Study on Individual Tree Segmentation of Different Tree Species Using Different Segmentation Algorithms Based on 3D UAV Data

Individual structural parameters of trees, such as forest stand tree height and biomass, serve the foundation for monitoring dynamic changes in resources. are closely related to individual crown segmentation. Although three-dimensional (3D) data have been successfully used determine segmentation, this phenomenon is influenced by various factors, (i) source 3D data, (ii) segmentation algorithm, (iii) species. To further quantify effect factors on light detection ranging (LiDAR) image-derived points were obtained unmanned aerial vehicles (UAVs). Three different algorithms (PointNet++, Li2012, layer-stacking (LSS)) segment crowns four The results show that two accuracy LiDAR was generally better than using with a maximum difference 0.13 F values. For three algorithms, PointNet++ algorithm best, an value 0.91, whereas result LSS yields worst result, 0.86. Among tested species, Liriodendron chinense followed Magnolia grandiflora Osmanthus fragrans, Ficus microcarpa worst. Similar trees observed based data. fragrans superior according determined These demonstrate species all impact trees. greatest, source. Consequently, future research acquisition methods should be selected deep learning adopted improve