Ground Penetrating Radar (GPR) Techniques and Applications

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

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

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

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

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

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

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

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

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

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

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

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