Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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3D Model Construction and Evaluation Using Drone in Terms of Time Efficiency

시간효율 관점에서 드론을 이용한 3차원 모형 구축과 평가

  • Son, Seung-Woo (Department of Land and Water Environment Research, Korea Environment Institute) ;
  • Kim, Dong-Woo (Department of Land and Water Environment Research, Korea Environment Institute) ;
  • Yoon, Jeong-Ho (Department of Land and Water Environment Research, Korea Environment Institute) ;
  • Jeon, Hyung-Jin (Department of Land and Water Environment Research, Korea Environment Institute) ;
  • Kang, Young-Eun (Research Department, Site Planning Co) ;
  • Yu, Jae-Jin (Department of Land and Water Environment Research, Korea Environment Institute)
  • 손승우 (한국환경정책.평가연구원) ;
  • 김동우 (한국환경정책.평가연구원) ;
  • 윤정호 (한국환경정책.평가연구원) ;
  • 전형진 (한국환경정책.평가연구원) ;
  • 강영은 ((주)싸이트플래닝 건축사사무소) ;
  • 유재진 (한국환경정책.평가연구원)
  • Received : 2018.08.22
  • Accepted : 2018.11.02
  • Published : 2018.11.30
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Abstract

In a situation where the amount of bulky waste needs to be quantified, a three-dimensional model of the wastes can be constructed using drones. This study constructed a drone-based 3D model with a range of flight parameters and a GCPs survey, analyzed the relationship between the accuracy and time required, and derived a suitable drone application technique to estimate the amount of waste in a short time. Images of waste were photographed using the drone and auto-matching was performed to produce a model using 3D coordinates. The accuracy of the 3D model was evaluated by RMSE calculations. An analysis of the time required and the characteristics of the top 15 models with high accuracy showed that the time required for Model 1, which had the highest accuracy with an RMSE of 0.08, was 954.87 min. The RMSE of the 10th 3D model, which required the shortest time (98.27 min), was 0.15, which is not significantly different from that of the model with the highest accuracy. The most efficient flight parameters were a high overlapping ratio at a flight altitude of 150 m (60-70% overlap and 30-40% sidelap) and the minimum number of GCPs required for image matching was 10.

대형폐기물량을 산정해야 하는 상황에서 드론을 이용하여 폐기물의 3차원 모형을 구축하여 폐기물의 정량적인 양을 산출할 수 있다. 필요에 따라서 단시간에 폐기물량을 산정해야 하는 경우가 있다. 본 연구에서는 다양한 비행변수와 지상기준점 측량을 통해 드론 기반의 3차원 모형을 구축하고 정확도와 소요되는 시간의 관계를 분석하였으며 단시간에 폐기물량 산정을 위한 적절한 드론 활용 기법을 도출하고자 하였다. 드론을 이용하여 폐기물의 영상을 촬영하여 자동정합하고 3차원 좌표를 가지는 모형을 생성하였다. 3차원 모형의 정확도는 RMSE(Root Mean Square Error) 계산을 통해 평가하였다. 총 49개 모형의 RMSE는 최고 0.08부터 최저 124.75로 나타났다. 정확도가 높은 상위 15개 모형의 소요시간과 그 특성을 분석한 결과, RMSE가 0.08로 영상의 정확도가 가장 높은 1번 모형의 소요시간이 954.87분으로 나타났다. 또한 소요시간이 98.27분으로 가장 짧은 10번 3차원 모형의 RMSE는 0.15로써 정확도가 가장 높은 모형과 큰 차이가 없음을 확인하였다. 가장 효율적인 드론 비행변수는 비행고도 150m에서 높은 촬영중복도(종중복도 60-70%, 횡중복도 30-40%)이며 영상정합에 필요한 지상기준점 개수는 최소 10개 이상인 것으로 나타났다. 본 연구의 결과는 드론을 활용하여 신속하고 효율적인 폐기물량 산정하는데 기초자료로 활용될 수 있다.

Keywords

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Fig. 1. Study area

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Fig. 3. Digital Surface Model using Drone (1∼4: High Accuracy / 46∼49: Low Accuracy)

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Fig. 2. (a) is Ortho image using drone. (b) are Ortho image and 3D model zoomed in version.

