Automatic dual-polarized ground penetrating radar for enhanced 3-D tree roots system architecture reconstruction

• Main Authors: Luo, Wenhao, Lee, Yee Hui, Hao, Tong, Mohamed Lokman Mohd Yusof, Yucel, Abdulkadir C.
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2025
• Subjects: Engineering; Dual-polarized ground penetrating radar; Optimized slice relation clustering
• Online Access: https://hdl.handle.net/10356/182298
• Institution: Nanyang Technological University

Tree root systems are crucial for providing structural support and stability to trees. However, in urban environments, they can pose challenges due to potential conflicts with the foundations of roads and infrastructure, leading to significant damage. Therefore, there is a pressing need to investigate the subsurface tree root system architecture (RSA). Ground-penetrating radar (GPR) has emerged as a powerful tool for this purpose, offering high-resolution and nondestructive testing (NDT) capabilities. One of the primary challenges in enhancing GPR's ability to detect roots lies in accurately reconstructing the 3-D structure of complex RSAs. This challenge is exacerbated by subsurface heterogeneity and intricate interlacement of root branches, which can result in erroneous stacking of 2-D root points during 3-D reconstruction. This study introduces a novel approach using our developed wheel-based dual-polarized GPR system capable of capturing four polarimetric scattering parameters at each scan point through automated zigzag movements. A dedicated radar signal processing framework analyzes these dual-polarized signals to extract essential root parameters. These parameters are then used in an optimized slice relation clustering (OSRC) algorithm, specifically designed for improving the reconstruction of complex RSA. The efficacy of integrating root parameters derived from dual-polarized GPR signals into the OSRC algorithm is initially evaluated through simulations to assess its capability in RSA reconstruction. Subsequently, the GPR system and processing methodology are validated under real-world conditions using natural Angsana tree root systems. The findings demonstrate a promising methodology for enhancing the accurate reconstruction of intricate 3-D tree RSA structures.