This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1190/geo2021-0602.1. This is version 2 of this Preprint.
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Abstract
Recent studies highlight the potential of the drone platform for
ground-penetrating radar (GPR) surveying. Most guidance for
optimizing drone flight heights is based on maximizing the image
quality of target responses, but no study yet considers the impact
on diffraction traveltimes. Strong GPR velocity contrasts across
the air-ground interface introduce significant refraction effects
that distort diffraction hyperbolas and introduce errors into diffraction-based velocity analysis. The severity of these errors is
explored with synthetic GPR responses, using ray- and finite-difference approaches, and a field GPR data set acquired over
a sequence of diffracting features buried up to 1 m depth.
Throughout, GPR antennas with 1000 MHz center frequency are
raised from the ground to heights <0.9 m (i.e., 0–3 times the
wavelength in air). Velocity estimates are within +10% of modeled values (spanning from 0.07 to 0.13 m/ns) if the antenna
height is within 1/2 wavelength in air above the ground surface.
Greater heights reduce diffraction curvature, damaging velocity
precision, and masking diffractions against a background of subhorizontal reflectivity. Field data highlight further problems of the
drone-based platform, with data dominated by reverberations in
the air gap and reduced spatial resolution of wavelets at target
depth. We suggest that a drone-based platform is unsuitable for
diffraction-based velocity analysis, and any future drone surveys
are benchmarked against ground-coupled data sets.
DOI
https://doi.org/10.31223/X5GS5K
Subjects
Earth Sciences, Geophysics and Seismology, Other Earth Sciences
Keywords
drone, diffraction, GPR, ground penetrating radar, velocity analysis
Dates
Published: 2021-09-06 11:13
Last Updated: 2022-07-19 00:23
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License
CC BY Attribution 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data Availability (Reason not available):
https://doi.org/10.6084/m9.figshare.16573025.v1
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