Slice-Relation-Clustering Framework via Horizontal Angle Information for 3-D Tree Roots Reconstruction

Tree root system 3-D reconstruction and spatial distribution analysis are the prevalent aspects of tree root investigation using ground penetrating radar (GPR). Precedent 3-D reconstruction methods are found to be effective in mapping simple, smooth root structures. However, repetitive and dense B-scans are needed; otherwise, the retrieved roots' spatial distribution and growth extension trend accuracy would deteriorate with the increase in the root systems' complexity. To address these issues, this article, for the first time, explores the possibility of integrating the horizontal angle information of the tree roots and a slice-relation-clustering (SRC) algorithm to reconstruct the complex tree root systems in a 3-D manner. The proposed framework, which takes the roots' horizontal angle as an analyzing condition instead of biological properties that are similar among neighboring branches used in the existing methods, clusters preprocessed and focused 2-D reflection patterns from the same single root together. The whole roots system is the combination of every single root cluster. Real measurement results show that our proposed method achieves a high efficiency in accurate root system reconstruction.

Automated summary

This article explores the integration of the horizontal angle information of tree roots and a slice-relation-clustering algorithm to reconstruct complex tree root systems in a 3-D manner. Real measurement results show that our proposed method achieves a high efficiency in accurate root system reconstruction.