زمین شناسی مهندسی

زمین شناسی مهندسی

ارزیابی روش ویدئوگرامتری برای محاسبه حجم عملیات خاکی در مقایسه با روش‌های مرسوم نقشه‌برداری زمینی

نویسندگان
دانشکده عمران، آب و محیط زیست دانشگاه شهید بهشتی
چکیده
محاسبه حجم عملیات خاکی در معادن از موضوعات چالش برانگیز، پر هزینه و زمان‌بر این حوزه به شمار می­‌رود. در پروژه­های معدنی برای برنامه‌ریزی فروش محصولات تولید شده و محاسبه هزینه-عملکرد پیمانکاران، محاسبه احجام خاک‌برداری برای برآورد حجم استخراجی ضروری است. محاسبه احجام خاکی با چالش‌­های زیادی مانند انتخاب بهترین ابزار و روش اندازه‌­گیری، تطبیق نقشه­‌های تولید شده در اپوک‌­های مختلف، اعمال ضرایب تورم و تبدیل حجم به وزن همراه است. امروزه ابزارهایی چون اسکنرهای لیزری، توتال­استیشن‌­ها و دوربین‌­های متریک برای محاسبه احجام خاکی مورد استفاده قرار می‌­گیرند. اما استفاده از آن‌ها هزینه‌­بر بوده و نیاز به اپراتور با تجربه دارد. بنابراین لازم است روش‌­های محاسبه احجام در زمان کمتر با دقت قابل قبول بررسی شود. در این تحقیق استفاده از گوشی­‌های هوشمند برای برآورد بهینه حجم عملیات خاکی مورد ارزیابی قرار گرفته است. داده‌های تصویری به‌دست‌آمده از گوشی هوشمند با روش ساختار ناشی از حرکت (SFM) پردازش شد و خروجی آن برای تولید مدل رقومی ارتفاعی به منظور تخمین حجم عملیات خاکی استفاده شد. اختلاف حجم خاک محاسبه شده نسبت به روش‌­های آزمایشگاهی و توتال ­استیشن برای دپو خاک و گودبرداری مورد مطالعه به ترتیب 86/3% و 84/1% است که نشان می‌­دهد روش مورد استفاده در این تحقیق از دقت لازم برای محاسبه احجام خاکی برخوردار است، و با توجه به مزیت‌­های زیادی که نسبت به روش‌­های مرسوم از نظر هزینه و زمان دارد، می‌­تواند جایگزین آن‌ها شود.


