This invention discloses a method for determining the volume of a single
standing tree based on a backpack-mounted
lidar, belonging to the field of
forestry surveying and
remote sensing technology. During
system operation, the three-dimensional
point cloud acquired by the backpack-mounted
lidar is preprocessed, a unified coordinate
system is established, and non-terrestrial point clouds are extracted. Individual tree segmentation is achieved by combining density peak clustering and vertical profile
connectivity analysis, obtaining individual tree
point cloud clusters. Equally spaced evaluation
layers are divided along the tree height direction, and the effective
point density,
azimuth coverage, and normal vector consistency of each layer are calculated to determine the
data reliability level. A high-reliability layer is selected, and weighted
least squares circle fitting is used to obtain the center and
radius of the cross-section, which are then used as observation constraints. Typical
trunk tapers of the same
tree species and age group are introduced as morphological priors. The optimal parameterized surface model is solved through
Bayesian inference, and finally, the volume of a single
standing tree is calculated by integrating the Huber formula.