Search Results (17)

For archaeological studies, the expected outcome of a Ground Penetrating Radar (GPR) survey is a series of time-slices (or depth-slices) that mark the position of buried structures at different depths. The clarity of these time-slices is strongly site-dependent and is particularly worsened in the presence of even small percentages of clay, which strongly attenuates the GPR signal. This is the condition affecting the Greek–Roman archaeological site of Tindari (Sicily, Italy). Here, we performed a multichannel GPR survey particularly focusing on a residential insula. In order to increase the signal-to-noise ratio, we tested two processing strategies: a conventional in-line stacking and a new concept of off-line stacking. This last was performed dividing spatially adjacent channels of the GPR multichannel system into groups and stacking the signals of each group at each specific location. We observed that off-line stacking improves the signal-to-noise ratio in 2D sections and time-slices quality. Comparisons showed that off-line stacking has a clear advantage over traditional in-line stacking, at least for the specific application reported in this paper. Off-line stacking of GPR multichannel systems is, therefore, simple but very effective in increasing the investigation depth, especially in challenging environments. Full article

Urban expansion in coastal areas involves infrastructure development, industrial growth, and mining activities. These coastal environments face various environmental and geological hazards that require geo-engineers to devise solutions. An integrated geophysical approach aims to address such complex challenges as sea level rise, sea water intrusion, shoreline erosion, landslides and previous anthropogenic activity in coastal settings. In this study, the proposed methodology involves the systematic application of geophysical methods (FDEM, 3D GPR, 3D ERT, seismic), starting with a broad-scale survey and then proceeding to a localized exploration, in order to identify lithostratigraphy, bedrock depth, sea water intrusion and detect anthropogenic buried features. The critical aspect is to leverage the unique strengths and limitations of each method within the coastal environment, so as to derive valuable insights for survey design (extension and orientation of measurements) and data interpretation. The coastal zone of Throrikos valley, Attica, Greece, serves as the test site of our geophysical investigation methodology. The planning of the geophysical survey included three phases: The application of frequency-domain electromagnetic (FDEM) and 3D ground penetrating radar (GPR) methods followed by a 3D electrical resistivity tomography (ERT) survey and finally, using the seismic refraction tomography (SRT) and multichannel analysis of surface waves (MASW). The FDEM method confirmed the geomorphological study findings by revealing the paleo-coastline, superficial layers of coarse material deposits and sea water preferential flow due to the presence of anthropogenic buried features. Subsequently, the 3D GPR survey was able to offer greater detail in detecting the remains of an old marble pier inland and top layer relief of coarse material deposits. The 3D ERT measurements, deployed in a U-shaped grid, successfully identified the anthropogenic feature, mapped sea water intrusion, and revealed possible impermeable formation connected to the bedrock. ERT results cannot clearly discriminate between limestone or deposits, as sea water intrusion lowers resistivity values in both formations. Finally, SRT, in combination with MASW, clearly resolves this dilemma identifying the lithostratigraphy and bedrock top relief. The findings provide critical input for engineering decisions related to foundation planning, construction feasibility, and preservation of coastal infrastructure. The methodology supports risk-informed design and sustainable development in areas with both natural and cultural heritage sensitivity. The applied approach aims to provide a complete information package to the modern engineer when faced with specific challenges in coastal settings. Full article

The automation of the detection infrastructure in GPR imagery is a key issue, particularly in the context of the non-invasive acquisition of radargrams with a multi-antenna ground-penetrating radar. Due to the fact that the dataset acquired with a multi-antenna GPR is very large, in the context of automating the process of detecting hyperbolas, the authors have proposed an adaptive approach to the selection of GPR images. The aim of this project was to develop a method for the selection of GPR images by means of applying the appropriate quality indicators. The authors propose a new, adaptive approach to the selection of radargrams that were recorded during the route of a GPR in a single profile, where several radargrams were recorded. Depending on the obtained initial values of the standard indicators for the assessment of the quality and quality maps of the radargrams, those images from selected channels that will ensure the highest possible quality and efficiency of hyperbola detection were selected. The stage of image quality assessment is essential in the context of improving the effectiveness of the automated detection of underground infrastructure. The quality assessment was performed based on the entropy indicator, PIQE, and Laplacian variance. The selected quality indicators allowed the authors to assess the degree of blurring, noise, and the number of details representing the underground structures that are present in GPR images. An additional product of the quality assessment were the generated maps that present the distribution of entropy in the analyzed images. The image selection was verified based on the results of the parameters that assess the effectiveness of the detection of hyperbolas that represent underground networks. The proposed innovative adaptive approach to the selection of images acquired by GPR enabled a significant improvement in the efficiency of the detection of hyperbolas representing underground utility networks, by 15–40%, shortening data processing and infrastructure detection times. Full article

