Topic Editors

Archaeology and Classics Program, American University of Rome, Via Pietro Roselli 4, 00153 Rome, Italy
School of the Natural Built Environment, Queen’s University, University Road, Belfast BT7 1NN, Northern Ireland, UK
CREA-FL, Council for Agricultural Research and Economics, Research Centre for Forestry and Wood, Via Valle Della Quistione 27, 00166 Rome, Italy

Ground Penetrating Radar (GPR) Techniques and Applications

Abstract submission deadline
31 July 2024
Manuscript submission deadline
31 October 2024
Viewed by
17873

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

  • GPR theory
  • GPR in architecture and engineering
  • GPR in geoscience
  • GPR in archaeology and cultural heritage
  • GPR in agriculture and forest science
  • GPR in forensic science
  • applications of GPR in water management
  • GPR data processing and analysis
  • combined use of GPR and other remote sensing techniques

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Electronics
electronics
2.9 4.7 2012 15.6 Days CHF 2400 Submit
Eng
eng
- - 2020 18.7 Days CHF 1200 Submit
Forensic Sciences
forensicsci
- - 2021 15.9 Days CHF 1000 Submit
Forests
forests
2.9 4.5 2010 16.9 Days CHF 2600 Submit
Geosciences
geosciences
2.7 5.2 2011 23.6 Days CHF 1800 Submit
Heritage
heritage
1.7 2.8 2018 16.9 Days CHF 1600 Submit
Infrastructures
infrastructures
2.6 4.3 2016 16.9 Days CHF 1800 Submit
Remote Sensing
remotesensing
5.0 7.9 2009 23 Days CHF 2700 Submit

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Published Papers (9 papers)

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11 pages, 8194 KiB  
Case 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 - 04 Dec 2023
Viewed by 1199
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
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24 pages, 9328 KiB  
Article
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 1 | Viewed by 2669
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
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18 pages, 16356 KiB  
Technical 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
Viewed by 1069
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
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20 pages, 4818 KiB  
Article
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 - 06 Jul 2023
Viewed by 1011
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
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20 pages, 11535 KiB  
Article
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
Viewed by 1190
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
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19 pages, 3786 KiB  
Communication
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 1 | Viewed by 1870
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
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22 pages, 5272 KiB  
Article
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 2 | Viewed by 1289
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
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9 pages, 3316 KiB  
Article
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 1 | Viewed by 1550
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
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30 pages, 10476 KiB  
Article
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 1 | Viewed by 2262
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
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