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http://dx.doi.org/10.7780/kjrs.2021.37.6.1.20

Extraction of Individual Trees and Tree Heights for Pinus rigida Forests Using UAV Images  

Song, Chan (Department of Forest Science, Kongju National University)
Kim, Sung Yong (Div. of Forest Fire and Landslide, National Institute of Forest Science)
Lee, Sun Joo (Div. of Forest Fire and Landslide, National Institute of Forest Science)
Jang, Yong Hwan (Department of Forest Science, Kongju National University)
Lee, Young Jin (Department of Forest Science, Kongju National University)
Publication Information
Korean Journal of Remote Sensing / v.37, no.6_1, 2021 , pp. 1731-1738 More about this Journal
Abstract
The objective of this study was to extract individual trees and tree heights using UAV drone images. The study site was Gongju national university experiment forest, located in Yesan-gun, Chungcheongnam-do. The thinning intensity study sites consisted of 40% thinning, 20% thinning, 10% thinning and control. The image was filmed by using the "Mavic Pro 2" model of DJI company, and the altitude of the photo shoot was set at 80% of the overlay between 180m pictures. In order to prevent image distortion, a ground reference point was installed and the end lap and side lap were set to 80%. Tree heights were extracted using Digital Surface Model (DSM) and Digital Terrain Model (DTM), and individual trees were split and extracted using object-based analysis. As a result of individual tree extraction, thinning 40% stands showed the highest extraction rate of 109.1%, while thinning 20% showed 87.1%, thinning 10% showed 63.5%, and control sites showed 56.0% of accuracy. As a result of tree height extraction, thinning 40% showed 1.43m error compared with field survey data, while thinning 20% showed 1.73 m, thinning 10% showed 1.88 m, and control sites showed the largest error of 2.22 m.
Keywords
Unmanned Aerial Vehicle; Digital Surface Model; Orthophoto; Individual tree; Pinus rigida;
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