Dergiler / Türkiye Jeoloji Bülteni / 2026 / Cilt: 60 Sayı: 2

3D Multi-view Stereo Modelling of an Open Mine Pit Using a Lightweight UAV

Sayfa
223–242
Yayın Tarihi
2017-04-01
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

SfM-MVS is a cost-effective, rapid and promising technique for digital mapping, modelling and monitoring in various spatial scales of Geology.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Digital elevation models have been evolved in decades, their resolution and accuracy have improved vividly.
📊
Temel Bulgular & Veri:Improvements in stereo-photogrammetry did not decelerate.
💡
Sonuç & Katkı:SfM-MVS is a cost-effective, rapid and promising technique for digital mapping, modelling and monitoring in various spatial scales of Geology.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:3D modelling · Aerial imaging · DEM

Özet

Digital elevation models have been evolved in decades, their resolution and accuracy have improved vividly. Geological, structural and geomorphological benefits of those high-quality digital elevation models enhanced the quality of the research and engineering and unfold the visibility of the data. Modern techniques such as laser scanners provide a quantum leap on digital modelling, however the cost of those methods limits their widespread usage. Improvements in stereo-photogrammetry did not decelerate. On the contrary, the evolution of Structure from Motion–Multi-view stereo-photogrammetry (SfM-MVS) method is accelerated by the continuous developments in digital photography and computer vision technologies. We have used a lightweight drone to acquire digital aerial photographs of an open mine pit for an ultimate purpose of modelling the terrain using SfM-MVS procedure. We have been able to derive a high resolution (0.3 m/pixel) DEM and a very high resolution (0.04 m/pixel) orthorectified aerial image. Both datasets are representing the topography with high sample point densities. Elevation model dataset has been compared with the regular topographic point measurements of the mine pit and the accuracy of the aerially derived model have been investigated. Sources of modelling errors, the effect of temporal physical changes in the terrain, effect and importance of geo-referencing have been discussed in detail. SfM-MVS is a cost-effective, rapid and promising technique for digital mapping, modelling and monitoring in various spatial scales of Geology.

🔖

Bu Makaleye Atıf Yap

Ulusoy, İ., Şen, E., Tuncer, A., Sönmez, H., Bayhan, H. (2017). 3D Multi-view Stereo Modelling of an Open Mine Pit Using a Lightweight UAV. Türkiye Jeoloji Bülteni, Cilt: 60 Sayı: 2, 223–242. https://doi.org/10.25288/tjb.303032

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (43)

