A Processing Framework for Tree-Root Reconstruction Using Ground-Penetrating Radar Under Heterogeneous Soil Conditions

Since tree roots are important to ecosystems, particularly in the context of global climate change, better understanding of their organization is necessary. Ground-penetrating radar (GPR) appears a useful tool to that effect. In this contribution, a novel processing procedure to reconstruct 3-D root architectures from GPR data in heterogeneous environments is proposed, involving three main steps: 1) noise-related information is removed using singular value decomposition (SVD); 2) a modified version of randomized Hough transform (RHT) yields the soil dielectric constant; and 3) a matched-filter technique combined with Hilbert transform then operates as wave migration. Viability is first studied from comprehensive numerical simulations carried out with the gprMax software on a realistic root model in a 3-D heterogeneous environment. The heterogeneous soil effect is studied carefully through a number of simulations involving six different soil types. Then, controlled laboratory measurements are conducted on a root prototype using a bistatic GPR system involving folded complementary bowtie antennas in the frequency range of 300 MHz to 3.3 GHz. The 3-D results from both simulations and experiments show the good performance and potential of the proposed processing.