Annual Shoot Segmentation and Physiological Age Classification from TLS Data in Trees with Acrotonic Growth

The development of terrestrial laser scanning (TLS) has opened new avenues in the study trees. Although TLS provides valuable information on structural elements, fine-scale analysis, e.g., at annual shoots (AS) scale, is currently not possible. We present a model to segment and classify AS from tree skeletons into finite set “physiological ages” (i.e., state specialization physiological age (PA)). When testing against perfect data, 90% year 99% ages were correctly extracted. length-estimated errors varied between 0.39 cm 2.57 depending PA. applying reconstructions using real-life simulated 50% 77% total length are reconstructed. Using an architectural automaton deal with non-reconstructed short axes, associated number reduced 5% 12%, respectively. Finally, was applied real trees consistent previous findings obtained manual measurements similar context. This method could be used for determining phenotype or analyzing architecture.