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

• Published in: Remote sensing (Basel, Switzerland) Vol. 9; no. 12; p. 1257
• Main Authors: Chen, Shijuan, McDermid, Gregory, Castilla, Guillermo, Linke, Julia
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2017
• Subjects: accuracy assessment; Aerial surveys; Boreal forests; Cost analysis; Cost control; Forests; Global navigation satellite system; Lidar; Navigation satellites; Photogrammetry; point clouds; remote sensing; Root-mean-square errors; Taiga; Terrain; UAV; Unmanned aerial vehicles; Vegetation; Vegetation surveys
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs9121257

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.