DOI QR코드

DOI QR Code

Accuracy Analysis of Coastal Area Modeling through UAV Photogrammetry

무인항공측량을 통한 해안 지형 모델링의 정확도 분석

  • 최경아 (서울시립대학교 공간정보공학과) ;
  • 이임평 (서울시립대학교 공간정보공학과)
  • Received : 2016.11.04
  • Accepted : 2016.12.23
  • Published : 2016.12.31

Abstract

Coastal erosion happens frequently in many different types. To control coastal erosion zone effectively and establish response plans, we need to accumulate data indicating topography changes through monitoring the erosion situation continuously. UAV photogrammetric systems, which can fly autonomously at a low altitude, are recommended as an economical and precision means to monitor the coastal zones. In this study, we aim to verify the accuracy of the generated orthoimages and DEM as a result of processing the UAV data of a coastal zone by comparing them with various reference data. We established a verification routine and examined the possibilities of applying the UAV photogrammetric systems to monitoring coastal erosion by checking the analyzed accuracy by the routine. As a result of verifying the generated the geospatial information from acquired data under various configurations, the horizontal and vertical accuracy (RMSE) were about 2.7 cm and 4.8 cm respectively, which satisfied 5 cm, the accuracy required for coastal erosion monitoring.

빈번하게 다양한 유형으로 발생하는 해안 침식 현상에 대하여 지속적인 모니터링을 통하여 변화 자료를 축적함으로써 효과적으로 침식 지역을 관리하고 대응 방안을 수립할 수 있다. 경제적으로 정밀한 해안지역 모니터링을 수행하기 위한 수단으로써 저고도 자율 비행이 가능한 드론사진측량 시스템이 제안되고 있다. 본 연구에서는 해안 지역에서 드론 시스템으로부터 취득된 데이터를 처리하여 생성된 정사영상과 수치표고모델(Digital Elevation Model: DEM)을 다양한 기준 데이터와 비교함으로써 정확도를 분석하고자 한다. 비교 검증 방법을 수립하고, 이에 따라 분석된 정확도를 확인함으로써 해안 침식 모니터링에 드론 사진측량의 활용 가능성을 검증하였다. 기준 데이터와 다양한 조건에서 취득된 드론 영상으로부터 생성된 공간정보를 비교한 결과, 수평 및 수직 정확도(RMSE)는 각각 약 2.9 cm와 4.8 cm이었으며, 이는 해안 침식 모니터링의 요구정확도인 5 cm를 거의 만족시키는 수준으로 판단된다.

Keywords

References

  1. AUVSI News, Lockheed Indago Monitors Coastal Erosion, 2015.8.12.
  2. Bradley, D.M., M.A. Cavidson, and D.A. Huntley, 2001. Measurements of the response of a coastal inlet using video monitoring techniques, Marine Geology, 175: 251-272. https://doi.org/10.1016/S0025-3227(01)00144-X
  3. ChinaDaily, Drone bases will monitor seacoasts, 2012.10.21.
  4. Gangwon News, Survey on Coastal Erosion, 2016.2.29.
  5. Jung, J., 2016. Major Implementation Tasks for Methodical Management of Coastal Erosion Management Areas, Proc. of the Korean Society for Marine Environment & Energy Conference, pp. 29-29.
  6. Kim, K.H., 2011. Beach Erosion as a Coastal Disaster, The Journal of the Korean Society of Civil Engineers, 59(11): 40-45 (in Korean with English abstract).
  7. Kim, T., 2006. Bottom Topography Observation in the International Zone Using a Camera Monitoring System, The Journal of Korean Society of Coastal and Ocean Engineers, 18(1): 63-68 (in Korean with English abstract).
  8. Ministry of Land, Transport and Maritime Affairs, 2008. Research Report: the System Construction for Coastal Erosion Monitoring.
  9. Park, J., 2013. Monitoring of Sediment Transports on Coatal Wetland in Taeanhaean National Park, Proc. of the Korean Society of Environment and Ecology Conference, vol. 2, pp. 22-23.
  10. Stefan, G.J.A., I.L. Tumer, T.D.T Dronkers, M. Caljouw, and L. Nipius, 2003. A video-based technique for mapping intertidal beach bathymetry, Coastal Engineering, 49: 275-289. https://doi.org/10.1016/S0378-3839(03)00064-4
  11. Texas A&M AgriLife Today, Drones Survey Waning Red Tide at South Padre Island, 2015.10.22.
  12. The New York Times, Drones on a Different Mission, 2014.7.21.
  13. Tsuchiya, Y., Y. Kawata, T. Yamashita, T. Shibano, M. Kawasaki, and S. Habara, 1992. Sandy beach stabilization: Preservation of Shirarahama beach, Wakayama, Proc. of the 23rd International Conference on Coastal Engineering, vol. 3, pp. 3426-3439.
  14. Nathaniel, G.P., and R.A. Holman, 1997. Intertidal beach profile estimation using video images, Marine Geology, 140: 1-24. https://doi.org/10.1016/S0025-3227(97)00019-4

Cited by

  1. 무인항공시스템을 이용한 도시공간 지형모델 생성 및 정확도 평가 vol.17, pp.5, 2016, https://doi.org/10.12815/kits.2018.17.5.117
  2. 한국의 연안원격탐사 활용 vol.36, pp.2, 2016, https://doi.org/10.7780/kjrs.2020.36.2.2.1
  3. 다중 원격탐사 플랫폼 기반 곰소만 갯벌 정밀 지형변화 연구 vol.36, pp.2, 2020, https://doi.org/10.7780/kjrs.2020.36.2.2.4
  4. 고해상도 다분광 인공위성영상자료 기반 시화 간척지 갯골 변화 양상 분석 vol.36, pp.6, 2016, https://doi.org/10.7780/kjrs.2020.36.6.2.10
  5. Exploring RPAS potentiality using a RGB camera to understand short term variation on sandy beaches vol.210, pp.None, 2016, https://doi.org/10.1016/j.catena.2021.105949