کلیدواژه‌ها

Altuntaş, C., 2021. Camera self-calibration by using SFM based dense matching for close-range images. Eurasian Journal of Science Engineering and Technology, 2(2), pp. 069-082.
Balaguer-Puig, M., Marqués-Mateu, A., Lerma, J.L., Ibáñez-Asensio, S., 2017. Estimation of small-scale soil erosion in laboratory experiments with Structure from Motion photogrammetry. Geomorphology, 295, pp. 285-296.
Bessin, Z., Jaud, M., Letortu, P., Vassilakis, E., Evelpidou, N., Costa, S., Delacourt, C., 2023. Smartphone Structure-from-Motion Photogrammetry from a Boat for Coastal Cliff Face Monitoring Compared with Pléiades Tri-Stereoscopic Imagery and Unmanned Aerial System Imagery. Remote Sensing, 15(15): 3824.
Carbonell, M., 1989. Architectural photogrammetry. In: Karara HM, editor. Non-topographic photogrammetry. Falls Church, Virginia: ASPRS, p. 321–47.
Chandle, J.H., 1999. Effective application of automated digital photogrammetry for geomorphological research. Earth Surface Processes and Landforms, 24, pp. 51-63.
Cooper, M.A.R., Robson, S., 1996. Theory of Close-Range Photogrammetry. Close Range Photogrammetry and Machine Vision, pp. 9-51.
Corradetti, A., Seers, T.D., Billi, A., Tavani, S., 2021. Virtual Outcrops in a Pocket: The Smartphone as a Fully Equipped Photogrammetric Data Acquisition Tool. The Geological society of America, 31, pp. 4–9.
Eltner, A., Sofia, G., 2020. Structure from motion photogrammetric technique. Developments in Earth Surface Processes, 23, pp. 1-24.
Fang, K., Dong, A., Tang, H., An, P., Zhang, B., Miao, M., Ding, B., Hu, X., 2022. Comprehensive assessment of the performance of a multi smartphone measurement system for landslide model test. Landslides, 20, pp. 845–864.
Fonstad, M. A., Dietrich, J. T., Courville, B. C., Jensen, J. L., Carbonneau P. E., 2013. Topographic structure from motion: a new development in photogrammetric measurement. Earth surface processes and Landforms, 38, pp. 421-430.
Fraser, C.S, Cronk, S., 2009 .A hybrid measurement approach for close-range photogrammetry. ISPRS Journal of Photogrammetry and Remote Sensing, 64, pp. 328-333.
Gharehaghajlou1, A., Önal, O., 2018. A parametric study on the bulk density determination of soil specimens using close-range photogrammetry. 13th International Congress on Advances in Civil Engineering, İzmir, Turkey.
Govender, N., 2009. Evaluation of feature detection algorithms for structure from motion. Council for Scientific and Industrial Research, South Africa, https://www.researchgate.net/publication/40877914.
Harris, C., Stephens, M., 1988. A combined corner and edge detector. Proceedings of the Fourth Alvey Vision Conference, Manchester, pp. 147-151.
Hanif M., Seghouane A., 2012. Blurred Image Deconvolution Using Gaussian Scale Mixtures Model in Wavelet Domain. International conference on digital image computing techniques and applications (DICTA).
Hollick, J., Moncrieff, S., Belton, D., Woods, A.J., Hutchison, A., Helmholz, P., 2013. Creation of 3d models from large unstructured image and video datasets. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., 40, pp. 133–137.
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, pp. 1-17.
Kun-Cahyono, B., 2009. Digital elevation modeling of inaccessible slope by using date signature main supervisor date co-supervisor close-range photogrammetric data. master's thesis, Civil Engineering Department Univ. Technology Petronas Bandar Seri Iskandar, 167p.
Lane, S.N., James, T.D., Crowell, M.D., 2000. Application of digital photogrammetry to complex topography for geomorphological research. The Photogrammetric Record, 16, pp. 793-821.
Langhammer, J., Janský, B., Kocum, J., Minařík, R., 2018. 3-D reconstruction of an abandoned montane reservoir using UAV photogrammetry, aerial LiDAR and field survey. Applied Geography, 98, pp. 9-21.
Lowe, D. G., 2004. Distinctive image features from scale invariant key points. International journal of computer vision, 60, pp. 91-110.
Matuzeviˇcius, D., Serackis, A., 2022. Three-Dimensional Human Head Reconstruction Using Smartphone-Based Close-Range Video Photogrammetry. Appl. Sci., 12(1), pp. 1-26.
Matthews, N. A., 2008. Aerial and Close-Range Photogrammetric Technology: Providing Resource Documentation, Interpretation, and Preservation. Technical Note 428. U.S. Department of the Interior, Bureau of Land Management, National Operations Center, Denver, Colorado. 42p.
Mohammadi, M., Rashidi, M., Mousavi, V., Karami, A., Yu, Y., Samali, B., 2021. Case study on accuracy comparison of digital twins developed for a heritage bridge via UAV photogrammetry and terrestrial laser scanning. in: Proceedings of the 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 10.
Musicco, A., Rossi, N., Verdoscia, C., 2023. Accuracy evaluation of smartphone-based videogrammetry for cultural heritage documentation process. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 48(2023), pp. 1119- 1126.
usicco, Antonella, Nicola Rossi, and Cesare Verdoscia.
"ACCURACY EVALUATION OF SMARTPHONE-BASED
VIDEOGRAMMETRY FOR CULTURAL HERITAGE
DOCUMENTATION PROCESS." The International Archives of
the Photogrammetry, Remote Sensing and Spatial Information
Sciences 48 (2023): 1119-1126.
Raevaa, P.L., Filipovaa, S.L., Filipova, D. G., 2016. Volume computation of a stockpile a study case comparing GPS and UAV measurements in in an open pit quarry. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 41-B1, 23 ISPRS Congress, Prague, Czech Republic.
Remondino, F., El-Hakim, S., 2006. Image-based 3-D modelling: a review. The Photogrammetric Record 21(115), pp. 269–291.
Samad, A.M., Asri, N.A., Anuar Ahmad, A., 2012. The use of digital image for volume determination using digital close range photogrammetric method. Proceedings - 2012 IEEE 8th International Colloquium on Signal Processing and Its Applications, pp. 321-324.
Shan, J., Li, Z., Lercel, D., Tissue, K., Hupy, J., Carpenter, J., 2023. Democratizing photogrammetry: an accuracy perspective. Geo-spatial Information Science. 26(2), pp. 175-188.
Shao, X., Wei, K., He, X., 2023. Calibration of stereo-digital image correlation for large field of view measurement based on photogrammetry. Optics and Lasers in Engineering, 169, p.107732.
Tucci, G., Gebbia, A., Conti, A., Fiorini, L., Lubello, C., 2019. Monitoring and Computation of the Volumes of Stockpiles of Bulk Material by Means of UAV Photogrammetric Surveying. Remote Sens. 11(12), p. 1471.
Wróżyński, R., Pyszny, K., Sojka, M., Przybyła, C., Błażejewska, S.M., 2017. Ground volume assessment using ’Structure from Motion’ photogrammetry with a smartphone and a compact camera. Open Geosci, 9, pp. 281–294.
Yakar, M., Yilmaz, H.M., Mutluoglu, O., 2013. Performance of photogrammetric and terrestrial laser scanning methods in volume computing of excavation and filling areas. Earth Sciences, 39, pp. 387–394.
Yilmaz, H.M., 2010. Close range photogrammetry in volume computing. Experimental Techniques, 34, pp. 48-54.
Yilmaz, H.M., Yakar, M., 2008. Computing of volume of excavation areas by digital close-range photogrammetry. Arabian Journal for Science and Engineering, 33(1), pp. 63-79.
Zhang, Z., Kang, J., Feng, L., Sun, Z., Wu, B., 2023. Practical zoom camera calibration method for close-range photogrammetry. Optics Letters, 48(2), pp. 243-246.