한국측량학회지 (Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)

  • 제38권4호
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  • Pages.345-352
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  • 2020
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  • 1598-4850(pISSN)
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  • 2288-260X(eISSN)
한국측량학회 (Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)
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갯벌지역 고해상도 지형정보 구축을 위한 항공 라이다와 UAV 데이터 통합 활용에 관한 연구

A Study on the Integration of Airborne LiDAR and UAV Data for High-resolution Topographic Information Construction of Tidal Flat

  • Kim, Hye Jin (Institute of Engineering Research, Seoul National University) ;
  • Lee, Jae Bin (Dept. of Civil Engineering, Mokpo National University) ;
  • Kim, Yong Il (Dept. of Civil and Environmental Engineering, Seoul National University)
  • 투고 : 2020.07.21
  • 심사 : 2020.08.26
  • 발행 : 2020.08.31
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초록

갯벌의 보존과 복원 및 안전사고 예방을 위해서, 갯골의 정확한 위치와 형상을 포함하는 갯벌 지형정보 구축이 필요하다. 현장 측량이 어려운 갯벌 지역에 대해, 항공 라이다 측량은 넓은 지역에 대한 정확한 위치정보 데이터의 취득이 가능하며, UAV (Unmanned Aerial Vehicle) 측량은 상대적으로 공간해상력이 우수한 데이터를 경제적으로 제공할 수 있다. 본 연구에서는 효과적인 갯벌 지형정보 구축을 위하여 항공 라이다와 UAV 포인트 클라우드 간의 데이터 통합을 수행하고, 갯골의 세부 지형을 갱신하는 방법을 제안하였다. 이를 위해 ICP (Iterative Closest Point) 알고리즘을 활용하여 두 이종 데이터를 자동 정합하고, 지면 필터링 기법인 CSF (Cloth Simulation Filtering)를 활용하여 갯골을 추출한 후, 갯골 영역에 대한 고점밀도 UAV 데이터와 평평한 지면에 대한 항공 라이다 데이터를 통합하였다. 통합된 데이터로부터 DEM (Digital Elevation Model) 및 갯골의 영역과 깊이 정보를 생성하여 대축척 갯벌 지도 제작을 위한 고해상도 지형정보를 구축하였다. 연구결과, 제안한 방법을 통해 GCP (Ground Control Point) 없이 UAV 데이터를 기하보정하고, 갯골의 세부 지형정보를 포함하면서 데이터 용량은 상대적으로 작은 통합 데이터를 생성할 수 있었다.

To preserve and restore tidal flats and prevent safety accidents, it is necessary to construct tidal flat topographic information including the exact location and shape of tidal creeks. In the tidal flats where the field surveying is difficult to apply, airborne LiDAR surveying can provide accurate terrain data for a wide area. On the other hand, we can economically obtain relatively high-resolution data from UAV (Unmanned Aerial Vehicle) surveying. In this study, we proposed the methodology to generate high-resolution topographic information of tidal flats effectively by integrating airborne LiDAR and UAV point clouds. For the purpose, automatic ICP (Iterative Closest Points) registration between two different datasets was conducted and tidal creeks were extracted by applying CSF (Cloth Simulation Filtering) algorithm. Then, we integrated high-density UAV data for tidal creeks and airborne LiDAR data for flat grounds. DEM (Digital Elevation Model) and tidal flat area and depth were generated from the integrated data to construct high-resolution topographic information for large-scale tidal flat map creation. As a result, UAV data was registered without GCP (Ground Control Point), and integrated data including detailed topographic information of tidal creeks with a relatively small data size was generated.

