UAV photogrammetry for mapping vegetation in the low-Arctic

Abstract

Plot-scale field measurements are necessary to monitor changes to tundra vegetation, which has a small stature and high spatial heterogeneity, while satellite remote sensing can be used to track coarser changes over larger regions. In this study, we explored the potential of unmanned aerial vehicle (UAV) photographic surveys to map low-Arctic vegetation at an intermediate scale. A multicopter was used to capture highly overlapping, subcentimetre photographs over a 2 ha site near Tuktoyaktuk, Northwest Territories. Images were processed into ultradense 3D point clouds and 1 cm resolution orthomosaics and vegetation height models using Structure-from-Motion (SfM) methods. Shrub vegetation heights measured on the ground were accurately represented using SfM point cloud data (r2 = 0.96, SE = 8 cm, n = 31) and a combination of spectral and height predictor variables yielded an 11-class classification with 82% overall accuracy. Differencing repeat UAV surveys before and after manually trimming shrub patches showed that vegetation height decreases in trimmed areas (− 6.5 cm, SD = 21 cm). Based on these findings, we conclude that UAV photogrammetry provides a promising, cost-efficient method for high-resolution mapping and monitoring of tundra vegetation that can be used to bridge the gap between plot and satellite remote sensing measurements.

Keywords

• unmanned aerial vehicle (UAV)
• unmanned aircraft system (UAS)
• Arctic
• shrubs
• vegetation
• Structure-from-Motion