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Article

Estimating Tree Height and Volume Using Unmanned Aerial Vehicle Photography and SfM Technology, with Verification of Result Accuracy

1
Graduate School of Bioresource Sciences, Nihon University, 1866 Kameino, Fujisawa, Kanagawa 252-0880, Japan
2
College of Bioresource Sciences, Nihon University, 1866 Kameino, Fujisawa, Kanagawa 252-0880, Japan
*
Author to whom correspondence should be addressed.
Drones 2020, 4(2), 19; https://doi.org/10.3390/drones4020019
Received: 18 March 2020 / Revised: 7 May 2020 / Accepted: 9 May 2020 / Published: 11 May 2020
This study aimed to investigate the effects of differences in shooting and flight conditions for an unmanned aerial vehicle (UAV) on the processing method and estimated results of aerial images. Forest images were acquired under 80 different conditions, combining various aerial photography methods and flight conditions. We verified errors in values measured by the UAV and the measurement accuracy with respect to tree height and volume. Our results showed that aerial images could be processed under all the studied flight conditions. However, although tree height and crown were decipherable in the created 3D model in 64 conditions, they were undecipherable in 16. The standard deviation (SD) in crown area values for each target tree was 0.08 to 0.68 m2. UAV measurements of tree height tended to be lower than the actual values, and the RMSE (root mean square error) was high (5.2 to 7.1 m) through all the 64 modeled conditions. With the estimated volume being lower than the actual volume, the RMSE volume measurements for each flight condition were from 0.31 to 0.4 m3. Therefore, irrespective of flight conditions for UAV measurements, accuracy was low with respect to the actual values. View Full-Text
Keywords: unmanned aerial vehicle; structure from motion; estimated value accuracy; flight altitude; degree of overlap in photography unmanned aerial vehicle; structure from motion; estimated value accuracy; flight altitude; degree of overlap in photography
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MDPI and ACS Style

Kameyama, S.; Sugiura, K. Estimating Tree Height and Volume Using Unmanned Aerial Vehicle Photography and SfM Technology, with Verification of Result Accuracy. Drones 2020, 4, 19. https://doi.org/10.3390/drones4020019

AMA Style

Kameyama S, Sugiura K. Estimating Tree Height and Volume Using Unmanned Aerial Vehicle Photography and SfM Technology, with Verification of Result Accuracy. Drones. 2020; 4(2):19. https://doi.org/10.3390/drones4020019

Chicago/Turabian Style

Kameyama, Shohei, and Katsuaki Sugiura. 2020. "Estimating Tree Height and Volume Using Unmanned Aerial Vehicle Photography and SfM Technology, with Verification of Result Accuracy" Drones 4, no. 2: 19. https://doi.org/10.3390/drones4020019

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