Drone-borne Ground-Penetrating Radar for Digital Soil Mapping
(2024) AGROGEO — Location: Zürich (1.February.2024)
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- Abstract
- Characterizing soil hydrogeophysical properties has always been a vital task in various fields, including hydrology, meteorology, environmental sciences, and agriculture. Our studies collectively demonstrate the potential of drone-borne Ground Penetrating Radar (GPR) for high-resolution mapping of soil moisture and electrical conductivity at the field scale. We explore its application in precision agriculture and environmental monitoring. These studies aim to showcase the potential, benefits, and limitations of GPR for soil characterization at the field scale and provide insights into the factors influencing GPR measurements and inversion. The drone-borne GPR system for soil moisture mapping comprises a handheld vector network analyzer, a hybrid horn-dipole antenna, a GPS unit, a microcomputer, and a smartphone for remote control. Soil moisture and electrical conductivity are determined through full-wave inverse modeling based on the full-wave radar equation and Green’s functions for multilayered media. In the case of electrical conductivity characterization, we observe that the soil surface reflection coefficient becomes highly sensitive to electrical conductivity and less sensitive to permittivity when the frequency is relatively low, typically in the range of 15-45 MHz. This phenomenon is demonstrated and analyzed through numerical experiments. To validate our findings, we conducted field experiments and analyzed soil moisture and conductivity maps by comparing them with topographical conditions and results from electromagnetic induction (EMI) surveys. Furthermore, we investigated the effects of incidence angles and soil surface roughness on the inverse estimates. The former can be minimized or mitigated by using a less directive antenna or by considering the angles during calibration. The latter issue can be addressed by employing lower frequencies, depending on the prevailing roughness conditions.
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Citations
Wu, K., & Lambot, S. (2024). Drone-borne Ground-Penetrating Radar for Digital Soil Mapping. Agrogeo 24 Abstracts Agriculture and geophysics: Illuminating the subsurface!, 19. https://doi.org/10.62329/CUCY3610 (Original work published 2024)