In the process of using multi-channel ground-penetrating radar (GPR) for underground cavity exploration, the acquired 3D data include reflection data from underground cavities or various underground objects (structures). Reflection data from unspecified structures can interfere with the identification process of underground cavities. This study aims to identify underground cavities using a C-GAN model with an applied ResBlock technique. This deep learning model demonstrates excellent performance in the image domain and can automatically classify the presence of cavities by analyzing 3D GPR data, including reflection waveforms (A-scan), cross-sectional views (B-scan), and plan views (C-scan) measured from the ground under roads. To maximize the performance of the C-GAN model, a background filtering algorithm (BFA) was developed and applied to enhance the visibility and clarity of underground cavities. To verify the performance of the developed BFA, 3D data collected from roads in Seoul, Republic of Korea, using 3D GPR equipment were transformed, and the C-GAN model was applied. As a result, it was confirmed that the recall, an indicator of cavity prediction, improved by approximately 1.15 times compared to when the BFA was not applied. This signifies the verification of the effectiveness of the BFA. This study developed a special algorithm to distinguish underground cavities. This means that in the future, not only the advancement of separate equipment and systems but also the development of specific algorithms can contribute to the cavity exploration process. Full article

Ground-penetrating radar (GPR) is a non-invasive technology that uses electromagnetic pulses for subsurface exploration. In the railroad sector, it is crucial to assessing soil layers and infrastructure, offering insights into soil stratification and geological features and aiding in identifying subsurface hazards. However, the automation of radargram analysis is impeded by the lack of ground truth—accurate real-world data used to validate machine learning models—thus affecting the deployment of advanced algorithms. This study focuses on generating high-quality simulated data to address the shortage of real-world data in the context of object detection along railroad tracks and presents a fully automated pipeline that includes data generation, algorithm training, and validation using real-world data. By doing so, it paves the way for significantly easing the future task of object detection algorithms in the railway sector. A simulation environment, including the digital twin of a GPR antenna, was developed for artificial data generation. The process involves pre- and post-processing techniques to transform the three-dimensional data from the multichannel GPR system into two-dimensional datasets. This ensures minimal information loss and suitability for established two-dimensional object detection algorithms like the well-known YOLO (You Only Look Once) framework. Validation involved real-world measurements on a track with predefined buried objects. The entire pipeline, encompassing data generation, processing, training, and application, was automated for efficient algorithm testing and implementation. Artificial data show promise for better performance with increased training. Future AI and sensor advancements will enhance subsurface exploration, contributing to safer and more reliable railroad operations. Full article

Eliminating common-mode clutter in data is one of the key aspects of road sensing with GPR. Common-mode interference can occur as a result of multipath propagation of an electromagnetic signal when the reflected signal from the same object arrives at the receiver from different directions and with different delays. Similar phenomena also occur when using antennas raised above the surface due to multiple reflections between the air–surface interface and the antenna. These interferences can significantly distort the data received by the GPR and interfere with the accurate determination of the parameters of the roadway. Therefore, the elimination of common-mode clutter is an important task to improve the quality of the obtained results. In this paper, we consider a method for filtering common-mode clutter in the radar data of the multichannel GPR “Terrazond”, which were obtained by sounding a test section of a highway. The results obtained during filtering can then be used to determine the thickness of the pavement layers using approaches that take into account the signal delay determined by the amplitude jump, for example, the common point method or if the permittivity of each layer is known. The obtained thicknesses of pavement layers are compared with the results obtained during core drilling by the Russian Road Research Institute. Full article

