Ground Penetrating Radar (GPR) Techniques and Applications

Topic Information

Dear Colleagues,

This Topic aims to collect high-quality submissions in the research field of ground-penetrating radar (GPR). We encourage researchers from various fields within the journals’ scope to contribute papers highlighting the latest developments in their research field or to invite relevant experts and colleagues to do so. The topic includes but is not limited to: 

• GPR theory
• GPR in architecture
• GPR in engineering
• GPR in geology
• GPR in archaeology and cultural heritage
• GPR in agriculture and forest science
• GPR in forensic science
• Design, realization, and testing of GPR systems and antennas
• GPR data processing and analysis
• Modeling and inversion methods for GPR
• Applications of GPR in the geosciences
• Applications of GPR in water management
• New data processing algorithms
• Combined use of GPR and other remote sensing techniques.

Both original research articles and comprehensive review papers are welcome.

Dr. Pier Matteo Barone
Dr. Alastair Ruffell
Dr. Carlotta Ferrara
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Electronics electronics	2.6	5.3	2012	16.4 Days	CHF 2400
Eng eng	-	2.1	2020	21.5 Days	CHF 1200
Forensic Sciences forensicsci	-	1.7	2021	20.8 Days	CHF 1000
Forests forests	2.4	4.4	2010	16.2 Days	CHF 2600
Geosciences geosciences	2.4	5.3	2011	23.5 Days	CHF 1800
Heritage heritage	2.0	2.9	2018	19.8 Days	CHF 1600
Infrastructures infrastructures	2.7	5.2	2016	17.8 Days	CHF 1800
Remote Sensing remotesensing	4.2	8.3	2009	23.9 Days	CHF 2700

Preprints.org is a multidisciplinary platform offering a preprint service designed to facilitate the early sharing of your research. It supports and empowers your research journey from the very beginning.

MDPI Topics is collaborating with Preprints.org and has established a direct connection between MDPI journals and the platform. Authors are encouraged to take advantage of this opportunity by posting their preprints at Preprints.org prior to publication:

1. Share your research immediately: disseminate your ideas prior to publication and establish priority for your work.
2. Safeguard your intellectual contribution: Protect your ideas with a time-stamped preprint that serves as proof of your research timeline.
3. Boost visibility and impact: Increase the reach and influence of your research by making it accessible to a global audience.
4. Gain early feedback: Receive valuable input and insights from peers before submitting to a journal.
5. Ensure broad indexing: Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Related Topic

Published Papers (15 papers)

Order results

Content type Publication Date

Result details

Normal Extended Compact

Journals

All Electronics Eng Forensic Sciences Forests Geosciences Heritage Infrastructures Remote Sensing

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

Error

Oops... you haven't selected anything for export.

Ok

clear

22 pages, 26127 KiB  

Open AccessArticle

Defect Recognition: Applying Time-Lapse GPR Measurements and Numerical Approaches

by Enas Abdelsamei, Diaa Sheishah, Mohamed Aldeep, Csaba Tóth and György Sipos

Eng 2025, 6(1), 5; https://doi.org/10.3390/eng6010005 - 1 Jan 2025

Cited by 1 | Viewed by 937

Abstract

Roads are critical components of infrastructure, and assessing their quality is essential to ensure the safe transport of people and goods, which in turn supports economic prosperity. Various factors, such as subsurface conditions, moisture content, and temperature, influence road performance and can degrade [...] Read more.

Roads are critical components of infrastructure, and assessing their quality is essential to ensure the safe transport of people and goods, which in turn supports economic prosperity. Various factors, such as subsurface conditions, moisture content, and temperature, influence road performance and can degrade their efficiency as transportation networks. While surface road defects can often be identified through visual inspection, information about subsurface extensions, their impact on structural integrity, and potential risks remain concealed. This study aimed to perform a comparative analysis of dielectric permittivity (ε) using time-lapse Ground Penetrating Radar (GPR) measurements on pre- and post-renovated road sections. This study also sought to evaluate the effectiveness of this approach for road assessment and to employ forward modeling for a deeper understanding of road defects and their associated hazards. Results revealed that the pre-renovated road section exhibited significant fluctuations in dielectric values, ranging from 3.13 to 15.9. In contrast, the post-renovated section showed consistent values within a narrow range of 5 to 6.6. Different crack types were classified, and the mean ε for each visually identified crack type was calculated. Despite the higher frequency of transverse cracks compared to other defects, longitudinal cracks exhibited the highest mean dielectric value (~10.3), while alligator cracks had the lowest (~8.33). Numerical simulations facilitated accurate interpretation of the defects identified in the road section, providing insights into their nature and associated risks. The methodology used for crack classification and numerical simulation can be applied to other road sections globally, offering a standardized approach to road assessment and maintenance planning. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