  1. Abdullah, Q., Bethel, J., Hussain, M., Munjy, R., 2013. Photogrammetric project and mission planning. In Manual of Photogrammetry, in: McGlone, J.C. (Ed.), American Society for Photogrammetry and Remote Sensing: Bethesda. MD, pp. 1187–1220.
  2. Agisoft [WWW Document], 2016. URL http://www.agisoft.com/ (accessed 1.30.16).
  3. Barazzetti, L., Scaioni, M., Remondino, F., 2010. Orientation and 3D modelling from markerless terrestrial images: Combining accuracy with automation. The Photogrammetric Record 25, 356–381. doi:10.1111/j.1477 9730.2010.00599.x
  4. Bemis, S.P., Micklethwaite, S., Turner, D., James, M.R., Akciz, S., Thiele, S.T., Bangash, H.A., 2014. Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology. Journal of Structural Geology 69, 163–178. doi:10.1016/j.jsg.2014.10.007
  5. Bennet, M.J., 2015. Evaluating the Creation and Preservation Challenges of Photogrammetry-based 3D Models. UConn Libraries Published Works. Paper 52.
  6. Brothelande, E., Lénat, J.-F., Normier, A., Bacri, C., Peltier, A., Paris, R., Kelfoun, K., Merle, O., Finizola, A., Garaebiti, E., 2015. Insights into the evolution of the Yenkahe resurgent dome (Siwi caldera, Tanna Island, Vanuatu) inferred from aerial high-resolution photogrammetry. Journal of Volcanology and Geothermal Research 299, 78.
  7. Burns, J.H.R., Delparte, D., Gates, R.D., Takabayashi, M., 2015. Integrating structure-from-motion photogrammetry with geospatial software as a novel technique for quantifying 3D ecological characteristics of coral reefs. PeerJ 3:e1077.doi:10.7717/peerj.1077
  8. Calakli, F., Ulusoy, O.A., Restrepo, M., Taubin, G., Mundy, L.J., 2012. High resolution surface reconstruction from multi-view aerial imagery [WWW Document]. Second International Conference on 3D Imaging, Modeling, Processing,
  9. Visualization and Transmission (3DIMPVT).doi:10.1109/3DIMPVT.2012.54
  10. Esposito, S., Fallavollita, P., Wahbeh, W., Nardinocchi, C., Balsi, M., 2014. Performance evaluation of UAV photogrammetric 3D reconstruction, in: Geoscience and Remote Sensing Symposium (IGARSS). IEEE, Quebec City, QC, pp. 4788–4791. doi:10.1109/IGARSS.2014.6947565
  11. Etimaden [WWW Document], 2016. URL http://www.etimaden.gov.tr/tr/page/uretim-emet (accessed 1.29.16).
  12. Fan, L., Smethurst, J.A., Atkinson, P.M., Powrie, W. 2015. Error in target-based georeferencing and registration in terrestrial laser scanning. Computers and Geosciences 83, 54-64.
  13. Forte, M., 2014. 3D ARCHAEOLOGY New Perspectives and Challenges – The Example of Çatalhöyük. Journal of Eastern Mediterranean Archaeology and Heritage Studies 2(1).
  14. Furukawa, Y., Ponce, J., 2010. Accurate, dense, and robust multiview stereopsis. IEEE transactions on pattern analysis and machine intelligence. 8.
  15. Gimenez, R., Marzolff, I., Campo, M., Seeger, M., Ries, J., Casali, J., Alvarez-Mozos, J., 2009. Accuracy of
  16. Gomez, C., Purdie, H., 2014. High-resolution monitoring of glacier and valley with combined ground- and UAV-based Photogrammetry: Study of fox valley, New Zealand, in: IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES). Indonesia.
  17. Gong, Y., Wang, Y.-F., 2011. Multi-view stereo point clouds visualization. Lecture Notes in Computer Science 281–290. doi:10.1007/978-3-642-240287_26
  18. Granshaw, S.I., 1980. Bundle adjustment methods in engineering photogrammetry. The Photogrammetric Record 10, 181–207. doi:10.1111/j.1477-9730.1980.tb00020.x
  19. Haukaas, C., 2015. New opportunities in digital archaeology: The use of low-cost Photogrammetry for 3D documentation of archaeological objects from Banks island, NWT (Electronic Thesis and Dissertation Repository No. Paper 2117.).
  20. Helvacı, C., 2015. Geological Features of Neogene Basins Hosting Borate Deposits: An Overview of Deposits and Future Forecast, Turkey. Bulletin of The Mineral Research and Exploration 151, 169–215. doi:10.19111/bmre.05207
  21. James, M.R., Robson, S., 2012. Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application. Journal of Geophysical Research 117, F03017. doi:10.1029/2011jf002289
  22. James, M.R., Robson, S., 2014. Mitigating systematic error in topographic models derived from UAV and ground-based image networks. Earth Surface Processes and Landforms 39, 1413–1420. doi:10.1002/esp.3609
