Complementing forest inventory data with information from unmanned aerial vehicle imagery and photogrammetry
This article is part of a larger document. View the larger document here.Abstract
Although a prerequisite for an accurate assessment of tree competition, growth, and morphological plasticity, measurements conducive to three-dimensional (3D) representations of individual trees are seldom part of forest inventory operations. This is in part because until recently our ability to measure the dimensionality, spatial arrangement, and shape of trees and tree components precisely has been constrained by technological and logistical limitations and cost. Active remote sensing technologies such as airborne LiDAR provide only partial crown reconstructions, while the use of terrestrial LiDAR is laborious and has portability limitations and high cost. In this work we capitalized on recent improvements in the capabilities and availability of small unmanned aerial vehicles (UAVs) and light and inexpensive cameras, and developed an affordable method for obtaining precise and comprehensive 3D models of trees and small groups of trees. The method employs slow-moving UAVs that acquire images along predefined trajectories near and around targeted trees and computer vision-based approaches that process the images to obtain detailed tree reconstructions. We present a step-by-step workflow which utilizes open source programs and original software. We anticipate that further refinement and development of our method can render it a valuable source of tree dimensionality information, complementary to the data recorded in traditional forest inventory field operations.