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회전익 UAS 영상기반 고밀도 측점자료의 위치 정확도 평가

Assessing the Positioning Accuracy of High density Point Clouds produced from Rotary Wing Quadrocopter Unmanned Aerial System based Imagery

  • 이용창 (인천대학교 도시과학대학 도시환경공학부)
  • Lee, Yong Chang (Division of Urban & Environmental Engineering, College of Urban Sciences, Incheon National University)
  • 투고 : 2015.04.27
  • 심사 : 2015.06.02
  • 발행 : 2015.06.30

초록

최근, 무인항공촬영시스템(UAV, UAS, 또는 드론)은 자료취득을 위한 플랫폼 및 측정기기로서 사진측량의 응용분야, 특히 고밀도 측점자료(HDPC : High Density Point Clouds) 구성에 큰 관심이 모아지고 있다. 본 연구는 저가회전익 UAS 영상에 의한 시험대상지 지표면의 고밀도 측점자료를 구성하고 위치 정확도를 평가한 내용이다. 정확도 평가는 62개의 지상 검사점에 대한 Network RTK GNSS 측량 결과를 기준으로 UAS 기반 HDPC 모형의 좌표와 비교 검토하였다. 연구결과, 작업지역 정사영상 내, 검사점의 평면 및 수직 좌표성분의 평균제곱근오차(RMSE)는 각각 ${\sigma}_H={\pm}0.102m$${\sigma}_V={\pm}0.209m$, 수직 좌표성분의 최대오차는 0.570m로서 '영상지도제작 작업규정'에 따른 축척 1:1000(출력 시, 평면위치오차 1m)의 정사영상모자익 제작이 가능하였다. 또한, 격자규격 $1m{\times}1m$, 수치지도축척 1:1000의 수치표고모델을 제작할 경우, '항공레이저측량 작업규정'제한 기준에는 약간 미흡하였지만, 소규모지역을 대상으로 회전익 무인항공촬영시스템에 의한 축척 1:1000~1:2500의 정사영상 및 수치표고모델 제작의 가능성을 확인할 수 있었다.

Lately, Unmanned Aerial Vehicles(UAV), Unmanned Aerial Systems(UAS) or also often known as drones, as a data acquisition platform and as a measurement instrument are becoming attractive for many photogrammetric surveying applications, especially generation of the high density point clouds(HDPC). This paper presents the performance evaluation of a low-cost rotary wing quadrocopter UAS for generation of the HDPC in a test bed environment. Its performance was assessed by comparing the coordinates of UAS based HDPC to the results of Network RTK GNSS surveying with 62 ground check points. The results indicate that the position RMSE of the check points are ${\sigma}_H={\pm}0.102m$ in Horizonatal plane, and ${\sigma}_V={\pm}0.209m$ in vertical, and the maxium deviation of Elevation was 0.570m within block area of ortho-photo mosaic. Therefore the required level of accuracy at NGII for production of ortho-images mosaic at a scale of 1:1000 was reached, UAS based imagery was found to make use of it to update scale 1:1000 map. And also, since this results are less than or equal to the required level in working rule agreement for airborne laser scanning surveying of NGII for Digital Elevation Model generation of grids $1m{\times}1m$ and 1:1000 scale, could be applied with production of topographic map and ortho-image mosaic at a scale of 1:1000~1:2500 over small-scale areas.

