Accurate Tree Roots Positioning and Sizing over Undulated Ground Surfaces by Common Offset GPR Measurements

TL;DR

This paper introduces a novel method for accurately detecting and sizing tree roots using GPR over undulated ground surfaces by accounting for surface variations in the analysis, validated through simulations and field tests.

Contribution

It proposes a new fitting method based on electromagnetic wave travel time that considers uneven ground surfaces, improving root detection accuracy over traditional hyperbolic fitting methods.

Findings

The proposed method improves root positioning accuracy on undulating terrains.

Field experiments confirm the effectiveness of the new fitting models.

Numerical examples demonstrate better performance compared to standard methods.

Abstract

Tree roots detection is a popular application of the Ground-penetrating radar (GPR). Normally, the ground surface above the tree roots is assumed to be flat, and standard processing methods based on hyperbolic fitting are applied to the hyperbolae reflection patterns of tree roots for detection purposes. When the surface of the land is undulating (not flat), these typical hyperbolic fitting methods becomes inaccurate. This is because, the reflection patterns change with the uneven ground surfaces. When the soil surface is not flat, it is inaccurate to use the peak point of an asymmetric reflection pattern to identify the depth and horizontal position of the underground target. The reflection patterns of the complex shapes due to extreme surface variations results in analysis difficulties. Furthermore, when multiple objects are buried under an undulating ground, it is hard to judge their relative positions based on a B-scan that assumes a flat ground. In this paper, a roots fitting method based on electromagnetic waves (EM) travel time analysis is proposed to take into consideration the realistic undulating ground surface. A wheel-based (WB) GPR and an antenna-height-fixed (AHF) GPR System are presented, and their corresponding fitting models are proposed. The effectiveness of the proposed method is demonstrated and validated through numerical examples and field experiments.