22 pages, 4915 KiB  

Open AccessArticle

Mutual Interference Suppression and Signal Enhancement Method for Ground-Penetrating Radar Based on Deep Learning

by Wentai Lei, Xin Tan, Chaopeng Luo and Wei Xue

Electronics 2024, 13(23), 4722; https://doi.org/10.3390/electronics13234722 - 29 Nov 2024

Viewed by 985

Abstract

Ground-Penetrating Radar (GPR) is a non-destructive sensing technology that utilizes high electromagnetic frequencies. However, mutual interference waves caused by multiple scattering between targets can significantly complicate the interpretation of GPR B-scan images, especially when shallow targets obscure deeper ones. Existing methods primarily focus [...] Read more.

Ground-Penetrating Radar (GPR) is a non-destructive sensing technology that utilizes high electromagnetic frequencies. However, mutual interference waves caused by multiple scattering between targets can significantly complicate the interpretation of GPR B-scan images, especially when shallow targets obscure deeper ones. Existing methods primarily focus on extracting target signals from background clutter, frequently overlooking the impact of mutual interference. This paper proposes a convolutional neural network, termed MIS-SE-Net (Mutual Interference Suppression and Signal Enhancement Network), designed to suppress mutual interference waves while preserving shallow target signals and enhancing deeper ones. MIS-SE-Net incorporates attention gates into its encoder–decoder architecture, thereby improving its capabilities in interference suppression and enhancement of weak signals. The network is optimized using a combination of Mean Absolute Error (MAE) loss and perceptual loss. To evaluate MIS-SE-Net, the multi-scale weighted back projection (MWBP) imaging algorithm is used. Simulation results show that after processing with MIS-SE-Net, the integrated side-lobe ratio (ISLR) metric of MWBP imaging decreases by an average of 2.37%, while the signal-to-clutter ratio (SCR) increases by an average of 1.65%. For measured data, results show an average decrease of 7.51% in ISLR and an increase of 2.47% in SCR. These findings validate the effectiveness of the proposed method in suppressing interference, enhancing weak signals, and improving imaging quality. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

13 pages, 3778 KiB  

Open AccessArticle

Preliminary Insights on Moisture Content Measurement in Square Timbers Using GPR Signals and 1D-CNN Models

by Jiaxing Guo, Huadong Xu, Yan Zhong and Kuanjie Yu

Forests 2024, 15(10), 1800; https://doi.org/10.3390/f15101800 - 14 Oct 2024

Cited by 1 | Viewed by 1041

Abstract

Accurately measuring the moisture content (MC) of square timber is crucial for ensuring the quality and performance of wood products in wood processing. Traditional MC detection methods have certain limitations. Therefore, this study developed a one-dimensional convolutional neural network (1D-CNN) model based on [...] Read more.

Accurately measuring the moisture content (MC) of square timber is crucial for ensuring the quality and performance of wood products in wood processing. Traditional MC detection methods have certain limitations. Therefore, this study developed a one-dimensional convolutional neural network (1D-CNN) model based on the first 8 nanoseconds of ground-penetrating radar (GPR) signals to predict the MC of square timber. The study found that the mixed-species model exhibited effective predictive performance (R² = 0.9864, RMSE = 0.0393) across the tree species red spruce, Dahurian larch, European white birch, and Manchurian ash (MC range 0%–133.1%), while single-species models showed even higher accuracy (R² ≥ 0.9876, RMSE ≤ 0.0358). Additionally, the 1D-CNN model outperformed other algorithms in automatically capturing complex patterns in GPR full-waveform amplitude data. Moreover, the algorithms based on full-waveform amplitude data demonstrated significant advantages in detecting wood MC compared to those based on a traditional time–frequency feature parameter. These results indicate that the 1D-CNN model can be used to optimize the drying process and detect the MC of load-bearing timber in construction and bridge engineering. Future work will focus on expanding the dataset, further optimizing the algorithm, and validating the models in industrial applications to enhance their reliability and applicability. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

