Evaluating The Approaches of the 3D Models Generation of a Soil Surface: A Review Study
DOI:
https://doi.org/10.51173/jt.v5i3.1451Keywords:
Videogrammetric Technology, Close Range Photogrammetry, 3D Models Soil SurfaceAbstract
There are various approaches used to create 3D models of soil surfaces, including field surveying, photogrammetry and laser scanning methods. However, most of these methods are high cost, requiring many employees and long processing time. Thus, this study will evaluate these approaches and will show the merits and the significances of each approach used for 3D soil generations. The review study shows that the videogrammetric method is considered the efficient approach for 3D soil surface generation because it is economic, precise, fast, and needs few workers.
Downloads
References
Batakanwa, N., & Lipecki, T. (2020). The use of video camera to create metric 3D model of engineering objects. Geoinformatica Polonica, 19. doi.org/10.24867/07kg05radovic.
Mikhail, E. M., Bethel, J. S., & McGlone, J. C. (2001). Introduction to modern photogrammetry. John Wiley & Sons. doi: 10.12691/jgg-2-3-5
Chong, A. K., Al-Baghdadi, J. A. A., & Alshadli, D. (2014, January). High-definition video cameras for measuring movement of vibrating bridge structure. In International Conference on Vibration and Vibro-acoustics (ICVV2014) (pp. 1-10). University of Southern Queensland.
Alsadik, B. S. A. (2014). Guided close range photogrammetry for 3D modelling of cultural heritage sites. Netherlands: ITC Printing Department. DOI:10.3990/1.9789036537933
Elliot W. J., Laflen J. M., Thomas A. W., Kohl K. D. (1997). "Photogrammetric and rillmeter techniques for hydraulic measurement in soil erosion studies," Transactions of the ASAE, 40(1), pp 157–165 doi: 10.13031/2013.21261) @1997
Nouwakpo, S., Huang, C. H., Frankenberger, J., Bethel, J., & Lafayette, W. (2010, June). A simplified close range photogrammetry method for soil erosion assessment. In 2nd Joint Federal Interagency Conference, Las Vegas, NV (Vol. 27) doi:10.1236/sssaj2011.0148
Hu Y, Fister W, He Y, Kuhn NJ. 2020. Assessment of crusting effects on interrill erosion by laser scanning. PeerJ 8:e8487 https://doi.org/10.7717/peerj.8487
Milenković, M., Pfeifer, N., & Glira, P. (2015). Applying terrestrial laser scanning for soil surface roughness assessment. Remote Sens. 2015, 7(2), 2007-2045; https://doi.org/10.3390/rs70202007
Nouwakpo, S. K., Weltz, M. A., & McGwire, K. (2016). Assessing the performance of structure‐from‐motion photogrammetry and terrestrial LiDAR for reconstructing soil surface microtopography of naturally vegetated plots. Earth Surface Processes and Landforms, 41(3), 308-322. https://doi.org/10.1002/esp.3787
Liu, L., Bi, Q., Zhang, Q., Tang, J., Bi, D., & Chen, L. (2022, March). Evaluation Method of Soil Surface Roughness after Ditching Operation Based on Wavelet Transform. In Actuators (Vol. 11, No. 3, p. 87). MDPI. https://doi.org/10.3390/act11030087
Lee, S., Choi, Y., 2015. Topographic survey at small-scale open-pit mines using a popular rotary-wing unmanned aerial vehicle (drone). J. Korean Soc. Rock Mech. 25, 462e469.https://doi.org/10.7474/TUS.2015.25.5.462
Winkelmaier, G., Battulwar, R., Khoshdeli, M., Valencia, J., Sattarvand, J., Bahram, P., 2020. Topographically guided UAV for identifying tension cracks using imagebased analytics in open-pit mines. IEEE J. Trans. Ind. Eng. https://doi.org/ 10.1109/TIE.2020.2992011.DOI: 10.1109/TIE.2020.2992011
Zekkos, D., Professor, A., Greenwood, W., Lynch, J., Athanasopoulos-Zekkos, A., Clark, M., 2018. Lessons learned from the application of UAV-enabled structurefrom-motion photogrammetry in geotechnical engineering. Int. J. Geoengin. Case Hist. 4 (4), 254e274.DOI: http://dx.doi.org/10.4417/IJGCH-04-04-03
Kaźmierowski, C., Ceglarek, J., Królewicz, S., Cierniewski, J., Universityc, A. M., Jasiewicz, J., & Wyczałek, M. (2015). Soil surface roughness quantification using DEM obtained from UAV photogrammetry. Geomorphometry for Geosciences, Adam Mickiewicz University in Poznań–Institute of Geoecology and Geoinformation doi:10.13140/RG.2.1.4811.8889
Cleveland, L.J., Wartman, J., 2006. Principles and applications of digital photogrammetry for geotechnical engineering. Site Geomater. Characteriz. ASCE, 128–135.https://doi.org/10.1061/40861(193)16
Kenarsari, A. E., Vitton, S. J., & Beard, J. E. (2017). Creating 3D models of tractor tire footprints using close-range digital photogrammetry. Journal of Terramechanics, 74, 1-11.https://doi.org/10.1016/j.jterra.2017.06.001
Stojic, M., Chandler, J., Ashmore, P. and Luce, J., 1998. The assessment of sediment transport rates by automated digital photogrammetry. Photogrammetric Engineering & Remote Sensing, 64(5): 387–395 DOI:10.1002/(SICI)1096-9837(199901)24:13.0.CO;2-H.
