DOI QR코드

DOI QR Code

Construction of Coastal Surveying Database and Application Using Drone

  • Received : 2018.06.12
  • Accepted : 2018.06.28
  • Published : 2018.06.30

Abstract

Drone has been continuously studied in the field of geography and remote sensing. The basic researches have been actively carried out before the utilization in the field of photogrammetry. In Korea, it is necessary to study the actual way of research in accordance with the drone utilization environment. In particular, analysis on the characteristics of DSM (Digital Surface Model) generated through drone are needed. In this study, the characteristic of drone DSM as a data acquisition method was analyzed for coastal management. The coastal area was selected as the study area, and data was acquired by using drone. As a result of the study, the terrain model and the ortho image of coastal area were produced. The accuracy of UAV (Unmanned Aerial Vehicle) results were very high about 10cm at check points. However, concavo-convex shapes appeared in very flat areas such as tidal flats and roads. To correct this terrain model distortion, a new terrain model was created through data processing and the results were evaluated. If additional studies are carried out and the construction and analysis of terrain model using drone image is done, drone data for coastal management will be available.

Keywords

References

  1. Casella, E., Rovere, A., Pedroncini, A., Stark, C.P., Casella, M., Ferrari, M., and Firpo, M. (2016), Drones as tools for monitoring beach topography changes in the Ligurian Sea (NW Mediterranean), Geo-Marine Letters, Vol. 36, No. 2, pp. 151-163. https://doi.org/10.1007/s00367-016-0435-9
  2. Cho, S., Bang, E., and Kang, I. (2015), Construction of precise digital terrain model for nonmetal open-pit mine by using unmanned aerial photograph, Economic and Environmental Geology, Vol. 48, No. 3, pp. 205-212. https://doi.org/10.9719/EEG.2015.48.3.205
  3. Kim, C., Kim, H., Kang, G., Kim, G., Kim, W., Park, C., Do, J., Lee, M., Choi, S., and Park, H. (2016), Shipborne mobile LiDAR(Light Detection and Ranging) system for the monitoring of coastal changes, Economic and Environmental Geology, Vol. 49, No. 4, pp. 281-290. https://doi.org/10.9719/EEG.2016.49.4.281
  4. Lague, D., Brodu, N., and Leroux, J. (2013), Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (N-Z), ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 82, pp. 10-26. https://doi.org/10.1016/j.isprsjprs.2013.04.009
  5. Lee, G.S., Choi, Y.W., Lee, M.H., Kim, S.G., and Cho, G.S. (2016), Reconnaissance surveying for cultural assets using unmanned aerial vehicle, Journal of the Korean Cadastre Information Association, Vol. 18, No. 3, pp. 25-34.
  6. Moon, H. and Lee, W. (2016), Development and verification of a module for positioning buried persons in collapsed area, Journal of the Korea Academia-Industrial Cooperation Society, Vol. 17, No. 12, pp. 427-436.
  7. Park, J. and Um, D. (2016), Analysis of positioning performance according to the condition of multi- constellation GNSS, Journal of the Korea Academia- Industrial Cooperation Society, Vol. 17, No. 4, pp. 567- 572. https://doi.org/10.5762/KAIS.2016.17.4.567
  8. Sim, G. (2016), Metadata design based on vector type geospatial information standard for the collection and management of inundation map, Journal of the Korea Academia-Industrial Cooperation Society, Vol. 17, No. 5, pp. 42-48.
  9. Trimble Inc. (2018), Trimble UX5 aerial image solution, Trimble, http://www.trimble.com/agriculture/ux5 (last date accessed: 17 March 2018).
  10. Turner, I.L., Harley, M.D., and Drummond, C.D. (2016), UAVs for coastal surveying, Coastal Engineering, Vol. 114, pp. 19-24. https://doi.org/10.1016/j.coastaleng.2016.03.011
  11. Zhang, K., Chen, S.C., Whitman, D., Shyu, M.L., Yan, J.H., and Zhang, C. (2003), A progressive morphological filter for removing nonground measurements from airborne LiDAR data, IEEE Transaction Geoscience and Remote Sensing, Vol. 41, No. 4, pp. 872-882. https://doi.org/10.1109/TGRS.2003.810682