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3D mapping of tree roots is a popular ground-penetrating radar (GPR)application. In real field tests, the recognition of tree roots suffers due tonoisey reflection patterns from subsurface targets that are not of interest,such as rocks, cavities, soil unevenness, etc. A Slice-Connection ClusteringAlgorithm (SCC) is applied to separate the regions of interest from each otherin a reconstructed 3D image. The proposed method can successfully recognize theradar signatures of the roots and distinguish roots from other objects.Meanwhile, most noise radar features are ignored through our method. The final3D mapping of the radargram obtained by the method can be used to estimate thelocation and extension trend of the tree roots. The effectiveness of theproposed system is tested on real GPR data.

Slice-Connection Clustering Algorithm for Tree Roots Recognition in Noisy 3D GPR Data