19 pages, 11916 KiB  

Open AccessArticle

Ground Penetrating Radar (GPR) Investigations in Urban Areas Affected by Gravity-Driven Deformations

by Nicola Angelo Famiglietti, Pietro Miele, Bruno Massa, Antonino Memmolo, Raffaele Moschillo, Luigi Zarrilli and Annamaria Vicari

Geosciences 2024, 14(8), 222; https://doi.org/10.3390/geosciences14080222 - 20 Aug 2024

Viewed by 1895

Abstract

The 1980 Ms 6.9 Irpinia earthquake was responsible for the activation or reactivation of numerous gravitative deformations mainly hosted by clayey lithotypes, affecting wide areas of Benevento Province and the Sele and Ofanto R. Valleys. The case of Calitri offers valuable insights into [...] Read more.

The 1980 Ms 6.9 Irpinia earthquake was responsible for the activation or reactivation of numerous gravitative deformations mainly hosted by clayey lithotypes, affecting wide areas of Benevento Province and the Sele and Ofanto R. Valleys. The case of Calitri offers valuable insights into a methodological approach to studying mass movements affecting human settlements. Post-earthquake investigations in Calitri involved extensive geognostic boreholes and in situ surveys, providing substantial data for lithological characterization and landslide modeling. Additionally, over the past two decades, satellite-based techniques have supported the mapping and characterization of ground deformations in this area, improving our understanding of spatiotemporal evolution. Despite these efforts, a detailed subsurface comprehensionof the tectono-stratigraphy and geometriesof gravity-induced deformation remains incomplete. This study aims to enhance our knowledge of gravity-driven deformations affecting urban areas by using deep-penetrating GroundPenetrating Radar (GPR) surveys to identify landslide-related structures, rupture surfaces, and lithological characterization of the involved lithotypes. The integration of GPR surveys with classical morphotectonic analysis led to the delineation of the main subsurface discontinuities (stratigraphy, tectonics, and gravity-related), correlating them with available geognostic data. This approach provided non-invasive, detailed insights into subsurface features and stands out as one of the rare case studies in Italy that employed the GPR method for landslide investigations. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

33 pages, 5501 KiB  

Open AccessEditor’s ChoiceArticle

Using Geophysics to Locate Holocaust Era Mass Graves in Jewish Cemeteries: Examples from Latvia and Lithuania

by Philip Reeder, Harry Jol, Alastair McClymont, Paul Bauman and Michael Barrow

Heritage 2024, 7(7), 3766-3798; https://doi.org/10.3390/heritage7070179 - 16 Jul 2024

Cited by 1 | Viewed by 1847

Abstract

A common practice used by the Germans and collaborators in World War II, as part of the Holocaust, was to use existing Jewish cemeteries as places for mass burial. Research was completed at the Old Jewish Cemetery in Riga, Latvia, the Livas Jewish [...] Read more.

