Image Data Acquisition for Estimating Individual Trees Metrics: Closer Is Better

Abstract

Background and Objectives: The recent use of Structure-from-Motion with Multi-View Stereo photogrammetry (SfM-MVS) in forestry has underscored its robustness in tree mensuration. This study evaluated the differences in tree metrics resulting from various related SfM-MVS photogrammetric image acquisition scenarios. Materials and Methods: Scaled tri-dimensional models of 30 savanna trees belonging to five species were built from photographs acquired in a factorial design with shooting distance (d = 1, 2, 3, 4 and 5 m away from tree) and angular shift (α = 15°, 30°, 45° and 60°; nested in d). Tree stem circumference at 1.3 m and bole volume were estimated using models resulting from each of the 20 scenarios/tree. Mean absolute percent error (MAPE) was computed for both metrics in order to compare the performance of each scenario in relation to reference data collected using a measuring tape. Results: An assessment of the effect of species identity (s), shooting distance and angular shift showed that photographic point cloud density was dependent on α and s, and optimal for 15° and 30°. MAPEs calculated on stem circumferences and volumes significantly differed with d and α, respectively. There was a significant interaction between α and s for both circumference and volume MAPEs, which varied widely (1.6 ± 0.4%–20.8 ± 23.7% and 2.0 ± 0.6%–36.5 ± 48.7% respectively), and were consistently lower for smaller values of d and α. Conclusion: The accuracy of photogrammetric estimation of individual tree attributes depended on image-capture approach. Acquiring images 2 m away and with 30° intervals around trees produced reliable estimates of stem circumference and bole volume. Research Highlights: This study indicates that the accuracy of photogrammetric estimations of individual tree attributes is species-dependent. Camera positions in relation to the subject substantially influence the level of uncertainty in measurements.