Toward Detailed and Accurate Forest Inventory with Multi-Source Lidar Data

Accurate forest inventories are crucial for ecological research and resource management. A novel workflow is introduced to fuse lidar point clouds from terrestrial, mobile, and unmanned aerial vehicle systems, significantly improving the characterization of forest structure. The proposed method uses a robust coarse-to-fine registration and a quantitative voxel-based metric to evaluate the scanning completeness of single and fused data sets to derive accurate individual tree segmentation and forest parameter results. The work is validated using a unique data set (released on paper acceptance), and it demonstrates that fusing multi-source lidar data provides a more complete and accurate representation of forest ecosystems, underscoring its potential for more effective ecological monitoring and sustainable forest management.