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An approach of mapping quarries in Vietnam using low-cost Unmanned Aerial Vehicles

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Warianty tytułu
PL
Podejście do mapowania kamieniołomów w Wietnamie za pomocą tanich bezzałogowych statków powietrznych (dronów)
Konferencja
POL-VIET 2019 : scientific-research cooperation between Poland and Vietnam : 08–10.07.2019, Krakow
Języki publikacji
EN
Abstrakty
EN
In Vietnam, there are a huge number of quarries that are exploited and mainly provide materials to the construction sector of the country. However, most of the quarries are operating without topographic plans due to a lack of surveying activities. This paper introduces an approach of using low-cost UAVs to produce digital surface models which in turn are used to draw topographic maps of quarries in Vietnam. For assessments of accuracy, safety, and working efficiency, four quarries different in terrain conditions, namely Luong Son, Long Son, Nui Nho, and Nui Dai were selected as the study areas. Ground control points were established in each area by using GNSS/RTK for camera calibration and accuracy assessment. The accuracy of DSM was assessed using the root-mean-square error (RMSE) in X, Y, Z, XY, and XYZ components. Capturing images from each site were processed by using Agisoft®PhotoScan Professional 1.5.2. The results showed that all the DSM models of the four areas have high accuracy, RMSE on the checked GCPs ranges from 1.0 to 9.0 cm, from 1.2 to 5.0 cm, from 4.4 to 13.4 cm, from 1.6 to 10.3 cm, and from 4.9 to 16.9 cm for X, Y, Z, XY, XYZ components, respectively. We concluded that the low-cost UAV based mapping technology can guarantee the accuracy of DSMs, the safety of UAV flying, and the efficiency of surveying working simultaneously when using in quarries.
Słowa kluczowe
Rocznik
Strony
249--263
Opis fizyczny
Bibliogr. 17 poz., tab., zdj.
Twórcy
  • Hanoi University of Mining and Geology, Department of Mine Surveying, Hanoi, Vietnam
  • Hanoi University of Mining and Geology, Department of Surface Mining, Hanoi, Vietnam
  • Mine Surveying, Krakow, Poland
  • Hanoi University of Mining and Geology, Department of Mine Surveying, Hanoi, Vietnam
autor
  • Hanoi University of Mining and Geology, Department of Mine Surveying, Hanoi, Vietnam
Bibliografia
  • 1. Tran, X.H. and A.T. Nguyen. Innovation, Modernization, exploitation, screening, production in order to achieve the sustainable development of Coal and Minerals Industry in Vietnam National Mining Science and Technology Congress. 2011. Nha Trang, Vietnam.
  • 2. Lee Sungjae and C. Yosoon, opographic survey at small-scale open-pit mines using a popular rotary-wing unmanned aerial vehicle (drone). Tunnel & Underground Space, 2015. 25.
  • 3. Tien Bui, D., et al. Lightweight Unmanned Aerial Vehicle and Structure-from-Motion Photogrammetry for Generating Digital Surface Model for Open-Pit Coal Mine Area and Its Accuracy Assessment. 2018. Cham: Springer International Publishing.
  • 4. Jonathan L. Carrivick, Mark W. Smith, and D.J. Quincey, Structure from Motion in the Geosciences. 2016: Wiley.
  • 5. Siebert, S. and J. Teizer, Mobile 3D mapping for surveying earthwork projects using an Unmanned Aerial Vehicle (UAV) system. Automation in Construction, 2014. 41: p. 1-14.
  • 6. Cryderman, C., S.B. Mah, and A. Shufletoski, Evaluation of UAV Photogrammetric Accuracy for Mapping and Earthworks Computations. GEOMATICA, 2014. 68(4): p. 309-317.
  • 7. Clapuyt, F., V. Vanacker, and K. Van Oost, Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms. Geomorphology, 2016. 260: p. 4-15.
  • 8. Park, M.H., S.G. Kim, and S.Y. Choi, The study about building method of geospatial informations at construction sites by unmanned aircraft system (UAS). Journal of the Korean Cadastre Information, 2013. 15(1): p. 145-156.
  • 9. Birk, A., et al.
  • 10. Niethammer, U., et al., UAV-based remote sensing of the Super-Sauze landslide: Evaluation and results. Engineering Geology, 2012. 128: p. 2-11.
  • 11. Zarco-Tejada, P.J., et al., Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods. European Journal of Agronomy, 2014. 55(C): p. 89-99.
  • 12. ICAO, Unmanned Aircraft Systems (UAS), I.C.A. Organization, Editor. 2011: ICAO:Montreal, QC, Canada.
  • 13. ICAO, Manual on Remotely Piloted Aircraft Systems (RPAS), I.C.A. Organization, Editor. 2015: ICAO: Montreal, QC, Canada.
  • 14. Stöcker, E.C., et al., Review of the current state of UAV regulations. Remote sensing, 2017. 9(5): p. urn:issn:2072-4292.
  • 15. Ajayi, O.G., et al., Generation of accurate digital elevation models from UAV acquired low percentage overlapping images. International Journal of Remote Sensing, 2017. 38(8-10): p. 3113-3134.
  • 16. DJI, Phantom 4 Pro Visionary intelligence and elevated imagination, https://www.dji.com/phantom-4-pro. 2017.
  • 17. Agüera-Vega, F., F. Carvajal-Ramírez, and P. Martínez-Carricondo, Accuracy of Digital Surface Models and Orthophotos Derived from Unmanned Aerial Vehicle Photogrammetry. Journal of Surveying Engineering, 2016: p. 04016025.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b105e9e4-6f33-4f6d-beaa-c88da37b444b
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