Manual and ground penetrating radar field measurements of field-corn spacing, planting depth, and furrow feature identification

2020 ◽  
Vol 180 ◽  
pp. 104125
Author(s):  
Kenneth O.M. Mapoka ◽  
Stuart J. Birrell ◽  
David J. Eisenmann
Keyword(s):  
Ground Penetrating Radar ◽  
Field Measurements ◽  
Feature Identification ◽  
Planting Depth ◽  
Field Corn ◽  
Ground Penetrating

scholarly journals Object Detection of Ground-Penetrating Radar Signals Using Empirical Mode Decomposition and Dynamic Time Warping

Forests ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 230 ◽  
Author(s):  
Xi Wu ◽  
Christopher Adam Senalik ◽  
James Wacker ◽  
Xiping Wang ◽  
Guanghui Li
Keyword(s):  
Object Detection ◽  
Empirical Mode Decomposition ◽  
Ground Penetrating Radar ◽  
Dynamic Time Warping ◽  
Dielectric Constants ◽  
Time Warping ◽  
Feature Identification ◽  
Mode Decomposition ◽  
Dynamic Time ◽  
Ground Penetrating

An object detection method of ground-penetrating radar (GPR) signals using empirical mode decomposition (EMD) and dynamic time warping (DTW) is proposed in this study. Two groups of timber specimens were examined. The first group comprised of Douglas fir (Pseudotsuga menziesii) timber sections prepared in the laboratory with inserts of known internal characteristics. The second group comprised of timber girders salvaged from the timber bridges on historic Route 66 over 80 years. A GSSI Subsurface Interface Radar (SIR) System 4000 with a 2 GHz palm antenna was used to scan these two groups of specimens. GPR sensed differences in dielectric constants (DC) along the scan path caused by the presence of water, metal, or air within the wood. This study focuses on the feature identification and defect classification. The results show that the processing methods were efficient for the illustration of GPR information.

Vertical fracture detection by exploiting the polarization properties of ground‐penetrating radar signals

Geophysics ◽  
2004 ◽  
Vol 69 (3) ◽  
pp. 803-810 ◽  
Author(s):  
Georgios P. Tsoflias ◽  
Jean‐Paul Van Gestel ◽  
Paul L. Stoffa ◽  
Donald D. Blankenship ◽  
Mrinal Sen
Keyword(s):  
Ground Penetrating Radar ◽  
Field Measurements ◽  
Domain Modeling ◽  
Fracture Detection ◽  
Vertical Fracture ◽  
Phase Lead ◽  
Time Domain Modeling ◽  
Single Polarization ◽  
Ground Penetrating

Vertically oriented thin fractures are not always detected by conventional single‐polarization reflection profiling ground‐penetrating radar (GPR) techniques. We study the polarization properties of EM wavefields and suggest multipolarization acquisition surveying to detect the location and azimuth of vertically oriented fractures. We employ analytical solutions, 3D finite‐difference time‐domain modeling, and field measurements of multipolarization GPR data to investigate EM wave transmission through fractured geologic formations. For surface‐based multipolarization GPR measurements across vertical fractures, we observe a phase lead when the incident electric‐field component is oriented perpendicular to the plane of the fracture. This observation is consistent for nonmagnetic geologic environments and allows the determination of vertical fracture location and azimuth based on the presence of a phase difference and a phase lead relationship between varying polarization GPR data.

Estimating winter ebullition bubble volume in lake ice using ground-penetrating radar

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. H13-H25 ◽  
Author(s):  
Nadia Fantello ◽  
Andrew D. Parsekian ◽  
Katey M. Walter Anthony
Keyword(s):  
Ground Penetrating Radar ◽  
Growth Models ◽  
Field Measurements ◽  
Gas Content ◽  
Atmospheric Methane ◽  
Lake Ice ◽  
Electromagnetic Models ◽  
Lake Bottom Sediments ◽  
Ground Penetrating ◽  
Gas Volume

Freshwater lakes are an important source of atmospheric methane ([Formula: see text]); however, uncertainties associated with quantifying fluxes limit the accuracy of climate warming projections. Among emission pathways, ebullition (bubbling) is the principal and most challenging to account for given its spatial and temporal patchiness. When lakes freeze, many methane-rich bubbles escaping from lake-bottom sediments are temporarily trapped by downward-growing lake ice. Because bubble position is then seasonally fixed, we postulate that it should be possible to locate bubbles using a geophysical approach sensitive to perturbations in the ice-water interface and ice sheet structure generated by bubbles. We use ground-penetrating radar (GPR) to noninvasively quantify the amount of ebullition gas present in lake ice. To do this, an appropriate petrophysical transformation is required that relates radar wave velocity and volumetric gas content. We use laboratory experiments to show that electromagnetic models and volumetric mixing formulas were good representations of the gas volume-permittivity relationship. We found a standard deviation in dielectric permittivity between the models of 0.03, 0.03, and 0.02 for 20%, 50%, and 70% gas content, respectively. Second, by combining two GPR geometries (common and multioffset), we were able to locate bubbles and estimate gas volume with low uncertainty, with [Formula: see text] being the lowest uncertainty found and [Formula: see text] the largest. Finally, we found that GPR reflection patterns were associated with different previously identified ice-bubble classes. These geophysical results coupled with ancillary field measurements and ice-growth models also suggest how GPR can contribute to estimates of seasonal and annual ebullition fluxes over large spatiotemporal scales within and among lakes, thereby helping to reduce uncertainties in upscaled estimates of ecosystem methane emissions.

