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This study explores the impact of corrosion on Ground Penetrating Radar (GPR) responses through practical experiments and numerical modelling, focusing on rebar diameter reduction, corrosion product layer thickness, crack formation and corrosion product filling in vertical and transverse crack. Practical experiments involved GPR testing of reinforced concrete slab. By analyzing B-scans we identify areas with moderate and severe corrosion. Numerical modelling using the Finite Difference Time Domain (FDTD) Method to model GPR signal propagation in a concrete bridge deck with corrosion is applied. Key finding includes a significant 26.70% increase in reflected wave amplitude when corrosion product filling in vertical crack increased by 400%, highlighting its extensive effect on signal GPR propagation. Reduced rebar diameter led to a 9.79% amplitude decrease and a 0.06 ns arrival time delay. Increased corrosion product layer thickness primarily affected arrival time with a 0.06 ns extension but significantly amplified GPR signal amplitude. These findings offer insights for improving GPR based corrosion detection and assessment methods, leading to more robust systems for concrete bridge deck inspection and maintenance. This paper contributes to understanding how corrosion affects the signal that is detected by GPR. This information can be used to improve the way that we manage and assess corrosion in concrete bridge deck. [ABSTRACT FROM AUTHOR]

Hyperbolae in radargrams are caused by a variety of small subsurface objects. The analysis of their curvature enables the determination of propagation velocity in the subsurface, which is important for exact time-to-depth conversion and migration and also yields information on the water content of the soil. Using deep learning methods and fitting (DLF) algorithms, it is possible to automatically detect and analyze large numbers of hyperbola in 3D Ground-Penetrating Radar (GPR) datasets. As a result, a 3D velocity model can be established. Combining the hyperbola locations and the 3D velocity model with reflection depth sections and timeslices leads to improved archaeological interpretation due to (1) correct time-to-depth conversion through migration with the 3D velocity model, (2) creation of depthslices following the topography, (3) evaluation of the spatial distribution of hyperbolae, and (4) derivation of a 3D water content model of the site. In an exemplary study, we applied DLF to a 3D GPR dataset from the multi-phased (2nd to 12th century CE) archaeological site of Goting on the island of Föhr, Northern Germany. Using RetinaNet, we detected 38,490 hyperbolae in an area of 1.76 ha and created a 3D velocity model. The velocities ranged from approximately 0.12 m/ns at the surface to 0.07 m/ns at approx. 3 m depth in the vertical direction; in the lateral direction, the maximum velocity variation was ±0.048 m/ns. The 2D-migrated radargrams and subsequently created depthslices revealed the remains of a longhouse, which was not known beforehand and had not been visible in the unmigrated timeslices. We found hyperbola apex points aligned along linear strong reflections. They can be interpreted as stones contained in ditch fills. The hyperbola points help to differentiate between ditches and processing artifacts that have a similar appearance as the ditches in time-/depthslices. From the derived 3D water content model, we could identify the thickness of the archaeologically relevant layer across the whole site. The layer contains a lot of humus and has a high water retention capability, leading to a higher water content compared to the underlying glacial moraine sand, which is well-drained. [ABSTRACT FROM AUTHOR]

This paper investigates the use of ground-penetrating radar (GPR) technology for detecting shallow buried objects, utilizing an air-coupled stepped frequency continuous wave (SFCW) radar system that operates within a 2 GHz bandwidth starting at 500 MHz. Different GPR data acquisition methods for air-coupled systems are compared, specifically down-looking, side-looking, and circular acquisition strategies, employing the back projection algorithm to provide focusing of the acquired GPR data. Experimental results showed that the GPR can penetrate up to 0.6 m below the surface in a down-looking mode. The developed radar and the back projection focusing algorithm were used to acquire data in the side-looking and circular mode, providing focused images with a resolution of 0.1 m and detecting subsurface objects up to 0.3 m below the surface. The proposed approach transforms B-scans of the GPR-based data into 2D images. The provided approach has significant potential for advancing shallow object detection capabilities by transforming hyperbola-based features into point-like features. [ABSTRACT FROM AUTHOR]

Coal–rock interface recognition is one of the key challenges in advancing unmanned rapid tunneling systems. To address this, a method based on variations in ground-penetrating radar (GPR) reflection wave amplitude is proposed for identifying coal-rock interfaces in soft coal seams. A mathematical model derived from Maxwell's equations calculates the coal seam area based on the reflected wave amplitude. Experiments using a 400 MHz radar antenna show that the method achieves identification errors of 3.58 cm, 3.74 cm, and 4.23 cm for coal-to-rock ratios of 1:2, 1:1, and 2:1, respectively. In practical applications within a coal mine excavation face, the identification error is 6.64 cm. This method provides crucial data for drum height adjustment and cutting arm speed regulation in unmanned tunneling systems. [ABSTRACT FROM AUTHOR]

