Characterizing Vegetation Structure on Anthropogenic Disturbance Features in Alberta’s Boreal Forest with Unmanned Aerial Vehicles
Characterizing vegetation structure is an important component for understanding ecological recovery on non-permanent human footprint features in forests. However, current approaches to measuring vegetation structure rely on field protocols that are costly and difficult to scale. Compared to traditional field methods, UAV (unmanned aerial vehicle) photogrammetry has shown great promise in characterizing vegetation structure in a more cost-efficient way. In this research, I used a point-intercept sampling strategy to conduct a comparison of UAV-based estimates and field measurements at two scales: (i) point level and (ii) site (plot) level. I found that at the aggregated site level, UAV photogrammetry alone could replace traditional field-based vegetation surveys of mean vegetation height across the range of conditions assessed in this study, though significant differences remain between remote- and field-based vegetation surveys at point level. Cost analysis indicates that using UAV point clouds alone provides substantial cost-saving over traditional field vegetation surveys.
Chen, S. (2017). Characterizing Vegetation Structure on Anthropogenic Disturbance Features in Alberta’s Boreal Forest with Unmanned Aerial Vehicles (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25309