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Open AccessArticle

Measuring Vegetation Height in Linear Disturbances in the Boreal Forest with UAV Photogrammetry

1
Department of Geography, University of Calgary, Calgary, AB T2N 1N4, Canada
2
Department of Earth and Environment, Boston University, 685 Commonwealth Avenue, Boston, MA 02215, USA
3
Northern Forestry Centre, 5320 122 Street Northwest, Edmonton, AB T6H 3S5, Canada
*
Author to whom correspondence should be addressed.
Remote Sens. 2017, 9(12), 1257; https://doi.org/10.3390/rs9121257
Received: 16 October 2017 / Revised: 28 November 2017 / Accepted: 29 November 2017 / Published: 3 December 2017
(This article belongs to the Special Issue Remote Sensing from Unmanned Aerial Vehicles (UAVs))
Monitoring vegetation recovery typically requires ground measurements of vegetation height, which is labor-intensive and time-consuming. Recently, unmanned aerial vehicles (UAVs) have shown great promise for characterizing vegetation in a cost-efficient way, but the literature on specific methods and cost savings is scant. In this study, we surveyed vegetation height on seismic lines in Alberta’s Boreal Forest using a point-intercept sampling strategy, and compared them to height estimates derived from UAV-based photogrammetric point clouds. In order to derive UAV-based vegetation height, we tested three different approaches to estimate terrain elevation: (1) UAV_RTK, where photogrammetric point clouds were normalized using terrain measurements obtained from a real-time kinematic global navigation satellite system (RTK GNSS) surveys; (2) UAV_LiDAR, where photogrammetric data were normalized using pre-existing LiDAR (Light Detection and Ranging) data; and (3) UAV_UAV, where UAV photogrammetry data were used alone. Comparisons were done at two scales: point level (n = 1743) and site level (n = 30). The point-level root-mean-square errors (RMSEs) of UAV_RTK, UAV_LiDAR, and UAV_UAV were 28 cm, 31 cm, and 30 cm, respectively. The site-level RMSEs were 11 cm, 15 cm, and 8 cm, respectively. At the aggregated site level, we found that UAV photogrammetry could replace traditional field-based vegetation surveys of mean vegetation height across the range of conditions assessed in this study, with an RMSE less than 10 cm. Cost analysis indicates that using UAV-based point clouds is more cost-effective than traditional field vegetation surveys. View Full-Text
Keywords: UAV; vegetation; point clouds; 3D; accuracy assessment; remote sensing UAV; vegetation; point clouds; 3D; accuracy assessment; remote sensing
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Chen, S.; McDermid, G.J.; Castilla, G.; Linke, J. Measuring Vegetation Height in Linear Disturbances in the Boreal Forest with UAV Photogrammetry. Remote Sens. 2017, 9, 1257.

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