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http://dx.doi.org/10.7780/kjrs.2019.35.1.1

Comparison the Mapping Accuracy of Construction Sites Using UAVs with Low-Cost Cameras  

Jeong, Hohyun (Department of Spatial Information Engineering, Pukyong National University)
Ahn, Hoyong (Department of Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences)
Shin, Dongyoon (Disaster Scientific Investigation Division, National Disaster Management Research Institute)
Choi, Chuluong (Department of Spatial Information Engineering, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.35, no.1, 2019 , pp. 1-13 More about this Journal
Abstract
The advent of a fourth industrial revolution, built on advances in digital technology, has coincided with studies using various unmanned aerial vehicles (UAVs) being performed worldwide. However, the accuracy of different sensors and their suitability for particular research studies are factors that need to be carefully evaluated. In this study, we evaluated UAV photogrammetry using smart technology. To assess the performance of digital photogrammetry, the accuracy of common procedures for generating orthomosaic images and digital surface models (DSMs) using terrestrial laser scanning (TLS) techniques was measured. Two different type of non-surveying camera(Smartphone camera, fisheye camera) were attached to UAV platform. For fisheye camera, lens distortion was corrected by considering characteristics of lens. Accuracy of orthoimage and DSM generated were comparatively analyzed using aerial and TLS data. Accuracy comparison analysis proceeded as follows. First, we used Ortho mosaic image to compare the check point with a certain area. In addition, vertical errors of camera DSM were compared and analyzed based on TLS. In this study, we propose and evaluate the feasibility of UAV photogrammetry which can acquire 3 - D spatial information at low cost in a construction site.
Keywords
UAV Photogrammetry; Fisheye Camera; Smart Phone Camera; Accuracy; DSM;
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  • Reference
1 Lambers, K., H. Eisenbeiss, M. Sauerbier, D. Kupferschmidt, T. Gaisecker, S. Sotoodeh, and T. Hanusch, 2007. Combining photogrammetry and laser scanning for the recording and modelling of the Late Intermediate Period site of Pinchango Alto, Palpa, Peru, Journal of Archaeological Science, 34(10): 1702-1712.   DOI
2 Leica Geosystems, 2008. Leica ALS60 Airborne Laser Scanner Product Specifications, Leica Geosystems AG, Heerbrugg, Switzerland.
3 Pix4D Support, 2016. Quality Report Help, https://support.pix4d.com/hc/en-us/articles/202558689#label102&gsc.tab=0, Accessed on Dec. 20, 2016.
4 Remondino, F., L. Barazzetti, F. Nex, M. Scaioni, and D. Sarazzi, 2011. UAV photogrammetry for mapping and 3d modeling-current status and future perspectives, Proc. of International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Zurich, Sep. 14-16, vol. XXXVIII-1/C22, pp. 25-31.
5 Ruzgienė, B., T. Berteska, S. Gecyte, E. Jakubauskienė, and V. C. Aksamitauskas, 2015. The surface modelling based on UAV Photogrammetry and qualitative estimation, Measurement, 73: 619-627.   DOI
6 Rumpler, M., A. Tscharf, C. Mostegel, S. Daftry, C. Hoppe, R. Prettenthaler, F. Fraundorfer, G. Mayer, and H. Bischof, 2017. Evaluations on multi-scale camera networks for precise and geo-accurate reconstructions from aerial and terrestrial images with user guidance, Computer vision and image understanding, 157: 255-273.   DOI
7 Samsung Galaxy S6 Edge, 2016. Specifications. Available online, http://www.samsung.com/us/support/owners/product/galaxy-s6-edgeverizon, Accessed on Dec. 14, 2016.
8 Seitz, S. M., B. Curless, J. Diebel, D. Scharstein, and R. Szeliski, 2006. A comparison and evaluation of multi-view stereo reconstruction algorithms, Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, New York, NY, Jun. 17-22, pp. 519-528.
9 Schwind, M., 2016. Comparing and characterizing three-dimensional point clouds derived by structure from motion photogrammetry, Texas A&M University, Texas, USA.
10 Balletti, C., F. Guerra, V. Tsioukas, and P. Vernier, 2014. Calibration of action cameras for photogrammetric purposes, Sensors, 14(9): 17471-17490.   DOI
11 Chiabrando, F., F. Nex, D. Piatti, and F. Rinaudo, 2011. UAV and RPV systems for photogrammetric surveys in archaelogical areas: two tests in the Piedmont region (Italy), Journal of Archaeological Science, 38(3): 697-710.   DOI
12 Coveney, S., A. S. Fotheringham, M. Charlton, and T. McCarthy, 2010. Dual-scale validation of a medium-resolution coastal DEM with terrestrial LiDAR DSM and GPS, Computers & Geosciences, 36(4): 489-499.   DOI
13 Candiago, S., F. Remondino, M. De Giglio, M. Dubbini, and M. Gattelli, 2015. Evaluating multispectral images and vegetation indices for precision farming applications from UAV images, Remote Sensing, 7(4): 4026-4047.   DOI
14 Dandois, J. P., M. Olano, and E. C. Ellis, 2015. Optimal altitude, overlap, and weather conditions for computer vision UAV estimates of forest structure, Remote Sensing, 7(10): 13895-13920.   DOI
15 Eisenbeiss, H. and L. Zhang, 2006. Comparison of DSMs generated from mini UAV imagery and terrestrial laser scanner in a cultural heritage application, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36(5): 90-96.
16 Gruszczynski, W., W. Matwij, and P. Cwiakala, 2017. Comparison of low-altitude UAV photogrammetry with terrestrial laser scanning as data-source methods for terrain covered in low vegetation, ISPRS Journal of Photogrammetry and Remote Sensing, 126: 168-179.   DOI
17 Strecha, C., A. Bronstein, M. Bronstein, and P. Fua, 2012. LDAHash: Improved matching with smaller descriptors, IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(1): 66-78.   DOI
18 Tscharf, A., M. Rumpler, F. Fraundorfer, G. Mayer, and H. Bischof, 2015. On the use of UAVs in mining and archaeology-geo-accurate 3d reconstructions using various platforms and terrestrial views, Proc. of ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, Toronto, Aug. 30-Sep. 2, vol. 2-1/W1, pp. 15-22.
19 Tong, X., X. Liu, P. Chen, S. Liu, K. Luan, L. Li, S. Liu, X. Liu, H. Xie, Y. Jin, and Z. Hong, 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(6): 6635-6662.   DOI
20 Lowe, D. G., 2004. Distinctive image features from scale-invariant keypoints, International Journal of Computer Vision, 60(2): 91-110.   DOI
21 Kung, O., C. Strecha, A. Beyeler, J. C. Zufferey, D. Floreano, P. Fua, and F. Gervaix, 2011. The accuracy of automatic photogrammetric techniques on ultra-light UAV imagery, Proc. of UAV-g 2011-Unmanned Aerial Vehicle in Geomatics, Zurich, CH, Sep. 14-16, no. EPFL-CONF-168806.