키워드

참고문헌

  1. Besel, P.J. and Mckay, N.D. (1992), A method for registration of 3-D shapes. IEEE Transactions of Pattern Analysis and Machine Intelligence, Vol. 14, No. 2, pp. 239-256. https://doi.org/10.1109/34.121791
  2. Chirol, C., Haigh, I.D., Pontee, N., Thompson, C.E., and Gallop, S.L. (2018), Parametrizing tidal creek morphology in mature saltmarshes using semi-automated extraction from lidar. Remote Sensing of Environment, Vol. 209, pp. 291-311. https://doi.org/10.1016/j.rse.2017.11.012
  3. Erwin, K.L. (2009), Wetlands and global climate change: the role of wetland restoration in a changing world. Wetlands Ecology and Management, Vol. 17, No. 1, pp. 71-84. https://doi.org/10.1007/s11273-008-9119-1
  4. Fagherazzi, S., Bortoluzzi, A., Dietrich, W.E., Adami, A., Lanzoni, S., Marani, M., and Rinaldo, A. (1999), Tidal networks: 1. Automatic network extraction and preliminary scaling features from digital terrain maps. Water Resources Research, Vol. 35, No. 12, pp. 3891-3904. https://doi.org/10.1029/1999WR900236
  5. Jaud, M., Grasso, F., Le Dantec, N., Verney, R., Delacourt, C., Ammann, J., Deloffre, J., and Grandjean, P., (2016), Potential of UAVs for monitoring mudflat morphodynamics (application to the seine estuary, France). ISPRS International Journal of Geo-Information, Vol. 5, No. 4, p. 50. https://doi.org/10.3390/ijgi5040050
  6. Kim, H.J., Kim, Y.I., and Lee, J.B. (2019), Extraction of tidal creeks using MCSF algorithm and UAV surveying data, Journal of Korean Society for Geospatial Information Science, Vol. 27, No. 1, pp. 43-50. (in Korean with English abstract)
  7. Kim, H., Kim, Y., and Lee, J. (2020), Tidal creek extraction from airborne LiDAR data using ground filtering techniques, KSCE Journal of Civil Engineering, Vol. 24, No. 9, pp. 2767-2783. https://doi.org/10.1007/s12205-020-2336-8
  8. Koh, C.H. and Khim, J.S. (2014), The Korean tidal flat of the Yellow Sea: Physical setting, ecosystem and management. Ocean & Coastal Management, Vol. 102, pp. 398-414. https://doi.org/10.1016/j.ocecoaman.2014.07.008
  9. Korea MOF (2017), Annual Report of the National Marine Ecosystem Monitoring. GPRN 11-1192000-000476-10, Korea Ministry of Oceans and Fisheries (Korea MOF), Sejong, pp. 55-62.
  10. Landis, J.R. and Koch, G.G. (1977), The measurement of observer agreement for categorical data. Biometrics, Vol. 33, No. 1, pp. 159-174. https://doi.org/10.2307/2529310
  11. Liu, Y., Zhou, M., Zhao, S., Zhan, W., Yang, K., and Li, M. (2015), Automated extraction of tidal creeks from airborne laser altimetry data. Journal of Hydrology, Vol. 527, pp. 1006-1020. https://doi.org/10.1016/j.jhydrol.2015.05.058
  12. Luisetti, T., Turner, R.K., Jickells, T., Andrews, J., Elliott, M., Schaafsma, M., Beaumont, N., Malcolm, S., Burdon, D., Adams, C., and Watts, W. (2014), Coastal zone ecosystem services: from science to values and decision making; a case study. Science of the Total Environment, Vol. 493, pp. 682-693. https://doi.org/10.1016/j.scitotenv.2014.05.099
  13. Martinez-Carricondo, P., Aguera-Vega, F., Carvajal-Ramirez, F., Mesas-Carrascosa, F.J., Garcia-Ferrer, A., and Perez-Porras, F.J. (2018), Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control points. International Journal of Applied Earth Observation and Geoinformation, Vol. 72, pp. 1-10. https://doi.org/10.1016/j.jag.2018.05.015
  14. Mason, D.C, Scott, T.R., and Wang, H.J. (2006), Extraction of tidal channel networks from airborne scanning laser altimetry. ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 61, No. 2, pp. 67-83. https://doi.org/10.1016/j.isprsjprs.2006.08.003
  15. Pe'eri, S. and Long, B. (2011), LIDAR technology applied in coastal studies and management. Journal of Coastal Research, Vol. 62, pp. 1-5. https://doi.org/10.2112/SI_62_1
  16. Perillo, G., Wolanski, E., Cahoon, D.R., and Hopkinson, C.S. (Eds.) (2018), Coastal Wetlands: an Integrated Ecosystem Approach, 2nd Edition, Elsevier, Amsterdam, Netherlands, pp. 221-234.
  17. Pirotti, F., Guarnieri, A., and Vettore, A. (2013), State of the art of ground and aerial laser scanning technologies for highresolution topography of the earth surface. European Journal of Remote Sensing, Vol. 46, No. 1, pp. 66-78. https://doi.org/10.5721/EuJRS20134605
  18. Provot, X. (1995, May), Deformation constraints in a mass-spring model to describe rigid cloth behaviour, Graphics interface, Canadian Information Processing Society, 17-19, May, Quebec, Canada, pp. 147-147.
  19. Teledyne Optech (2015), CZMIL Nova datasheet. Teledyne Optech, Toronto, http://info.teledyneoptech.com/acton/attachment/19958/f-02c4/1/-/-/-/-/CZMIL-Nova-Specsheet-150626-WEB.pdf (last date accessed: 1 August, 2019).
  20. Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., and Yan, G. (2016), An easy-to-use airborne LiDAR data filtering method based on cloth simulation, Remote Sensing, Vol. 8, p.501. https://doi.org/10.3390/rs8060501

피인용 문헌

  1. LiDAR를 활용한 과수 형상에 따라 선택적 방제가 가능한 지능형 방제기 vol.17, pp.4, 2020, https://doi.org/10.7839/ksfc.2020.17.4.023