A method for determining the volume of a single standing tree based on a backpack-type lidar

Abstract

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.

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