Lascelles, B., Favis-Mortlock, D., Parsons, T. and Boardman, J., 2002. Automated digital photogrammetry: a valuable tool for small-scale geomorphological research for the non-photogrammetrist? Transactions in GIS, 6(1): 5–15. https://doi.org/10.1111/1467-9671.00091
Rieke‐Zapp, D. H., & Nearing, M. A. (2005). Digital close-range photogrammetry for measurement of soil erosion. The Photogrammetric Record, 20(109), 69-87. https://doi.org/10.1111/j.1477-9730.2005.00305.x
Abban, B. K., Papanicolaou, A. N., Giannopoulos, C. P., Dermisis, D. C., Wacha, K. M., Wilson, C. G., & Elhakeem, M. (2017). Quantifying the changes of soil surface microroughness due to rainfall impact on a smooth surface. Nonlinear Processes in Geophysics, 24(3), 569-579 .https://doi.org/10.5194/npg-24-569-2017.
Grundy, L., Ghimire, C., & Snow, V. (2020). Characterisation of soil micro-topography using a depth camera. MethodsX, 7, 101144.https://doi.org/10.1016/j.mex.2020.101144
Suchan, J., & Azam, S. (2021). Controlled photogrammetry system for determination of volume and surface features in soils. MethodsX, 8, 101368.https://doi.org/10.1016/j.mex.2021.101368
Azizi, A., Abbaspour-Gilandeh, Y., Mesri-Gundoshmian, T., Farooque, A. A., & Afzaal, H. (2021). Estimation of soil surface roughness using stereo vision approach. Sensors, 21(13), 4386.https://doi.org/10.3390/s21134386
Herodowicz‐Mleczak, K., Piekarczyk, J., Kaźmierowski, C., Nowosad, J., & Mleczak, M. (2022). Estimating soil surface roughness with models based on the information about tillage practises and soil parameters. Journal of Advances in Modeling Earth Systems, 14(3), e2021MS002578 https://doi.org/10.1029/2021MS002578
Zhu, Z., & Brilakis, I. (2009). Comparison of optical sensor-based spatial data collection techniques for civil infrastructure modeling. Journal of Computing in Civil Engineering, 23(3), 170-177https://doi.org/10.1061/(ASCE)0887-3801(2009)23:3(170).
Remondino, F., & El‐Hakim, S. (2006). Image‐based 3D modelling: a review. The photogrammetric record, 21(115), 269-291 https://doi.org/10.1111/j.1477-9730.2006.00383.x
Vinci, A., Todisco, F., Brigante, R., Mannocchi, F., & Radicioni, F. (2017). A smartphone camera for the structure from motion reconstruction for measuring soil surface variations and soil loss due to erosion. Hydrology Research, 48(3), 673-685 https://doi.org/10.2166/nh.2017.075.
Laburda, T., Krása, J., Zumr, D., Devátý, J., Vrána, M., Zambon, N., ... & Dostál, T. (2021). SfM‐MVS Photogrammetry for Splash Erosion Monitoring under Natural Rainfall. Earth Surface Processes and Landforms, 46(5), 1067-1082 https://doi.org/10.1002/esp.5087
Ortiz-Coder, P., & Sánchez-Ríos, A. (2020). An integrated solution for 3D heritage modeling based on videogrammetry and V-SLAM technology. Remote Sensing, 12(9), 1529 https://doi.org/10.3390/rs12091529.
Deliry, S. I., & Avdan, U. (2021). Accuracy of unmanned aerial systems photogrammetry and structure from motion in surveying and mapping: A review. Journal of the Indian Society of Remote Sensing, 49(8), 1997-2017 https://doi.org/10.1007/s12524-021-01366.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Shaimaa Hailem Teamaa, Jasim Ahmed Ali AL-Baghdadi, Farid Majid Abd
This work is licensed under a Creative Commons Attribution 4.0 International License.