31 May 2017 Unmanned aerial vehicle-based structure from motion biomass inventory estimates
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J. of Applied Remote Sensing, 11(2), 026026 (2017). doi:10.1117/1.JRS.11.026026
Riparian vegetation restoration efforts require cost-effective, accurate, and replicable impact assessments. We present a method to use an unmanned aerial vehicle (UAV) equipped with a GoPro digital camera to collect photogrammetric data of a 0.8-ha riparian restoration. A three-dimensional point cloud was created from the photos using “structure from motion” techniques. The point cloud was analyzed and compared to traditional, ground-based monitoring techniques. Ground-truth data were collected on 6.3% of the study site and averaged across the entire site to report stem heights in stems/ha in three height classes. The project site was divided into four analysis sections, one for derivation of parameters used in the UAV data analysis and the remaining three sections reserved for method validation. Comparing the ground-truth data to the UAV generated data produced an overall error of 21.6% and indicated an R 2 value of 0.98. A Bland–Altman analysis indicated a 95% probability that the UAV stems/section result will be within 61    stems / section of the ground-truth data. The ground-truth data are reported with an 80% confidence interval of ± 1032    stems / ha ; thus, the UAV was able to estimate stems well within this confidence interval.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Emily Bedell, Monique Leslie, Katie Fankhauser, Jonathan Burnett, Michael G. Wing, Evan A. Thomas, "Unmanned aerial vehicle-based structure from motion biomass inventory estimates," Journal of Applied Remote Sensing 11(2), 026026 (31 May 2017). https://doi.org/10.1117/1.JRS.11.026026 Submission: Received 14 December 2016; Accepted 12 May 2017
Submission: Received 14 December 2016; Accepted 12 May 2017

Unmanned aerial vehicles

Biological research

Motion estimation


Data analysis

Digital cameras


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