Time-lapse ground-penetrating radar (GPR) surveys, combined with automated infiltration experiments, provide a non-invasive approach for investigating the distribution of infiltrated water within the soil medium and creating three-dimensional images of the wetting bulb. This study developed and validated an experimental protocol aimed at quantifying and visualizing water distribution fluxes in layered soils under both unsaturated and saturated conditions. The 3D images of the wetting bulb significantly enhanced the interpretation of infiltration data, enabling a detailed analysis of water movement through the layered system. We used the infiltrometer data and the Beerkan Estimation of Soil Transfer parameters (BEST) method to determine soil capacitive indicators and evaluate the physical quality of the upper soil layer. The field survey involved conducting time-lapse GPR surveys alongside infiltration experiments between GPR repetitions. These experiments included both tension and ponding tests, designed to sequentially activate the soil matrix and the full pore network. The results showed that the soil under study exhibited significant soil aeration and macroporosity (represented by AC and pMAC), while indicators related to microporosity (such as PAWC and RFC) were notably low. The RFC value of 0.55 m3 m−3 indicated the soil's limited capacity to retain water relative to its total pore volume. The PAWC value of 0.10 m3 m−3 indicated a scarcity of micropores ranging from 0.2 to 30 μm in diameter, which typically hold water accessible to plant roots within the total porosity. The saturated soil hydraulic conductivity, Ks, values ranged from 192.2 to 1031.0 mm h−1, with a mean of 424.4 mm h−1, which was 7.9 times higher than the corresponding unsaturated hydraulic conductivity measured at a pressure head of h = −30 mm (K−30). The results indicated that the upper soil layer supports root proliferation and effectively drains excess water to the underlying limestone layer. However, this layer has limited capacity to store and supply water to plant roots and acts as a restrictive barrier, promoting non-uniform downward water movement, as revealed by the 3D GPR images. The observed difference in hydraulic conductivity between the two layers suggests that surface ponding and overland flow are generated through a saturation excess mechanism. Water percolating through the soil can accumulate above the limestone layer, creating a shallow perched water table. During extreme rainfall events, this water table may rise, leading to the complete saturation of the soil profile. [ABSTRACT FROM AUTHOR]

The main purpose of this study is the subsurface investigation of two complex geological environments focusing on the improvement of data acquisition and processing parameters regarding electric and seismic tomographic techniques. Two different study areas, in central–east Peloponnese and SE Attica, were selected, where detailed geological mapping and surface geophysical survey were carried out. The applied geophysical survey included the application of electrical resistivity tomography (ERT), seismic refraction tomography (SRT) and ground penetrating radar (GPR). The geoelectrical measurements were acquired with different arrays and electrode configurations. Moreover, various types of seismic sources were used at seventeen shot locations along the seismic arrays. For the processing of geoelectrical data, clustered datasets were created, increasing the depth of investigation and discriminatory capability. The seismic data processing included the following: (a) the creation of synthetic models and seismic records to determine the effectiveness and capabilities of the technique, (b) spectral analysis of the seismic records to determine the optimal seismic source type and (c) inversion of the field data to create representative subsurface velocity models. The results of the two techniques successfully delineated the complex subsurface structure that characterizes these two geological environments. The application of the ERT combined with the SRT are the two dominant, high-resolution techniques for the elucidation of complex subsurface structures. [ABSTRACT FROM AUTHOR]

The site of Amasya-Oluz Höyük was discovered during a surface survey conducted in 1999, with archaeological excavations commencing in 2007. The site has revealed cultural layers and cities belonging to significant civilizations. Through archaeological excavations at Oluz Höyük, significant findings that could reshape the religious history of Anatolia have been uncovered. In the settlement dating back to the 5th century BC, important architectural complexes related to the Fire Cult (associated with early Zoroastrianism) of the Persian Settlement have been discovered. As civil and religious structures of the Persian Settlement continue to be unearthed at the höyük, these 2,500-year-old findings are expected to add new dimensions to the religious history of the period. The richness of the archaeological artifacts uncovered so far at Oluz Höyük is evidence that the mound is a significant archaeological heritage site in Anatolia. According to the "Charter for the Protection and Management of the Archaeological Heritage" prepared by ICOMOS and adopted in Lausanne in 1990, "the protection of the archaeological heritage must be based on the fullest and most detailed knowledge possible of its nature and characteristics" (Article 4). In this context, Ground Penetrating Radar (GPR) surveys were conducted in the southern section of Trench A, located at the top of the mound, near the western edge of the religious structure remains and in the area thought to be either a civil structure or part of a temple. Two- and three-dimensional subsurface images were obtained from these surveys. The GPR studies revealed high-amplitude anomalies that displayed linear, circular, right-angled, and geometrically structured forms. Archaeological excavations were conducted in this area, uncovering the foundations of a grain storage facility that had been affected by fire. [ABSTRACT FROM AUTHOR]