As an effective active remote sensing technology for the exploration of shallow underground targets, ground-penetrating radar (GPR) is a detection method that can be used to obtain information about the characteristics of underground targets by transmitting an electromagnetic wave from an antenna and analyzing the propagation of the electromagnetic wave underground. Due to the frequency (1 MHz–3 GHz) of GPRs, the depth of geological exploration is shallow (0.1–30 m). In order to penetrate the deeper Earth, it is necessary to increase the size of the antenna in accordance with the wavelength ratio and, thus, reduce the radiation frequency. For most bi-static antenna GPRs, a dipole antenna is used as the transmitting antenna and another antenna device is used as a receiving antenna, with both being horizontally linearly polarized (LP) antennas. In some cases, such a design can cause problems, such as the multi-path effect and polarization mismatching. When a GPR is used for deep exploration, increased numbers of errors and greater signal attenuation during data reception and processing often occur. In contrast, at the radiation source, with the use of large-aperture multiple-dipole antennas and multi-channel sequential rotational excitation, the electromagnetic wave can radiate in the form of circular polarization at a low frequency. In the receiving antenna, the issues caused by the multi-path effect and polarization mismatching can be addressed, even if LP antennas are used. A novel sequential rotationally excited (SRE) circularly polarized (CP) multiple-dipole array for a bi-static antenna GPR for deep exploration is proposed in this paper. A large-aperture CP multiple-dipole array is used instead of a small-size LP dipole antenna. The analysis and simulation results demonstrated that, comparing circular polarization and linear polarization with the premise of the same transmitting power, the SRE CP multiple-dipole antenna array radiation source achieved a significant enhancement (about 7 dB) in the signal-to-noise ratio (SNR) as the radiant energy was collected at the receiving antenna. More importantly, by reducing the exploration frequency to 10 KHz, the exploration depth could also be greatly increased by about tenfold. Full article

Artificial Neural Network (ANN) approaches are applied to detect and determine the object class using a special set of the UltraWideBand (UWB) pulse Ground Penetrating Radar (GPR) sounding results. It used the results of GPR sounding with the antenna system, consisting of one radiator and four receiving antennas located around the transmitting antenna. The presence of four receiving antennas and, accordingly, the signals received from four spatially separated positions of the antennas provide a collection of signals received after reflection from an object at different angles and, due to this, to determine the location of the object in a coordinate system, connected to the antenna. We considered the sums and differences of signals received by two of the four antennas in six possible combinations: (1 and 2, 1 and 3, 2 and 3, 1 and 4, etc.). These combinations were then stacked sequentially one by one into one long signal. Synthetic signals constructed in such a way contain many more notable differences and specific information about the class to which the object belongs as well as the location of the searched object compared to the signals obtained by an antenna system with just one radiating and one receiving antenna. It therefore increases the accuracy in determining the object’s coordinates and its classification. The pulse radiation, propagation, and scattering are numerically simulated by the finite difference time domain (FDTD) method. Results from the experiment on mine detection are used to examine ANN too. The set of signals from different objects having different distances from the GPR was used as a training and testing dataset for ANN. The training aims to recognize and classify the detected object as a landmine or other object and to determine its location. The influence of Gaussian noise added to the signals on noise immunity of ANN was investigated. The recognition results obtained by using an ANN ensemble are presented. The ensemble consists of fully connected and recurrent neural networks, gated recurrent units, and a long-short term memory network. The results of the recognition by all ANNs are processed by a meta network to provide a better quality of underground object classification. Full article

The shift to the early Holocene in northern Europe is strongly associated with major environmental and climatic changes that influenced hunter-gatherers’ activities and occupation during the Mesolithic period. The ancient lake Duvensee (10,000–6500 cal. BCE) has been studied for almost a century, providing archaeological sites consisting of bark mats and hazelnut-roasting hearths situated on small sand banks deposited by the glacier. No method is yet available to locate these features before excavation. Therefore, a key method for understanding the living conditions of hunter-gatherer groups is to reconstruct the paleoenvironment with a focus on the identification of areas that could possibly host Mesolithic camps and well-preserved archaeological artefacts. We performed a 16-channel MALÅ Imaging Radar Array (MIRA) system survey aimed at understanding the landscape surrounding the find spot Duvensee WP10, located in a hitherto uninvestigated part of the bog. Using an integrated approach of high-resolution ground radar mapping and targeted excavations enabled us to derive a 3D spatio-temporal landscape reconstruction of the investigated sector, including paleo-bathymetry, stratigraphy, and shorelines around the Mesolithic camps. Additionally, we detected previously unknown islands as potential areas for yet unknown dwelling sites. We found that the growth rates of the islands were in the order of approximately 0.3 m²/yr to 0.7 m²/yr between the late Preboreal and the Subboreal stages. The ground-penetrating radar surveying performed excellently in all aspects of near-surface landscape reconstruction as well as in identifying potential dwellings; however, the direct identification of small-scale artefacts, such as fireplaces, was not successful because of their similarity to natural structures. Full article

