Impacts of Soil Physicochemical Properties and Temporal‐Seasonal Soil‐Environmental Status on Ground‐Penetrating Radar Response

Sarkar, Reshmi; Paul, K. B.; Higgins, Todd R.

doi:10.2136/sssaj2018.10.0388

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…The interior of the void is generally air with a relative dielectric constant of 1, and the relative dielectric constant of road materials was generally between 3 and 10. The electromagnetic wave emitted by 3D GPR will be reflected at the interface between the void and road material (Sarkar et al, 2019;Wang et al, 2020b).…”

Section: Principle Of Void Detection Of 3d Ground-penetrating Radarmentioning

confidence: 99%

Research on Void Signal Recognition Algorithm of 3D Ground-Penetrating Radar Based on the Digital Image

Huang

Tang³

et al. 2022

Front. Mater.

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The three-dimensional ground-penetrating radar system is an effective method to detect road void disease. Ground penetrating radar image interpretation has the characteristics of multi-solution, long interpretation period, and high professional requirements of processors. In recent years, researchers have put forward solutions for automatic interpretation of ground-penetrating radar images, including automatic detection algorithm for subgrade diseases based on support vector machines, etc., but there are still some shortcomings such as training models with a large amount of data or setting parameters. In this article, a three-dimensional ground-penetrating radar void signal recognition algorithm based on the digital image is proposed, and the algorithm uses digital images to characterize radar signals. With the help of digital image processing methods, the images are processed by binarization, corrosion, expansion, connected area inspection, fine length index inspection, and three-dimensional matching inspection, so as to identify and determine the void signals and extract the void area volume index. The algorithm has been verified by laboratory tests and engineering projects, and the results show that the void identification algorithm can accurately identify the void area position; the error level between the measured values and the measured values of length, width, buried depth, and area is between 2.2 and 17.3%, and the error is generally within the engineering acceptance range. The volume index calculated by the algorithm has a certain engineering application value; compared with the support vector machine, the regressive convolution neural network, and other recognition methods, it has the advantage of not needing a large amount of data to train or modify parameters.

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Section: Principle Of Void Detection Of 3d Ground-penetrating Radarmentioning

confidence: 99%

Research on Void Signal Recognition Algorithm of 3D Ground-Penetrating Radar Based on the Digital Image

Huang

Tang³

et al. 2022

Front. Mater.

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“…GPR methods were also previously used to indirectly measure water flow (e.g., Zhang et al, 2014;Guo et al, 2020) as well as root density (e.g., Hruska et al, 1999;Guo et al, 2013). Interpreting the interplay of GPR signals with physical and chemical regolith properties is challenging (e.g., Saarenketo, 1998;Sucre et al, 2011;Tosti et al, 2013;Sarkar et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Comparison of regolith physical and chemical characteristics with geophysical data along a climate and ecological gradient, Chilean Coastal Cordillera (26 to 38° S)

Schaller¹,

Bo²,

Ehlers³

et al. 2020

SOIL

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Abstract. We combine geophysical observations from ground-penetrating radar (GPR) with regolith physical and chemical properties from pedons excavated in four study areas spanning 1300 km of the climate and ecological gradient in the Chilean Coastal Cordillera. Our aims are the following: (1) to relate GPR observations to depth-varying regolith physical and weathering-related chemical properties in adjacent pedons and (2) to evaluate the lateral extent to which these properties can be extrapolated along a hillslope using GPR observations. Physical observations considered include regolith bulk density and grain size distribution, whereas chemical observations are based on major and trace element analysis. Results indicate that visually determined pedolith thickness and the transition from the B to C horizons generally correlate with maximums in the 500 and 1000 MHz GPR envelope profiles. To a lesser degree, these maximums in the GPR envelope profiles agree with maximums in weathering-related indices such as the chemical index of alteration (CIA) and the chemical index of mass transfer (τ) for Na. Finally, we find that upscaling from the pedon to hillslope scale is possible with geophysical methods for certain pedon properties. Taken together, these findings suggest that the GPR profiles down hillslopes can be used to infer lateral thickness variations in pedolith horizons in different ecologic and climate settings, and to some degree the physical and chemical variations with depth.

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“…Interpreting the interplay of GPR signals with physical and chemical soil properties within the sub-surface is challenging and not well-understood (e.g., Saarenketo, 1999;Sucre et al, 2011;Tosti et al, 2013;Sarkar et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Comparison of soil characteristics from geophysical and geochemical techniques along a climate and ecological gradient, Chilean Coastal Cordillera (26° to 38° S)

Schaller

Ehlers

et al. 2020

Preprint

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Abstract. In this study, we combine geophysical observations from Ground Penetrating Radar (GPR) with soil physical, and geochemical properties from pedons excavated in four study areas spanning 1,300 km of the climate and ecological gradient in the Chilean Coastal Cordillera. Our aims are to: (1) relate GPR observations to depth varying soil physical and weathering-related chemical properties in adjacent pedons, and (2) evaluate the lateral extent to which these properties can be extrapolated along a hillslope using GPR observations. Physical observations considered include soil bulk density and grain size distribution whereas chemical observations are based on major and trace element analysis. Results indicate that visually-determined soil thickness and the transition from the soil B to C horizons generally correlate with maximums in the 500 and 1000 MHz GPR envelope profiles. To a lesser degree, these maximums in the GPR envelope profiles agree with maximums in weathering related indices such as the Chemical Index of Alteration (CIA) and the chemical index of mass transfer (τ) for Na. Finally, we find that up-scaling from the pedon to hillslope scale is possible with geophysical methods for certain pedon properties available. Taken together, these findings suggest that the GPR profiles along hillslopes can be used to infer lateral thickness variations in soil horizons, and to some degree the physical and chemical variations with depth.

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Impacts of Soil Physicochemical Properties and Temporal‐Seasonal Soil‐Environmental Status on Ground‐Penetrating Radar Response

Cited by 5 publications

References 33 publications

Research on Void Signal Recognition Algorithm of 3D Ground-Penetrating Radar Based on the Digital Image

Research on Void Signal Recognition Algorithm of 3D Ground-Penetrating Radar Based on the Digital Image

Comparison of regolith physical and chemical characteristics with geophysical data along a climate and ecological gradient, Chilean Coastal Cordillera (26 to 38° S)

Comparison of soil characteristics from geophysical and geochemical techniques along a climate and ecological gradient, Chilean Coastal Cordillera (26° to 38° S)

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