Nondestructive Tree Stem And Crown Volume Allometry In Hybrid Poplar Plantations Derived From Terrestrial Laser Scanning

Accurate and frequently updated tree volume estimates are required for poplar plantations, which are characterized by fast growth rate and short rotation. In this study, we tested the potential of terrestrial laser scanning (TLS) as a reliable method for developing nondestructive tree volume allometries in poplar plantations. The trial was conducted in Italy, where 4- to 10-year-old hybrid plantations were sampled to develop tree crown volume allometry in leaf-on conditions, tree stem volume, and height-diameter allometries in leaf-off conditions. We tested one-entry models based on diameter and two-entry models based on both diameter and height. Model performance was assessed by residual analysis. Results indicate that TLS can provide accurate models of tree stem and crown volume, with percentage of root-mean-square error of about 20 percent and 15 percent, respectively. The inclusion of height does not bring relevant improvement in the models, so that only diameter can be used to predict tree stem and crown volume. The TLS-measured stem volume estimates agreed with an available formula derived from harvesting. We concluded that TLS is a reliable method for developing nondestructive volume allometries in poplar plantations and holds great potential to enhance conventional tree inventory and monitoring.Study Implications: Terrestrial laser scanning (TLS) is a technique that allows nondestructive measurement of the three-dimensional structure of a tree with high precision and low cost. The ability of TLS to measure both tree crown volume and tree position can be effective to test optimal spacing requirements and also to test innovative schemes such as mixed or polycyclic poplar plantations. The spatially explicit nature of TLS measurements allows better integration with different remotely sensed sensors, which can be used in combination with TLS, enabling a multiscale assessment of poplar plantation structure with different levels of detail, enhancing conventional tree inventory and supporting effective management strategies.