Injecting grout into the gaps between tunnel shield segments and surrounding rocks can reduce ground subsidence and prevent ground water penetration. However, insufficient grouting and grouting defects may cause serious geological disasters. Ground penetrating radar (GPR) is widely used as a nondestructive testing (NDT) method to evaluate grouting quality and determine the existence of defects. This paper provides an overview of GPR applications for grouting defect detection behind tunnel shield segments. State-of-the-art methodologies, field cases, experimental tests and signal processing methods are discussed. The reported field cases and model test results show that GPR can detect grouting defects behind shield tunnel segments by identifying reflected waves. However, some subsequent problems still exist, including the interference of steel bars and small differences in the dielectric constants among media. Recent studies have focused on enhancing the signal-to-noise ratio and imaging methods. Advanced GPR signal processing methods, including full waveform inversion and machine learning methods, are promising for detecting imaging defects. Additionally, we conduct a preliminary experiment to investigate environmental noise, antenna configuration and coupling condition influences. Some promising topics, including multichannel configuration, rapid evaluation methods, elastic wave method scanning equipment for evaluating grout quality and comprehensive NDT methods, are recommended for future studies. Full article

This study explores the efficacy of utilizing a novel ground penetrating radar (GPR) acquisition platform and data analysis methods to quantify peanut yield for breeding selection, agronomic research, and producer management and harvest applications. Sixty plots comprising different peanut market types were scanned with a multichannel, air-launched GPR antenna. Image thresholding analysis was performed on 3D GPR data from four of the channels to extract features that were correlated to peanut yield with the objective of developing a noninvasive high-throughput peanut phenotyping and yield-monitoring methodology. Plot-level GPR data were summarized using mean, standard deviation, sum, and the number of nonzero values (counts) below or above different percentile threshold values. Best results were obtained for data below the percentile threshold for mean, standard deviation and sum. Data both below and above the percentile threshold generated good correlations for count. Correlating individual GPR features to yield generated correlations of up to 39% explained variability, while combining GPR features in multiple linear regression models generated up to 51% explained variability. The correlations increased when regression models were developed separately for each peanut type. This research demonstrates that a systematic search of thresholding range, analysis window size, and data summary statistics is necessary for successful application of this type of analysis. The results also establish that thresholding analysis of GPR data is an appropriate methodology for noninvasive assessment of peanut yield, which could be further developed for high-throughput phenotyping and yield-monitoring, adding a new sensor and new capabilities to the growing set of digital agriculture technologies. Full article

In this study, the applications and the limitations of the Ground-penetrating radar (GPR) investigation have been addressed with the main objective of improving the efficient GPR application of subsurface surveys on Korean expressways. The depth of investigation and detection performance of anomalous objects have been studied using two different types of multichannel GPR on the Korean Expressway Corporation’s nondestructive testing testbed for subsurface detection. Based on the field survey, it was found that utilizing the plane view by depth, cross-sectional and longitudinal profile data of the multichannel GPR simultaneously, analysis and evaluation of the GPR signals are more efficient and practical. Although there was a difference in the frequency of use, the precision difference between two GPR is almost similar in the investigation depth and detection performance of the pavement subsurface anomaly. Under an asphalt concrete standard pavement section, the effective depth of cavity detection is 1–1.5 m, while detection under concrete pavement is less than 1.0 m. In addition, there is still a need to calibrate depths using field cores when constructing a 3D underground facility map. Full article