  23. James, M.R., Varley, N., 2012. Identification of structural controls in an active lava dome with high resolution DEMs: Volcán de Colima, Mexico. Geophysical Research Letters 39, L22303. doi:10.1029/2012gl054245
  24. Javernick, L., Brasington, J., Caruso, B., 2014. Modeling the topography of shallow braided rivers using structure from motion photogrammetry. Geomorphology 213, 166–182. doi:10.1016/j.geomorph.2014.01.006
  25. Kraus, K., 1993. Photogrammetry, Vol. 1: Fundamentals and standard processes. Dümmlers.
  26. Lewis, A., Hilley, G.E., Lewicki, J.L., 2015. Integrated thermal infrared imaging and structure-frommotion
  27. Lowe, D.G., 2004. Distinctive image features from scale-invariant Keypoints. International Journal of Computer Vision 60, 91–110. doi:10.1023/b:visi.0000029664.99615.94
  28. Mackenzie, D., Elliott, J.R., Altunel, E., Walker, R.T., Kurban, Y.C., Schwenninger, J.-L., Parsons, B., 2016. Seismotectonics and rupture process of the MW 7.1 2011 Van reverse-faulting earthquake, eastern Turkey, and implications for hazard in regions of distributed shortening. Geophysical Journal International, 206 (1), 501-524.
  29. McLeod, T., Samson, C., Labrie, M., Shehata, K., Mah, J., Lai, P., Wang, L., Elder, J.H., 2013. Using video acquired from an unmanned aerial vehicle (UAV) to measure fracture orientation in an open-PIT mine. Geomatica, 67(3), 173-180.
  30. Niethammer, U., Rothmund, S., James, M.R., Travelletti, J., Joswig, M., 2010. UAV-Based Remote Sensing of Landslides. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Commission V Symposium, Newcastle upon Tyne, UK. Vol. XXXVIII, Part 5.
  31. Remondino, F., 2006. Detectors and descriptors for photogrammetric applications. International Archives of the Photogrammetry, Remote Sensing
  32. and Spatial Information Sciences: Symposium of ISPRS Commission III Photogrammetric Computer Vision PCV ’06, Int. Soc. for Photogramm. and Remote Sens., Bonn, Germany. 36, 49–54.
  33. Rosnell, T., Honkavaara, E., 2012. Point cloud generation from aerial image data acquired by a Quadrocopter type micro unmanned aerial vehicle and a digital still camera. Sensors 12, 453–480. doi:10.3390/s120100453
  34. Shahbazi, M., Sohn, G., Théau, J. and Ménard, P., 2015. UAV-based point cloud generation for openpit mine modelling. The international archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol XL-1W4, 313-320.
  35. Skarlatos, D., Kiparissi, S., 2012. Comparison of Laser Scanning, Photogrammetry and SfM-MVS Pipeline Applied in Structures and Artificial Surfaces, in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXII ISPRS Congress. Melbourne, Australia.
  36. Tong, X., Liu, X., Chen, P., Liu, S., Jin, Y., Li, L., Xie, H., Luan, K., 2015. Integration of UAV-Based Photogrammetry and terrestrial laser scanning for the Three-Dimensional mapping and monitoring of open-pit mine areas. Remote Sensing 7, 6635–6662. doi:10.3390/rs70606635
  37. Tonkin, T.N., Midgley, N.G., Cook, S.J., Graham, D.J., 2016. Ice-cored moraine degradation mapped and quantified using an unmanned aerial vehicle: A case study from a polythermal glacier in Svalbard. Geomorphology (in press). doi:10.1016/j.geomorph.2015.12.019
  38. Tuffen, H., James, M.R., Castro, J.M., Schipper, C.I., 2013. Exceptional mobility of an advancing rhyolitic obsidian flow at Cordón Caulle volcano in Chile. Nature Communications 4. doi:10.1038/ncomms3709
  39. Ullman, S., 1979. The interpretation of structure from motion. Proceedings of the Royal Society of London B: Biological Sciences 203, 405–426. doi:10.1098/rspb.1979.0006
  40. Van Damme, T., 2015. Computer Vision Photogrammetry For Underwater Archaeological Site Recording In A Low-Visibility Environment, in: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Underwater 3D Recording and Modeling. Piano di Sorrento, Italy. doi:10.5194/isprsarchives-XL5-W5-231-2015
  41. Vepakomma, U., Cormier, D., Thiffault, N., 2015. Potential of Uav based Convergent Photogrammetry in monitoring regeneration standards, in: ISPRS - International Archives of the Photogrammetry, Remote Sensing and
  42. Spatial Information Sciences. Toronto, Canada, pp. 281–285. doi:10.5194/isprsarchives-XL1-W4-281-2015
  43. Yücel, M.A., Turan, R.Y., 2016. Areal Change Detection and 3D Modeling of Mine Lakes Using HighResolution