The efficacy of human observation for discrimination and feature identification of targets measured by the NIITEK ground-penetrating radar

2004 ◽  
Author(s):  
Chandra S. Throckmorton ◽  
Peter A. Torrione ◽  
Leslie M. Collins ◽  
Paul D. Gader ◽  
Wen-Hsiung Lee ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Feature Identification ◽  
Ground Penetrating

Conditional stochastic inversion of common-offset GPR reflection data

Geophysics ◽  
2021 ◽  
pp. 1-49
Author(s):  
Zhiwei Xu ◽  
James Irving ◽  
Yu Liu ◽  
Zhu Peimin ◽  
Klaus Holliger
Keyword(s):  
Ground Penetrating Radar ◽  
Synthetic Data ◽  
Field Measurements ◽  
Data Set ◽  
Stochastic Inversion ◽  
Reflection Data ◽  
Inversion Procedure ◽  
Borehole Logs ◽  
Ground Penetrating ◽  
Porosity Measurements

We present a stochastic inversion procedure for common-offset ground-penetrating radar (GPR) reflection measurements. Stochastic realizations of subsurface properties that offer an acceptable fit to GPR data are generated via simulated annealing optimization. The realizations are conditioned to borehole porosity measurements available along the GPR profile, or equivalent measurements of another petrophysical property that can be related to the dielectric permittivity, as well as to geostatistical parameters derived from the borehole logs and the processed GPR image. Validation of our inversion procedure is performed on a pertinent synthetic data set and indicates that the proposed method is capable of reliably recovering strongly heterogeneous porosity structures associated with surficial alluvial aquifers. This finding is largely corroborated through application of the methodology to field measurements from the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

scholarly journals Finite-difference time domain (FDTD) modeling of ground penetrating radar pulse energy for locating burial sites

2019 ◽  
Vol 67 (6) ◽  
pp. 1945-1953 ◽  
Author(s):  
Akinniyi Akinsunmade ◽  
Jerzy Karczewski ◽  
Ewelina Mazurkiewicz ◽  
Sylwia Tomecka-Suchoń
Keyword(s):  
Finite Difference ◽  
Time Domain ◽  
Pulse Energy ◽  
Ground Penetrating Radar ◽  
Finite Difference Time Domain ◽  
Field Measurements ◽  
Data Interpretation ◽  
Real Field ◽  
Ground Penetrating ◽  
Difference Time

Abstract Analysis of the finite-difference time domain (FDTD) numerical simulation of ground penetrating radar (GPR) measurement for locating burial sites is described in this paper. Effective, efficient, and reliability interpretation of GPR field data obtained from clandestine sites is very crucial in forensic investigations. The main goal of the study is the prediction of the change in the interaction of the electromagnetic incident on changes in buried bodies with time. In order to achieve this, the research involves the modeling of the GPR electromagnetic pulse energy responses to simulated changes in buried body with time with a view to understand what the results of real field measurement will give. The field measurements were conducted with GPR system manufactured by Mala Geoscience with antennae frequency of 500 MHz, 250 MHz, and 100 MHz. Responses from both synthetic and field radargrams depict the target was intercepted at same time (approximately 25 ns). The results have demonstrated that FDTD modeling is an important tool for enhancing the reliability of GPR data interpretation particularly for forensic study.

scholarly journals Using gprMax to Model Ground-Penetrating Radar (GPR) to Locate Corn Seed as an Attempt to Measure Planting Depth

2019 ◽  
Vol 62 (3) ◽  
pp. 673-686
Author(s):  
Kenneth O. M. Mapoka ◽  
Stuart J. Birrell ◽  
Mehari Z. Tekeste ◽  
Brian Steward ◽  
David Eisenmann
Keyword(s):  
Ground Penetrating Radar ◽  
Crop Production ◽  
Sandy Loam ◽  
Primary Objective ◽  
Response Amplitude ◽  
Yield Potential ◽  
Electromagnetic Properties ◽  
Planting Depth ◽  
Corn Seed ◽  
Ground Penetrating

Abstract. Planting depth (PD) plays an essential role in crop production by substantially impacting germination rates and yield potential. However, techniques to measure PD nondestructively have not been developed. A two-dimensional gprMax simulation study was conducted to investigate the effects of soil electromagnetic properties on ground-penetrating radar (GPR) waves. The primary objective was to examine the possibility of using GPR as a nondestructive sensor to detect subsurface corn seeds with the goal of measuring PD. A conventional fixed-offset gprMax antenna in contact with the soil surface was used in the simulations. Corn seed models of different materials and sizes were simulated, with properties of natural and synthetic (metal) corn seeds. The seed models were spherical, with radial dimensions of 0.006 and 0.024 m to simulate small and large corn seeds, respectively. Corn seed models were embedded in three homogeneous soil models (sandy loam, loam, and clay), and 1.6 and 2.6 GHz antenna models were used as excitation frequencies. A-scans and B-scans were obtained from the simulations. The A-scans showed that all targets (small natural corn and metal corn models, and large natural corm and metal corn models) successfully provided response amplitudes proportional to their dielectric properties in sandy loam and loam, but not in clay. In high bulk density soils, GPR waves failed to penetrate the soil models, and the targets were not detected. The 2.6 GHz antenna provided better response amplitudes from the targets. In the driest soil models (2.5%, and 5%), no response amplitude signatures were observed. In dry and relatively dry soil models (15%), the simulation times were much shorter to obtain a response amplitude from the targets (with feeble response amplitudes) compared to relatively wetter soils. To validate these models, laboratory experiments were conducted with three treatment factors (soil type, planting depth, and moisture content). In dry soils, corn seeds could be detected using a 2.6 GHz GPR antenna; however, the detection varied substantially within replicates of the same moisture group. Further research is necessary to understand the effects of soil moisture on the detection variability of buried corn seeds. Keywords: Corn seed, Dielectric permittivity, Electromagnetic waves, Finite difference time domain, GPR, gprMax.

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