Mobile Laser Scanning for Estimating Tree Structural Attributes in a Temperate Hardwood Forests
Keywords:Tree structural attributes, hardwood forests, mobile lidar
The emergence of mobile lidar (MLS) in forestry has the potential to revolutionize forest inventory. Their speed and ease of use make them particularly effective for field data collection. Current approaches to predicting merchantable wood volume are based on allometric equations that are independent of tree shape and geometry. There are known biases and errors associated with this simplification, particularly for hardwood trees. The use of quantitative structure model (QSM) algorithms to estimate wood volume from 3D point clouds represents a promising alternative to destructive measurements for developing allometric models. The results of the study demonstrate that the new generations of MLS provide accurate estimates of diameter at breast height, tree height, crown dimensions, and main stem merchantable wood volume compared to destructive data and terrestrial lidar. These results are an important step toward the next generation of improved ground-based mobile lidar forest inventories. In this presentation, I will share necessary information so that practitioners can embrace this technology right away.