Method for Extracting Tree Diameter at Breast Height Based on Vehicle-Mounted LiDAR
DOI:
https://doi.org/10.63313/AJET.9048Keywords:
Vehicle-borne LiDAR, Fitting, Roughness, Least Squares, DBHAbstract
Addressing the issues of low fitting efficiency and precision in the process of fitting tree diameter at breast height (DBH) using vehicle-mounted LiDAR point clouds, this paper proposes an energy function model based on least squares roughness constraint weighting to compensate for fitting accuracy and improve the extraction method of tree DBH parameters. Through fitting and comparative analysis of tree DBH using the energy function on roads in the experimental area, the accuracy of DBH extraction has been significantly improved, with the mean absolute error (MAE) of road tree DBH being 1.70 cm and the root mean square error (RMSE) being 2.60 cm. The results indicate that working on only one side of the tree, namely the side visible from the road, is still feasible for approximating different DBH structural parameters using precise fitting.
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