Date of Award


Document Type


Degree Name

Master of Science (MS)


Environmental Engineering and Earth Science

Committee Chair/Advisor

Brady Flinchum

Committee Member

Ronald Falta

Committee Member

Ravi Ravichandran


Roots are critical to understanding tree health, subsurface biomass, and overall tree root stability. However, accessing tree roots is difficult and traditional methods used to quantify roots harm or kill the tree. Ground penetrating radar (GPR) provides a non-invasive way to characterize subsurface roots without harming the tree. GPR provides high-resolution data and the ability to collect data with high spatial coverage, making it an ideal tool for characterizing roots. GPR works by detecting contrasts in dielectric permittivity or electromagnetic (EM) velocity at interfaces between materials. Small scattering objects, like roots, generate predictable artifacts called diffraction hyperbolas. Diffraction hyperbolas will obscure subsurface structure but contain valuable information about the EM velocity of the soil because their shape depends on the mean root square of the velocity and the depth of the diffractor. We used diffraction hyperbolas to determine an average EM velocity and then used this velocity to apply a migration to remove the hyperbolas and clean up the image. We collected over 258 GPR lines at 10 cm spacing using a 500 MHz antenna. We set up the lines in three triangular grids remaining perpendicular to the radial direction centered over a large White Oak (Quercus alba) on Clemson’s campus. We hand fit ~1800 diffraction hyperbolas to show that the soil velocity was 0.091 m/ns, much faster than the commonly assumed 0.065 m/ns for soil. We used the average velocity to apply a F-K migration to every individual profile. On each profile, we calculated the instantaneous amplitude by taking the magnitude of the Hilbert Transform because roots show up as positive bulls-eye anomalies in this domain. We build depth sections where individual roots can be seen as deep as 1.36 m and extending as far as 8.6 m away from the trunk. These profiles can then be extracted and compiled at specific depths to create depth sections. Our data support two key observations: 1) obtaining an accurate migration velocity is critical to image roots, 2) Although improvements can still be made, GPR can be used to characterize root networks of trees with shallow (< 1.5 m) dendritic root networks. Using the methods presented in this thesis it is possible to estimate the subsurface biomass of the largest roots surrounding a given tree.



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