A common practice used by the Germans and collaborators in World War II, as part of the Holocaust, was to use existing Jewish cemeteries as places for mass burial. Research was completed at the Old Jewish Cemetery in Riga, Latvia, the Livas Jewish Cemetery in Liepaja, Latvia, and the Zaliakalnis Jewish Cemetery in Kaunas, Lithuania. The Old Jewish Cemetery in Riga was adjacent to the Riga Ghetto and was used to bury individuals murdered in the ghetto. In Kaunas, an area of the Zaliakalnis Jewish Cemetery is devoid of grave stones, and literature sources and testimony indicate that this area was used for the mass burial of Jews from the Kaunas Ghetto and other mass killings. In Liepaja, the local Jewish Heritage Foundation believes that there are mass graves within the Livas Cemetery. Methodologies for this research include the use of a pulseEkko Pro 500-megahertz ground-penetrating radar (GPR) system. Electrical resistivity tomography (ERT) data were collected through a linear array of electrodes coupled to a direct current (DC) resistivity transmitter and receiver. Analysis of aerial photography and satellite images was also employed at each location. ERT and GPR data indicate three separate trench anomalies in the Old Jewish Cemetery in Riga. The presence of these anomalies corroborates Holocaust survivor testimony that bodies were buried in mass graves in that area. In the Zaliakalnis Jewish Cemetery in Kaunas, ERT and GPR data indicate an anomaly in the western part of the cemetery, and ERT data further indicate two other possible mass graves. In Liepaja, preliminary GPR analysis indicates an anomaly in a cleared section of the cemetery. Based on the presence of geophysical anomalies in all three cemeteries, which correlate with literature sources and Holocaust survivor testimony, there is a high probability that mass graves are present at each site. Future research directions include expanding the search areas in each cemetery, additional literature and testimony-based research, and the addition of other geophysical methodologies. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

22 pages, 9269 KiB  

Open AccessArticle

Reconstruction of High-Resolution 3D GPR Data from 2D Profiles: A Multiple-Point Statistical Approach

by Chongmin Zhang, Mathieu Gravey, Grégoire Mariéthoz and James Irving

Remote Sens. 2024, 16(12), 2084; https://doi.org/10.3390/rs16122084 - 8 Jun 2024

Viewed by 2088

Abstract

Ground-penetrating radar (GPR) is a popular geophysical tool for mapping the underground. High-resolution 3D GPR data carry a large amount of information and can greatly help to interpret complex subsurface geometries. However, such data require a dense collection along closely spaced parallel survey [...] Read more.

Ground-penetrating radar (GPR) is a popular geophysical tool for mapping the underground. High-resolution 3D GPR data carry a large amount of information and can greatly help to interpret complex subsurface geometries. However, such data require a dense collection along closely spaced parallel survey lines, which is time consuming and costly. In many cases, for the sake of efficiency, a choice is made during 3D acquisitions to use a larger spacing between the profile lines, resulting in a dense measurement spacing along the lines but a much coarser one in the across-line direction. Simple interpolation methods are then commonly used to increase the sampling before interpretation, which can work well when the subsurface structures are already well sampled in the across-line direction but can distort such structures when this is not the case. In this work, we address the latter problem using a novel multiple-point geostatistical (MPS) simulation methodology. For a considered 3D GPR dataset with reduced sampling in the across-line direction, we attempt to reconstruct a more densely spaced, high-resolution dataset using a series of 2D conditional stochastic simulations in both the along-line and across-line directions. For these simulations, the existing profile data serve as training images from which complex spatial patterns are quantified and reproduced. To reduce discontinuities in the generated 3D spatial structures caused by independent 2D simulations, the target profile being simulated is chosen randomly, and simulations in the along-line and across-line directions are performed alternately. We show the successful application of our approach to 100 MHz synthetic and 200 MHz field GPR data under multiple decimation scenarios where survey lines are regularly deleted from a dense 3D reference dataset, and the corresponding reconstructions are compared with the original data. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

11 pages, 8194 KiB  

Open AccessCase Report

Unveiling the Hidden Secrets of Bomarzo Cathedral: New Evidence from Last Ground-Penetrating Radar Survey

by Pier Matteo Barone and Giovanni Lamoratta

Heritage 2023, 6(12), 7578-7588; https://doi.org/10.3390/heritage6120398 - 4 Dec 2023

Viewed by 1708

Abstract

The Bomarzo Cathedral, also known as the Duomo di Bomarzo, is a remarkable historical and architectural masterpiece situated in Bomarzo (VT), Italy. Constructed in the 16th century under the sponsorship of the Orsini family, the cathedral’s design is a harmonious blend of Renaissance [...] Read more.

