Evaluating tree branch angle measurements of European beech using terrestrial laser scanning

Branch angles are an important plant morphological trait affecting light interception within forest canopies. However, studies on branch angles have been limited due to the time-consuming nature of manual measurements using a protractor. Terrestrial laser scanning (TLS), however, provides new opportunities to measure branch angles more efficiently. Despite this potential, studies validating branch angle measurements from TLS have been limited. Here, our aim is to evaluate both manual and automatic branch angle measurements of European beech from TLS data using traditional field-measurements with a protractor as a reference. We evaluated the accuracy of branch angle measurements based on four automated algorithms (aRchiQSM, TreeQSM, Laplacian, Semantic-Laplacian) from TLS data. Additionally, we assessed different ways of manual branch angle measurements in the field. Our study was based on a dataset comprising 124 branch angles measured from six European beech in a European deciduous forest. Our results show that manual branch angle measurements from TLS data are in high agreement with the reference (root-mean-squared error, RMSE: [3.57°–4.18°], concordance correlation coefficient, CCC: [0.95−0.97]) across different branch length positions. Automated algorithms also are in high agreement with the reference although RMSE is approximately twice as large compared to manual branch angle measurements from TLS (RMSE: [9.29°–10.55°], CCC: [0.83−0.86]) with manual leaf points removal. When applying the automatic wood-leaf separation algorithm, the performance of the four methods declined significantly, with only approximately 20 branch angles successfully identified. Moreover, it is important to note that there is no influence of the measurement position (branch surface versus center) for branch angle measurements. However, for curved branches, the selection of branch measurement length significantly impacts the branch angle measurement. This study provides a comprehensive understanding of branch angle measurements in forests. We show that automated measurement methods based on TLS data of branch angles are a valuable tool to quantify branch angles at larger scales.