3D stem model construction with geometry consistency using terrestrial laser scanning data

摘要

The traditional stem model is inconsistent with the real geometry of the stem. Terrestrial laser scanning (TLS) provides a possibility of constructing a realistic stem model. In this study, we present a 3D stem model, which includes the stem axis curve and stem cross-sectional profile curve, with geometrical consistency and stem parameter retrieval methods using TLS data. The 3D stem axis curve is interpolated based on the geometric central points, which are calculated from stem slices formed by stem cross-sections. From the 3D stem axis curve, the stem shape characteristic is clearly depicted in 3D space. Stem parameters, such as the location of a stem cross-section, stem diameter, height, length, curvature and torsion at any position along the stem, are calculated. The stem cross-sectional profile curve is interpolated based on the stem cross-sectional profile points, which are calculated from stem cross-sectional points by angle simplification. Then, the convex-concave characteristic of the stem cross-section is represented by the stem cross-sectional profile curve, and from this, the integral method for basal area calculation is presented. The presented methods were tested on stem points from different tree species with different shape properties. The feasibility and validity of the 3D stem model was demonstrated by 3D stem model visualization. The root mean square error (RMSE) of the presented stem diameter method was 0.129 cm. Compared with the basal area calculated from the cross-sectional profile curve, the mean absolute percentage error (MAPE) and RMSE values of the traditional method were 8.921% and 49.926 cm(2), respectively. The stem parameter retrieval experiment demonstrated the accuracy and practicability of the 3D stem model. Compared with the traditional stem model, the 3D stem model can accurately represent the geometric structure of the stem and provide accurate calculations of stem parameters. It will help improve the applications of TLS in forestry inventories.