A processing framework for tree roots reconstruction using Ground-Penetrating Radar under heterogeneous soil conditions
Abstract
Since tree roots are important to ecosystems, particularly
in the context of global climate change, better understanding
their organization is necessary. Ground-penetrating radar
(GPR) appears a useful tool to that effect. In this contribution, a
novel processing procedure to reconstruct 3D root architectures
from GPR data in heterogeneous environments is proposed,
involving three main steps: (i) noise-related information is removed
using Singular Value Decomposition (SVD), (ii) a modified
version of Randomized Hough Transform (RHT) yields the soil
dielectric constant, (iii) a matched filter technique combined with
Hilbert Transform then operates as wave migration. Viability is
first studied from comprehensive numerical simulations carried
out with gprMax software on a realistic root model in a 3D
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 bi-static GPR system
involving folded complementary bowtie antennas in the 300 MHz
to 3.3 GHz frequency range. 3D results from both simulations
and experiments show the good performance and potential of the
proposed processing.