The Bomarzo Cathedral, also known as the Duomo di Bomarzo, is a remarkable historical and architectural masterpiece situated in Bomarzo (VT), Italy. Constructed in the 16th century under the sponsorship of the Orsini family, the cathedral’s design is a harmonious blend of Renaissance and Baroque styles. Despite enduring numerous challenges, including damage from the Italian Wars, extensive restoration efforts were undertaken to preserve its cultural legacy. Driven by a deep appreciation of the cathedral’s historical context, a ground-penetrating radar (GPR) investigation was deployed to gain insights into its foundations and potentially uncover buried remains beneath the floor and altar. The GPR investigation focused on the cathedral’s interior, specifically the central and left naves, altar, and oratory. This revealed the presence of disclosed rectangular chambers beneath the floor and altar, along with unique foundation structures. These findings, coupled with historical insights and architectural understanding, emphasize the cathedral’s cultural importance. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

24 pages, 9328 KiB  

Open AccessArticle

Utilizing Ground-Penetrating Radar for Water Leak Detection and Pipe Material Characterization in Environmental Studies: A Case Study

by Mohamed Gamal, Qingyun Di, Jinhai Zhang, Changmin Fu, Shereen Ebrahim and Amr Abd El-Raouf

Remote Sens. 2023, 15(20), 4924; https://doi.org/10.3390/rs15204924 - 12 Oct 2023

Cited by 11 | Viewed by 8065

Abstract

Detecting and mapping subsurface utilities in urban areas is crucial for identifying defects or damages in drinking and sewage pipes that can cause leaks. These leaks make it difficult to accurately characterize the pipes due to changes in their reflective properties. This study [...] Read more.

Detecting and mapping subsurface utilities in urban areas is crucial for identifying defects or damages in drinking and sewage pipes that can cause leaks. These leaks make it difficult to accurately characterize the pipes due to changes in their reflective properties. This study focused on detecting leaks originating from underground pipes and distinguishing between these various types of pipes. It also aimed to create a visual fingerprint model that displays the reflection characteristics of these pipes during different leak conditions, enabling efficient maintenance and handling procedures on the pipes. To achieve this, a finite-difference time-domain (FDTD) method was used to simulate two types of pipe materials with and without leak areas to construct different scenarios. Additionally, a ground-penetrating radar (GPR) field survey was conducted using a 600 MHz antenna in a part of the El Hammam area on Egypt’s northwest coast. The simulated images produced with numerical modeling were compared with the radar profiles obtained using GPR at particular locations. The numerical simulations and radar profiles demonstrated the noticeable influence of water leaks from the different pipes, wherein the reflection of saturated soil waves was interrupted due to the presence of saturated soil. Envelope and migration techniques were employed in a new application to accurately distinguish between different pipe types, specifically focusing on leak areas. The strong correlation between the real radar profile and the specific signal of a water pipe leak in the simulated models suggests that GPR is a reliable non-destructive geophysical method for detecting water pipe leaks and distinguishing between the different pipe materials in various field conditions. The simulated models, which serve as image-matching fingerprints to identify and map water pipe leaks, help us to comprehend reality better. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Graphical abstract

18 pages, 16356 KiB  

Open AccessTechnical Note

Processing GPR Surveys in Civil Engineering to Locate Buried Structures in Highly Conductive Subsoils

by Rosendo Mendoza, Carlos Araque-Perez, Bruna Marinho, Javier Rey and Mari Carmen Hidalgo

Remote Sens. 2023, 15(16), 4019; https://doi.org/10.3390/rs15164019 - 14 Aug 2023

Cited by 3 | Viewed by 1955

Abstract

Many studies have illustrated the great benefit of ground-penetrating radar (GPR) in civil engineering. However, in some cases, this geophysical survey method does not produce the desired results due to the electromagnetic characteristics of the subsoil. This study presents the results obtained in [...] Read more.

