Tree Height Estimation of Pinus densiflora and Pinus koraiensis in Korea with the Use of UAV-Acquired Imagery
2
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
The use of unmanned aerial vehicles (UAV) for the estimation of tree height is gaining recognition. This study aims to assess the effectiveness of tree height estimation of Pinus densiflora Sieb. et Zucc. and Pinus koraiensis Sieb. etZucc. using digital surface model (DSM) generated from UAV-acquired imageries. Images were taken with the TrimbleⓇ UX5 equipped with Sony α 5100. The generated DSM, together with the digital elevation model (DEM) generated from a digital map of the study areas, were used in the estimation of tree height. Field measurements were conducted in order to generate a regression model and carry out accuracy assessment. The obtained coefficients of determination (R2) and root mean square error (RMSE) for P. densiflora (R2=0.71; RMSE=1.00 m) and P. koraiensis (R2=0.64; RMSE=0.85 m) are comparable to the results of similar studies. The results of the paired two-tailed t-test show that the two tree height estimation methods are not significantly different (p-value=0.04 and 0.10, alpha level=0.01), which means that tree height estimation using UAV imagery could be used as an alternative to field measurement.
Abstract
The use of unmanned aerial vehicles (UAV) for the estimation of tree height is gaining recognition. This study aims to assess the effectiveness of tree height estimation of Pinus densiflora Sieb. et Zucc. and Pinus koraiensis Sieb. etZucc. using digital surface model (DSM) generated from UAV-acquired imageries. Images were taken with the TrimbleⓇ UX5 equipped with Sony α 5100. The generated DSM, together with the digital elevation model (DEM) generated from a digital map of the study areas, were used in the estimation of tree height. Field measurements were conducted in order to generate a regression model and carry out accuracy assessment. The obtained coefficients of determination (R2) and root mean square error (RMSE) for P. densiflora (R2=0.71; RMSE=1.00 m) and P. koraiensis (R2=0.64; RMSE=0.85 m) are comparable to the results of similar studies. The results of the paired two-tailed t-test show that the two tree height estimation methods are not significantly different (p-value=0.04 and 0.10, alpha level=0.01), which means that tree height estimation using UAV imagery could be used as an alternative to field measurement.
참고문헌 (20)
- Avery TE, "Forest Measurements", pp.456~ (2002), McGraw Hill Inc
- Balenović I, "Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution", Ann For Res, 58, pp.125~143 (2015)
- "Measuring the height of a single tree" (1998)[URL]
- 장안진, "컬러항공사진과 LiDAR 데이터를 이용한 수목 개체 및 수고 추정", 대한원격탐사학회지, 22(6), pp.543~551 (2006), 대한원격탐사학회
- Chao H, "Remote sensing and actuation using unmanned vehicles", pp.198~ (2012), IEEE Press
- Colomina I, "Unmanned aerial systems for photogrammetry and remote sensing : A review", ISPRS Journal of Photogrammetry and Remote Sensing, 92, pp.79~97 (2014)
- Dandois JP, "High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision", Remote Sensing of Environment, 136, pp.259~276 (2013)
- Diaz-Valera RA, "High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3D Photo Reconstruction : Application in Breeding Trials", Remote Sens, 7, pp.4213~4232 (2015)
- Erdody TL, "Fusion of LiDAR and imagery for estimating forest canopy fuels", Remote Sensing of Environment, 114, pp.725~737 (2010)
- Fieber KD, "Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment", ISPRS Journal of Photogrammetry and Remote Sensing, 104, pp.144~157 (2015)
- Gopalakrishnan R, "Prediction of Canopy Heights over a Large Region Using Heterogeneous Lidar Datasets : Efficacy and Challenges", Remote Sens, 7, pp.11036~11060 (2015)
- Korea Forest Service, "2015 Statistical Yearbook of Forestry", KFS, 440~ (2015)
- "Forest geographic information service" (2016)[URL]
- Latifi H, "Forest inventories by LiDAR data : A comparison of single tree segmentation and metric-based methods for inventories of a heterogeneous temperate forest", International Journal of Applied Earth Observation and Geoinformation, 42, pp.162~174 (2015)
- Lisein J, "A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery", Forests, 4, pp.922~944 (2013)
- Noh NJ, "Carbon and nitrogen dynamics in a Pinus densiflora forest with low and high stand densities", J Plant Ecol, 6, pp.368~379 (2013)
- van Laar A, "Forest Mensuration. Springer", pp.362~ (2010), Dordrecht
- Wallace L, "Assessment of Forest Structure Using Two UAV Techniques : A Comparison of Airborne Laser Scanning and Structure from Motion(SfM)Point Clouds", Forest, 7, pp.62~ (2016)
- West PW., "Tree and Forest Measurement", pp.192~ (2009), Springer
- Zarco-Tejada PJ, "Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle(UAV)and automatic 3D photo-reconstruction methods", Europ J Agronomy, 55, pp.89~99 (2014)