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http://dx.doi.org/10.21289/KSIC.2021.24.3.343

Estimating the Forest Micro-topography by Unmanned Aerial Vehicles (UAV) Photogrammetry  

Cho, Min-Jae (Forest Technology and Management Research Center, National Institute of Forest Science)
Choi, Yun-Sung (Forest Technology and Management Research Center, National Institute of Forest Science)
Oh, Jae-Heun (Forest Technology and Management Research Center, National Institute of Forest Science)
Lee, Eun-Jai (Forest Technology and Management Research Center, National Institute of Forest Science)
Publication Information
Journal of the Korean Society of Industry Convergence / v.24, no.3, 2021 , pp. 343-350 More about this Journal
Abstract
Unmanned aerial vehicles(UAV) photogrammetry provides a cost-effective option for collecting high-resolution 3D point clouds compared with UAV LiDAR and aerial photogrammetry. The main objectives of this study were to (1) validate the accuracy of 3D site model generated, and (2) determine the differences between Digital Elevation Model(DEM) and Digital Surface Model(DSM). In this study, DEM and DSM were shown to have varying degree of accuracy from observed data. The results indicated that the model predictions were considered tend to over- and under-estimated. The range of RMSE of DSM predicted was from 8.2 and 21.3 when compared with the observation. In addition, RMSE values were ranged from 10.2 and 25.8 to compare between DEM predicted and field data. The predict values resulting from the DSM were in agreement with the observed data compared to DEM calculation. In other words, it was determined that the DSM was a better suitable model than DEM. There is potential for enabling automated topography evaluation of the prior-harvest areas by using UAV technology.
Keywords
Aerial image; Photogrammetry; Digital Elevation Model; Digital Surface Model; Root-Mean-Square Error;
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