Many studies have illustrated the great benefit of ground-penetrating radar (GPR) in civil engineering. However, in some cases, this geophysical survey method does not produce the desired results due to the electromagnetic characteristics of the subsoil. This study presents the results obtained in two locations near Linares (southern Spain), evaluating the detection of structures buried in conductive host materials (0.02 S/m in site 1 and 0.015 S/m in site 2) characterized by strong signal attenuation. Accounting for the study depth, which was 1.5 m, a 500 MHz shielded GPR antenna was used at both sites. At the first site, a controlled experiment was planned, and it consisted of burying three linear elements. An iron pipe, a PVC pipe, and a series of precast blocks were buried at a depth of 0.5 m in a subsoil composed of highly conductive clayey facies. To eliminate additional multiples caused by other superficial structures and increasing the high-frequency content, the predictive deconvolution flow was applied. In the 3D processing, the cover surfaces technique was used. Once the acquired GPR signals was analyzed and the optimal processing flow established, a second site in which different infrastructures in a conductive host medium formed by marly facies was explored. The 2D flow and 3D processing applied in this work allows to detect and see the continuity of some structures not visible for the default processing. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Graphical abstract

20 pages, 4818 KiB  

Open AccessArticle

TSVR-Net: An End-to-End Ground-Penetrating Radar Images Registration and Location Network

by Beizhen Bi, Liang Shen, Pengyu Zhang, Xiaotao Huang, Qin Xin and Tian Jin

Remote Sens. 2023, 15(13), 3428; https://doi.org/10.3390/rs15133428 - 6 Jul 2023

Cited by 4 | Viewed by 2000

Abstract

Stable and reliable autonomous localization technology is fundamental for realizing autonomous driving. Localization systems based on global positioning system (GPS), cameras, LIDAR, etc., can be affected by building occlusion or drastic changes in the environment. These effects can degrade the localization accuracy and [...] Read more.

Stable and reliable autonomous localization technology is fundamental for realizing autonomous driving. Localization systems based on global positioning system (GPS), cameras, LIDAR, etc., can be affected by building occlusion or drastic changes in the environment. These effects can degrade the localization accuracy and even cause the problem of localization failure. Localizing ground-penetrating radar (LGPR) as a new type of localization can rely only on robust subsurface information for autonomous localization. LGPR is mostly a 2D-2D registration process. This paper describes the LGPR as a slice-to-volume registration (SVR) problem and proposes an end-to-end TSVR-Net-based regression localization method. Firstly, the information of different dimensions in 3D data is used to ensure the high discriminative power of the data. Then the attention module is added to the design to make the network pay attention to important information and high discriminative regions while balancing the information weights of different dimensions. Eventually, it can directly regress to predict the current data location on the map. We designed several sets of experiments to verify the method’s effectiveness by a step-by-step analysis. The superiority of the proposed method over the current state-of-the-art LGPR method is also verified on five datasets. The experimental results show that both the deep learning method and the increase in dimensional information can improve the stability of the localization system. The proposed method exhibits excellent localization accuracy and better stability, providing a new concept to realize the stable and reliable real-time localization of ground-penetrating radar images. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Graphical abstract

20 pages, 11535 KiB  

Open AccessArticle

Quantitative Evaluation for the Internal Defects of Tree Trunks Based on the Wavefield Reconstruction Inversion Using Ground Penetrating Radar Data

by Deshan Feng, Yuxin Liu, Xun Wang, Siyuan Ding, Deru Xu and Jun Yang

Forests 2023, 14(5), 912; https://doi.org/10.3390/f14050912 - 28 Apr 2023

Cited by 2 | Viewed by 2015

Abstract

A reliable inspection of the tree trunk internal defects is often considered vital in the health condition assessment for the living tree. There has been a desire to reconstruct the internal structure quantitatively using a non-destructive testing technology. This paper intends to apply [...] Read more.

A reliable inspection of the tree trunk internal defects is often considered vital in the health condition assessment for the living tree. There has been a desire to reconstruct the internal structure quantitatively using a non-destructive testing technology. This paper intends to apply wavefield reconstruction inversion (WRI) to obtain high-precision information from tree trunk detection using ground penetrating radar data. The variational projection method and the grouped multi-frequency strategy are adopted to strengthen the algorithm stability and adaptability by inverting frequency components sequentially. Through an irregular trunk model test, the influence of the penalty parameter, initial model, frequency strategy, and grid generation methods are investigated on WRI. Additionally, the comparison between full waveform inversion and WRI is discussed in detail. This synthetic case indicates that WRI is efficient and for a reasonable result, a proper multi-frequency strategy and an accurate mesh closer to reality are important. Furthermore, a field case of a historical tree is used to prove the validity and reliability of the algorithm. The success in this case indicates that our algorithm can characterize the distribution of media parameters of tree trunks accurately, which could provide data support for the rejuvenation and maintenance of living trees. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