This paper conceptualizes and evaluates the groundwater resource in a coastal urban area hydrologically influenced by peri-urban irrigation agriculture. Adra town in southern Spain was the case study chosen to evaluate the groundwater resource contributed from the northern steep urban sector (NSUS) to the southern flat urban sector (SFUS), which belongs to the Adra River Delta Groundwater Body (ARDGB). The methodology included (1) geological and hydrogeological data compilation; (2) thirteen Multichannel Analysis of Surface Waves (MASW), and eight Ground Penetrating Radar (GPR) profiles to define shallow geological structures and some hydrogeological features; (3) hydrogeological surveys for aquifer hydraulic definition; (4) conceptualization of the hydrogeological functioning; and (5) the NSUS groundwater resource evaluation. All findings were integrated to prepare a 1:5000 scale hydrogeological map and cross-sections. Ten hydrogeological formations were defined, four of them (Paleozoic weathered bedrock, Pleistocene littoral facies, Holocene colluvial, and anthropogenic filling) in the NSUS contributing to the SFUS. The NSUS groundwater discharge and recharge are, respectively, around 0.28 Mm³ year⁻¹ and 0.31 Mm³ year⁻¹, and the actual groundwater storage is around 0.47 Mm³. The groundwater renewability is high enough to guarantee a durable small exploitation for specific current and future urban water uses which can alleviate the pressure on the ARDGB. Full article

Due to the capabilities of non-destructive testing of inaccessible objects, GPR (Ground Penetrating Radar) is used in geology, archeology, forensics and increasingly also in engineering tasks. The wide range of applications of the GPR method has been provided by the use of advanced technological solutions by equipment manufacturers, including multi-channel units. The acquisition of data along several profiles simultaneously allows time to be saved and quasi-continuous information to be collected about the subsurface situation. One of the most important aspects of data acquisition systems, including GPR, is the appropriate methodology and accuracy of the geoposition. This publication aims to discuss the results of GPR measurements carried out using the multi-channel Leica Stream C GPR (IDS GeoRadar Srl, Pisa, Italy). The significant results of the test measurement were presented the idea of which was to determine the achievable accuracy depending on the georeferencing method using a GNSS (Global Navigation Satellite System) receiver, also supported by time synchronization PPS (Pulse Per Second) and a total station. Methodology optimization was also an important aspect of the discussed issue, i.e., the effect of dynamic changes in motion trajectory on the positioning accuracy of echograms and their vectorization products was also examined. The standard algorithms developed for the dedicated software were used for post-processing of the coordinates and filtration of echograms, while the vectorization was done manually. The obtained results provided the basis for the confrontation of the material collected in urban conditions with the available cartographic data in terms of the possibility of verifying the actual location of underground utilities. The urban character of the area limited the possibility of the movement of Leica Stream C due to the large size of the instrument, however, it created the opportunity for additional analyses, including the accuracy of different location variants around high-rise buildings or the agreement of the amplitude distribution at the intersection of perpendicular profiles. Full article

A site located on the island of Brač is known in history for world-famous architectural stone and stone mining, dating all the way back to ancient Greek and Roman times. The most famous building constructed from the stone from Brač is the Diocletian Cesar Palace in the town Split. Prospective new locations for quarries are still required because the demand for the stone from the island is still high. This paper presents a review of undertaken geophysical investigations, as well as engineering geologic site prospection, with the purpose of determining if the rock mass quality is suitable for the mining of massive blocks needed for an architectural purpose—dimension stones. Several surface noninvasive geophysical methods were applied on the site, comprising of two seismic methods, multichannel analysis of surface waves (MASW) and shallow refraction seismic (SRS) electrical methods of electrical resistivity tomography (ERT), as well as electromagnetic exploration with ground penetrating radar (GPR). Results of geophysical investigations were compared to the engineering geologic prospection results, as well to the visible rock mass structure and observed discontinuities on the neighboring existing open mine quarry. Rock mass was classified into three categories according to its suitability for dimension stone exploitation. Each category is defined by compressional and shear seismic velocities as well as electrical resistivity. It has been found that even small changes in moisture content within the large monolithic rock mass can influence measured values of electrical resistivity. In the investigated area, dimension stone quarrying is advisable if the rock mass has values of resistivity higher than 3000 Ωm, as well as compressional seismic velocities higher than 3000 m/s and shear wave velocities higher than 1500 m/s. Georadar was found to be a good tool for the visual determination of fissured systems, and was used to confirm findings from other geophysical methods. Full article