키워드

참고문헌

  1. Agisoft, 2015, Agisoft Photoscan professional version, http://www.agisoft.com
  2. DJI, 2015, Phantom 2 Series, www.dji.com
  3. Gehrke, R., Greiwe, A., Spreckels, V., and Schlienkamp, A., 2013, Aspects of DEM generation from UAS imagery, ISPRS, Vol. XL-1/W2, pp. 163-167.
  4. Haala, N. and Rothermel, M., 2012, Dense multiple stereo matching of highly overlapping imagery, ISPRS, Volume XXXIX-B1, XXII ISPRS Congress, pp. 387-392.
  5. Han, S. H., 2014a, Development and estimation of low price small autopilot UAS for geo-spatial information aquisition, Journal of the Korean Society, Vol. 34, No. 4, pp. 1343-1351.
  6. Han, S. H., 2014b, The development of a multisensor payload for a micro UAV and generation of ortho-images, Korean Society of Civil Engineers, Vol. 34, No. 5, pp. 1645-1653. https://doi.org/10.12652/Ksce.2014.34.5.1645
  7. Harwin, S., and Lucieer, A., 2012, Assessing the accuracy of georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle imagery, Remote Sensing, Vol 4, No. 6, pp. 1573-1599. https://doi.org/10.3390/rs4061573
  8. Hirschmuller, H., 2005, Accurate and efficient stereo processing by semi-global matching and mutual information, in Proceedings of the IEEE conference on computer vision and pattern recognition, Vol. 2, pp. 807-814.
  9. Kannala, U., and Brandt S., 2004, A generic camera model and calibration method for conventional, wide-angle, and fish-eye lenses, Cambridge, pp. 10-13.
  10. Kim, D. I., Song, Y. S., Kim, G. H., and Kim, C. W., 2014, A study on the application of UAV for Korean Land Monitoring, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 32, No. 1, pp. 29-38. https://doi.org/10.7848/ksgpc.2014.32.1.29
  11. Lee, I. S., Lee, J. O., Kim, S. J., and Hong, S. H., 2013, Orthophoto accuracy assessment of ultra-light fixed wing UAV photogrammetry techniques, Journal of the Korean Society of Civil Engineers, Vol. 33, No. 6, pp. 2593-2600. https://doi.org/10.12652/Ksce.2013.33.6.2593
  12. The National Geographic Information Institute of South Korea(NGII), 2013, Working rule agreement for airborne photogrammetry.
  13. The National Geographic Information Institute of South Korea,(NGII), 2012, Working rule agreement for airborne laser scanning surveying.
  14. The National Geographic Information Institute of South Korea,(NGII), 2012, Working rule agreement for orthoimage mosaic generation.
  15. The National Geographic Information Institute of South Korea,(NGII), 2010, Working rule agreement for digital-map generation.
  16. Park, H. G., 2014, Reservoir Disaster Monitoring using Unmanned Aerial Photogrammetry, Journal of the Korean Society for Geospatial Information System, Vol. 22, No. 4, pp. 143-149. https://doi.org/10.7319/kogsis.2014.22.4.143
  17. Park, Y. J., and Jung, K. Y., 2014, Availability Evaluation for Generation of Geospatial Information using Fixed Wing UAV, Journal of the Korean Society for Geospatial Information System, Vol. 22, No. 4, pp. 159-164. https://doi.org/10.7319/kogsis.2014.22.4.159
  18. Remondino, F., Spera, M. G., Nocerino, E., Menna, F. and Nex, F., 2014, State of the art in high density image matching, The Photogrammetric Record, Vol. 29, Issue 146, pp. 144-166. https://doi.org/10.1111/phor.12063
  19. Tellidis, I., and Levin, E., 2014, Photogrammetric image acquisition with small unmanned aerial systems, ASPRS 2014 annual conference, Louisville, Kentucky.
  20. UAV-g, 2015, Unmanned Aerial Vehicles in Geomatics, http://www.uav-g.org
  21. Xu, Z., Wu, L., Shen, Y., Li, F., Wang, Q., and Wang, R., 2014, Tridimensional reconstruction applied to cultural heritage with the use of camera-equipped UAV and terrestrial laser scanner, Remote Sensing, pp. 10413-10434.
  22. Yun, B. Y., and Lee, J. O., 2014, A study on application of the UAV in Korea for integrated operation with spatial information, Journal of the Korean Society for Geospatial Information System, Vol. 22, No. 2, pp. 3-9. https://doi.org/10.7319/KOGSIS.2014.22.2.003

피인용 문헌

  1. 드론 사진측량과 지적정보를 융합한 하천부지 점용 조사방법 vol.47, pp.2, 2015, https://doi.org/10.22640/lxsiri.2017.47.2.135
  2. UAS 및 지상 LiDAR 융합기반 건축물의 3D 재현 vol.7, pp.2, 2015, https://doi.org/10.22645/udi.2018.12.30.053
  3. 네트워크 RTK 무인기의 항공삼각측량 정확도 평가 vol.38, pp.6, 2015, https://doi.org/10.7848/ksgpc.2020.38.6.663
  4. A Study on 3D Model Construction by Controlling Unmanned Aerial Vehicle of Camera Angle vol.21, pp.2, 2021, https://doi.org/10.9798/kosham.2021.21.2.149