19 pages, 3786 KiB  

Open AccessCommunication

A Modular Method for GPR Hyperbolic Feature Detection and Quantitative Parameter Inversion of Underground Pipelines

by Chengke Zhu and Hongxia Ye

Remote Sens. 2023, 15(8), 2114; https://doi.org/10.3390/rs15082114 - 17 Apr 2023

Cited by 5 | Viewed by 4089

Abstract

Ground penetrating radar (GPR) is widely used to inspect underground pipelines because it is non-destructive. When the scan line of GPR is perpendicular to the pipe, it will exhibit hyperbolic features in GPR B-scan images, which have no intuitive relationship with the geometric [...] Read more.

Ground penetrating radar (GPR) is widely used to inspect underground pipelines because it is non-destructive. When the scan line of GPR is perpendicular to the pipe, it will exhibit hyperbolic features in GPR B-scan images, which have no intuitive relationship with the geometric and physical parameters of the pipeline, making the interpretation of GPR images difficult. This paper proposes a modular detection and quantitative inversion method for the hyperbolic features in GPR B-scan images, which is divided into two steps. In the first step, the YOLOv7 object detection network is used to automatically detect the hyperbolic features in GPR images. In the second step, a two-stage curve fitting method is proposed based on the characteristics of the detection model. It uses a few key point annotations of the hyperbolic pattern and some parameters of the GPR system to quantitatively invert the depth and radius of pipes. Using the same hardware and data set, YOLOv7 achieves an 11.1% improvement in detection accuracy and an 18.2% improvement in speed compared to YOLOv5. The relative errors of the proposed method for the depth and radius of the synthetic data in homogeneous media are 0.6% and 4.4%, respectively, and 4.8% and 15% in non-homogeneous media. The relative error of the depth inversion of the measured data TU1208 is less than 10%. The results show that the method can effectively invert the depth and radius of underground pipelines and reduce the difficulty of GPR data interpretation. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

22 pages, 5272 KiB  

Open AccessArticle

Efficient Underground Target Detection of Urban Roads in Ground-Penetrating Radar Images Based on Neural Networks

by Wei Xue, Kehui Chen, Ting Li, Li Liu and Jian Zhang

Remote Sens. 2023, 15(5), 1346; https://doi.org/10.3390/rs15051346 - 28 Feb 2023

Cited by 5 | Viewed by 2140

Abstract

Ground-penetrating radar (GPR) is an important nondestructive testing (NDT) tool for the underground exploration of urban roads. However, due to the large amount of GPR data, traditional manual interpretation is time-consuming and laborious. To address this problem, an efficient underground target detection method [...] Read more.

Ground-penetrating radar (GPR) is an important nondestructive testing (NDT) tool for the underground exploration of urban roads. However, due to the large amount of GPR data, traditional manual interpretation is time-consuming and laborious. To address this problem, an efficient underground target detection method for urban roads based on neural networks is proposed in this paper. First, robust principal component analysis (RPCA) is used to suppress the clutter in the B-scan image. Then, three time-domain statistics of each A-scan signal are calculated as its features, and one backpropagation (BP) neural network is adopted to recognize A-scan signals to obtain the horizontal regions of targets. Next, the fusion and deletion (FAD) algorithm is used to further optimize the horizontal regions of targets. Finally, three time-domain statistics of each segmented A-scan signal in the horizontal regions of targets are extracted as the features, and another BP neural network is employed to recognize the segmented A-scan signals to obtain the vertical regions of targets. The proposed method is verified with both simulation and real GPR data. The experimental results show that the proposed method can effectively locate the horizontal ranges and vertical depths of underground targets for urban roads and has higher recognition accuracy and less processing time than the traditional segmentation recognition methods. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Graphical abstract

9 pages, 3316 KiB  

Open AccessArticle

Improving FMCW GPR Precision through the CZT Algorithm for Pavement Thickness Measurements

by Tongxing Huang, Chaoyang Zhang, Dun Lu, Qiuyu Zeng, Wenjie Fu and Yang Yan

Electronics 2022, 11(21), 3524; https://doi.org/10.3390/electronics11213524 - 29 Oct 2022

Cited by 3 | Viewed by 2559

Abstract

Ground Penetrating Radar (GPR) application in road surface detection has been greatly developed in the past few decades, which enables rapid and economical estimation of pavement thickness and other physical properties in non-destructive testing (NDT) and non-contact testing (NCT). In recent years, with [...] Read more.

