Browse > Article
http://dx.doi.org/10.7780/kjrs.2019.35.5.1.7

A Study on the Improvement of UAV based 3D Point Cloud Spatial Object Location Accuracy using Road Information  

Lee, Jaehee (Spatial Information Research Institute, LX)
Kang, Jihun (Spatial Information Research Institute, LX)
Lee, Sewon (Spatial Information Research Institute, LX)
Publication Information
Korean Journal of Remote Sensing / v.35, no.5_1, 2019 , pp. 705-714 More about this Journal
Abstract
Precision positioning is necessary for various use of high-resolution UAV images. Basically, GCP is used for this purpose, but in case of emergency situations or difficulty in selecting GCPs, the data shall be obtained without GCPs. This study proposed a method of improving positional accuracy for x, y coordinate of UAV based 3 dimensional point cloud data generated without GCPs. Road vector file by the public data (Open Data Portal) was used as reference data for improving location accuracy. The geometric correction of the 2 dimensional ortho-mosaic image was first performed and the transform matrix produced in this process was adopted to apply to the 3 dimensional point cloud data. The straight distance difference of 34.54 m before the correction was reduced to 1.21 m after the correction. By confirming that it is possible to improve the location accuracy of UAV images acquired without GCPs, it is expected to expand the scope of use of 3 dimensional spatial objects generated from point cloud by enabling connection and compatibility with other spatial information data.
Keywords
UAV; 3D point cloud; location accuracy; transform matrix; 3D spatial object;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
연도 인용수 순위
1 Becker, C., N. Hani, E. Rosinskaya, E. D'Angelo, and C. Strecha, 2017. Classification of aerical photogrammetric 3D pint clouds, Proc. of 2017 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Science, Hannover, Germany, Jun. 6-9, vol. 4-1/W1, pp. 3-10.
2 Choi, H.S. and E.M. Kim, 2017. Image registration of drone images through association analysis of linear features, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 35(6): 441-452 (in Korean with English abstract).   DOI
3 Choi, H.S. and E.M. Kim, 2019. Automatic georeferencing of sequential drone images using linear features and distinct points, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 37(1): 19-28 (in Korean with English abstract).   DOI
4 El-Ashmawy, N. and A. Shaker, 2014. Raster vs. point cloud LiDAR data classification, Proc. of 2014 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Istanbul, Turkey, Sep. 29- Oct. 2, vol. 40-7, pp. 79-83.
5 Forlani, G., E. Dall'asta, F. Diotri, U.M. Cella, R. Roncella, and M. Santise, 2018. Quality assessment of DSMs produced from UAV flights georeferenced with on-board RTK positioning, Journal of Remote Sensing, 10(2): 311.   DOI
6 Han, D.Y., D.S. Kim, J.B. Lee, J.H. Oh, and Y.I. Kim, 2006. Automatic image-to-image registration of middle- and low- resolution satellite images using Scale-Invariant Feature Transform technique, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 24(5): 409-416 (in Korean with English abstract).
7 Han, Y.K., Y.G. Byun, J.W. Choi, D.Y. Han, and Y.I. Kim, 2010. Automatic registration of high resolution satellite images using local properties of tie points, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 28(3): 353-359 (in Korean with English abstract).
8 He, Y., B. Liang, J. Yang, S. Li, and J. He, 2017. An iterative closest points algorithm for registration of 3D laser scanner point clouds with geometric features, Journal of Sensors, 17(8): 1862.   DOI
9 Lim, S.B., C.W. Seo, and H.C. Yoon, 2015. Digital map updates with UAV photogrammetric methods, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 33(5): 397-405 (in Korean with English abstract).   DOI
10 Lee, H.S., D.J. Kim, J.H. Oh, J.I. Shin, and J.S. Jung, 2017. Tidal flat DEM generation and seawater changes estimation at Hampyeong bay using drone images, Korean Journal of Remote Sensing, 33(3): 325-331 (in Korean with English abstract).   DOI
11 Manyoky, M., P. Theiler, D. Steudler, and H. Eisenbeiss, 2011. Unmanned aerial vehicle in cadastral applications, Proc. of 2011 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Zurich, Switzerland, Sep. 14-16, vol. 38-1, pp. 57-62.
12 Kim, H.M., H.J. Yoon, S.W. Jang, and Y.H. Chung, 2017. Detection method of river floating debris using Unmanned Aerial Vehicle and multispectral sensors, Korean Journal of Remote Sensing, 33(5-1): 537-546 (in Korean with English abstract).   DOI
13 Jung, J.W., T.J. KIM, J.I. Kim, and S.A. Rhee, 2016. Comparison of match candidate pair constitution methods for UAV images without orientation parameters, Korean Journal of Remote Sensing, 32(6): 647-656 (in Korean with English abstract).   DOI
14 Kattenborn, T., M. Sperlich, K. Bataua, and B. Koch, 2014. Automatic single palm tree detection in plantations using UAV-based photogrammetric point clouds, Proc. of 2014 ISPRS Technical Commission Symposium, Zurich, Switzerland, Sep. 5-7, vol. 40-3, pp. 137-144.
15 Kim, H.G., J.I. Kim, S.J. Yoon, and T.J. Kim, 2018. Development of a method for calculating the allowable storage capacity of rivers by using drone images, Korean Journal of Remote Sensing, 34(2-1): 203-211 (in Korean with English abstract).   DOI
16 Kim, M.C. and H.J. Yoon, 2018. A Study on utilization 3D shape Pointcloud without GCPs using UAV images, Journal of the Korea Academia-Industrial Cooperation Society, 19(2): 97-104 (in Korean with English abstract).   DOI
17 Tomastik, J., M. Mokros, P. Surovy, A. Grznarova, and J. Merganic, 2019. UAV RTK/PPK method-an optimal solution for mapping inaccessible forested areas?, Journal of Remote Sensing, 11(6): 721.   DOI
18 Nevalainen, O., E. Honkavaara, S. Tuominen, N. Viljanen, T. Hakala, X. Yu, J. Hyyppa, H. Saari, I. Polonen, N.N. Imai, and A.M.G. Tommaslli, 2017. Individual tree detection and classification with UAV-Based photogrammetric point clouds and hyperspectral imaging, Journal of Remote Sensing, 9(3): 185.   DOI
19 Rifman, S.S. and D.M. McKinnon, 1974. Evaluation of digital correction techniques for ERTS Images; Final report, TRW Systems, Redondo Beach, CA, USA.