. Park, S.H. 2018. Color Analysis and Binarization of River Image for River Surveillance. The Journal of the Korea institute of electronic communication sciences, 13(1):175-186 
  21. Park, S.K., Kim, J., Lee, K.J., and Jo, M.H. 2013. Analysis of land use change within four major river areas using high-resolution air-photographs: the case of the Nakdong river basin. Journal of the Korean Association of Geographic Information Studies 16(4): 171-188 https://doi.org/10.11108/kagis.2013.16.4.171
  22. Yi, J.H., Ryu K.H., Shin, C., Baek, W.D., and Jeong, W.M. 2016. Bathymetry estimation using aerial imagery for shallow water region. Journal of The Korean Society of Hazard Mitigation 16(5):351-358