Ground Penetrating Radar (GPR) application in road surface detection has been greatly developed in the past few decades, which enables rapid and economical estimation of pavement thickness and other physical properties in non-destructive testing (NDT) and non-contact testing (NCT). In recent years, with the rapid development of microwave and millimeter-wave solid-state devices and digital signal processors, the cost of Frequency-Modulated Continuous-Wave (FMCW) radar has dropped significantly, with smaller size and lighter weight. Thereafter, FMCW GPR is considered to be applied during pavement inspection. To improve the precision of FMCW GPR for NDT and NCT of pavement thickness, a Chirp Z-transform (CZT) algorithm is introduced to FMCW GPR and investigated in this paper. A FMCW + CZT GPR at 2.5 GHz with a bandwidth of 1 GHz was built, and laboratory and field experiments were carried out. The experimental results demonstrate that the FMCW + CZT GPR radar can obtain the sample thickness with low error and recognize subtle thickness variations. This method realizes the high precision thickness measurement of shallow asphalt pavement by FMCW radar with a narrow bandwidth pulse signal and would provide a promising low-cost measurement solution for GPR. Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Figure 1

attachment

Supplementary material:
Supplementary File 1 (ZIP, 26861 KiB)

30 pages, 10476 KiB  

Open AccessArticle

Ground Penetrating Radar of Neotectonic Folds and Faults in South-Central Australia: Evolution of the Shallow Geophysical Structure of Fault-Propagation Folds with Increasing Strain

by Schirin Sellmann, Mark Quigley, Brendan Duffy and Ian Moffat

Geosciences 2022, 12(11), 395; https://doi.org/10.3390/geosciences12110395 - 26 Oct 2022

Cited by 2 | Viewed by 3359

Abstract

Using ground penetrating radar (GPR) we investigate the near surface (~0–10 m depth) geophysical structure of neotectonic fault-propagation folds and thrust faults in south-central Australia in varying stages of fold and fault growth. Variations in neotectonic fold scarp heights are interpreted to reflect [...] Read more.

Using ground penetrating radar (GPR) we investigate the near surface (~0–10 m depth) geophysical structure of neotectonic fault-propagation folds and thrust faults in south-central Australia in varying stages of fold and fault growth. Variations in neotectonic fold scarp heights are interpreted to reflect variations in accumulated slip on the underlying reverse faults. Fold scarps on the Nullarbor and Roe Plains are characterized by broad, asymmetric morphologies with vertical displacements of ~5 to ~40 m distributed over 1 to 2 km widths (~0.5 to ~4 m per 100 m). Within increasing scarp height there is an increase in the frequency and spatial density of strong reflector packages in the hanging wall that are attributed to material contrasts imposed by co-seismic fracturing and associated lithological and weathering variations. No evidence for discrete faulting is found at scarp heights up to 40 m (maximum relief of 4 m per 100 m). Where the principal slip zone of a fault ruptures to the surface, scarp morphologies are characterized by steep gradients (ca. 10 m per 100 m). Discrete faulting is imaged in GPR as structural lineaments, abrupt changes in the thickness of reflector packages with variations of amplitude, and/or hyperbolic diffraction packages indicative of the disturbance of reflector packages. Geophysical imaging of subtle changes in the shallow geological structure during growth of fault-propagation folds can be conducted using GPR informing the identification of locations for invasive investigations (e.g., trenching). Full article

(This article belongs to the Topic Ground Penetrating Radar (GPR) Techniques and Applications)

►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

 

Error

Oops... you haven't selected anything for export.

Ok

clear

Displaying articles 1-15