Table 1. Study Materials

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Table 2. Accuracy and Paramater of 3D Model Constructed with Drone

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Table 3. Time spent building 3D model (top 15 with high accuracy)

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References

  1. Rock, G., Ries, J. B. & Udelhoven, T, "Sensitivity analysis of UAV-photogrammetry for creating digital elevation models (DEM). In Proceedings of Conference on Unmanned Aerial Vehicle in Geomatics.
  2. Uysal, M., Toprak, A. S., & Polat, N, "DEM generation with UAV Photogrammetry and accuracy analysis in Sahitler hill", Measurement 73, pp. 539-543, 2015. https://doi.org/10.1016/j.measurement.2015.06.010
  3. S. A. Rhee, T. J. Kim ,J. I. Kim, M. C. Kim & H. J. Chang, "DSM Generation and Accuracy Analysis from UAV Images on River-side Facilities", Korean Journal of Remote Sensing 31(2), pp. 183-191, 2015. https://doi.org/10.7780/kjrs.2015.31.2.12
  4. G. S. Lee, Y. W. Choi & J. J. Lee, "Building of 3D Terrain Modeling and Evaluation of Location Accuracy using UAV in Beach Area", Korean Association of Cadastre Information 18(2), pp. 207-216, 2016.
  5. Coveney, S., & Roberts, K, "Lightweight UAV digital elevation models and orthoimagery for environmental applications: data accuracy evaluation and potential for river flood risk modelling", International journal of remote sensing 38(8-10), pp. 3159-3180, 2017. https://doi.org/10.1080/01431161.2017.1292074
  6. Perez-Alberti, A., & Trenhaile, A. S, "An initial evaluation of drone-based monitoring of boulder beaches in Galicia, north-western Spain", Earth Surface Processes and Landforms 40(1), pp. 105-111, 2015. https://doi.org/10.1002/esp.3654
  7. J. J. Yu, H. S. Park, Y. J. Yang & D. H. Jang, "Assessing the Applicability of UAS for Detecting Geomorphological Changes in Coastal Areas: A Case Study in the Baramarae Beach in Anmyeon-do", Journal of the Korean geomorphological association 23(4), pp. 113-126, 2016. https://doi.org/10.16968/JKGA.23.4.113
  8. S. W. Son, J. J. Yu, H. J. Jeon, S. H. Lim, Y. E. Kang, & J. H. Yoon, "Investigation of Measurement Feasibility of Large-size Wastes Based on Unmanned Aerial System", Korean Journal of Remote Sensing 33(5), pp. 809-820, 2017 https://doi.org/10.7780/kjrs.2017.33.5.3.5
  9. Udin, W. S., & Ahmad, A, "Assessment of photogrammetric mapping accuracy based on variation flying altitude using unmanned aerial vehicle", In IOP Conference Series: Earth and Environmental Science 18(1), pp. 012027, 2014. https://doi.org/10.1088/1755-1315/18/1/012027
  10. Mesas-Carrascosa, F. J., Notario Garcia, M. D., Merono de Larriva, J. E., &Garcia-Ferrer, A, "An analysis of the influence of flight parameters in the generation of unmanned aerial vehicle (UAV) orthomosaicks to survey archaeological areas", Sensors 16(11), pp. 1838, 2016. https://doi.org/10.3390/s16111838
  11. Aguera-Vega, F., Carvajal-Ramirez, F., & Martinez-Carricondo, P, "Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle", Measurement 98, pp. 221-227, 2017. https://doi.org/10.1016/j.measurement.2016.12.002
  12. Tomastik, J., Mokros, M., Salon, S., Chudy, F., &Tunak, D, "Accuracy of photogrammetric UAV-based point clouds under conditions of partially-open forest canopy", Forests 8(5), pp. 151, 2017. https://doi.org/10.3390/f8050151
  13. Yu Jae Jin, Park Hyun-su, Kim dong woo, Jeong Ho Yoon, & Seung Woo Son, "Assessing the Applicability of Sea Cliff Monitoring Using Multi-Camera and SfM Method", Journal of the Korean geomorphological association 25(1) pp. 67-80, 2018. https://doi.org/10.16968/JKGA.25.1.67