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 di erences 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 ( = 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 e ect of species identity (s), shooting distance and angular shift showed that photographic point cloud density was dependent on and s, and optimal for 15 and 30. MAPEs calculated on stem circumferences and volumes significantly di ered with d and , respectively. There was a significant interaction between 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 . 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.