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S&M2413 Research Paper of Special Issue https://doi.org/10.18494/SAM.2020.2912 Published: December 29, 2020 Statistical Analysis for Usability Evaluation of Unmanned Aerial Vehicle in Geomatics [PDF] Joon Kyu Park, Kap Yong Jung, and Joong Hyeok Heo (Received April 26, 2020; Accepted June 24, 2020) Keywords: accuracy, meta-analysis, geospatial information, statistical analysis, unmanned aerial vehicle
Unmanned aerial vehicles (UAVs) have advantages such as a relatively low operating cost and excellent ground–sample distance (GSD) compared with conventional manned aerial photogrammetry. Recently, the development of sensor technology has enabled digital mapping, terrain model generation, economic evaluation, monitoring, cadastral surveying, coastal surveying, and ground surveying. However, existing studies have shown the limited validity of UAVs for spatial information construction owing to limited experiments and analyses. In this study, the validity of UAVs for spatial information construction was evaluated, and recent case studies related to the accuracy of the results were analyzed. The results of 34 studies including quantitative results of UAV accuracy within the last 5 years were investigated, and the correlations of flight altitude, accuracy, and ground control point (GCP) number are presented through the analyses of existing studies. The horizontal and vertical accuracies of terrain information using a UAV were 0.51 m and 0.56 cm, respectively. The horizontal and vertical accuracies were correlated with the flight altitude and GCP number, with the flight altitude having a greater effect than the GCP number. In the future, the results of this study will be used as a basis to examine the validity of geospatial information construction using a UAV.
Corresponding author: Kap Yong JungThis work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Joon Kyu Park, Kap Yong Jung, and Joong Hyeok Heo, Statistical Analysis for Usability Evaluation of Unmanned Aerial Vehicle in Geomatics, Sens. Mater., Vol. 32, No. 12, 2020, p. 4337-4346. |