The Greek marble statue of the Auriga of Mozia Island, in Sicily, is the most important artwork displayed at the Whitaker Foundation Archaeological Museum. It underwent geophysical investigations twice, in 2012 and 2021, to assess the marble's degradation. The 2012 investigation prepared the statue for transfer to the Paul Getty Museum in New York and repositioning on an anti-seismic pedestal. The 2021 investigation evaluated potential new damage before another transfer. Both investigations utilized 3D ultrasonic tomography (UST) to detect degraded marble areas and ground-penetrating radar (GPR) to identify internal discontinuities, such as fractures or lesions, and locate metal pins that were previously inserted to reassemble the statue and its pedestal. Results from the UST indicate an average marble velocity of approximately 4700 m/s, suggesting good mechanical strength, with some areas showing lower velocities (~3000 m/s) within the material's variability range. The GPR profiles demonstrated internal signal homogeneity, excluding internal fracture surfaces or lesions, and confirmed the presence of metallic pins. This study highlights the effectiveness of integrating UST and GPR for non-invasive diagnostics of marble sculptures, providing detailed insights into the marble's condition and identifying hidden defects or damage. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Continuous measurements of soil moisture in the deeper parts of the unsaturated zone remain an important challenge. This study examines the development of an integrated system for the continuous and 3-D monitoring of the vadose zone processes in a cost- and energy-efficient way. This system comprises TDR, ERT and GPR geophysical techniques. Their capacities to adequately image subsurface moisture changes with continuous and time-lapse measurements are assessed during an artificial infiltration experiment conducted in a characteristic urban site with anthropogenic fills and much compaction. A 3-D array was designed for each method to expand the information of a single TDR probe and obtain a broader image of the subsurface. Custom spatial TDR probes installed in boreholes made with a percussion drilling instrument were used for soil moisture measurements. Moisture profiles along the probes were estimated with a numerical one-dimensional inversion model and a standard calibration equation. High conductivity water used during all infiltration tests led to the detection of the flow by all techniques. Preferential flow was present throughout the experiment and imaged sufficiently by all methods. Overall, the integrated approach conceals each method's weaknesses and provides a reliable 3-D view of the subsurface. The results suggest that this approach can be used to monitor the unsaturated zone at even greater depths. [ABSTRACT FROM AUTHOR]

The demand for nondestructive testing techniques (NDTs) that can be implemented continuously and cost-effectively for large-scale study purposes is increasing. Ground penetrating radar (GPR) as an NDT method permits the estimation of pavement materials characteristics without disrupting the serviceability of the system. This research used typical pavement materials for constructing load-bearing layers (base and subbase) for the GPR laboratory tests. A 2 GHz GPR antenna was applied to execute the tests by changing three essential variables of the material: water content, compaction and clay content. Machine learning and interactive methods were innovatively utilised to model the collected data. As a result, a multivariate non-linear empirical function is proposed by the interactive procedure. Furthermore, the machine learning modelling (SVM method) with R2 of 0.91 indicates promising results to evaluate the pavement layers' properties. Machine learning can enhance the speed and accuracy of analysis when faced with multi-variables and extensive data. [ABSTRACT FROM AUTHOR]

Coarse roots and the root plate play an important role in tree resistance to uprooting. In this study, a qualitative mechanistic model was developed to analyze coniferous tree resistance to uprooting in relation to tree morphological characteristics. The sizes of the crown, stem, and root plate of twenty sample spruces and twenty sample Korean pines were individually measured for this purpose. Using Ground Penetrating Radar (GPR), the coarse root distribution and root plate size were detected. In the qualitative mechanistic model, a larger crown area increased the overturning moment, while higher DBH and root plate mass increased the resistance moment. The resistance coefficient (Rm) was calculated by comparing resistive and overturning moments, classifying samples into three uprooting hazard levels. Trees with smaller crown areas, larger stems, and root plates tend to have higher resistance to uprooting, as indicated by higher Rm values. This qualitative mechanistic model provides a useful tool for assessing coniferous standing tree uprooting resistance. [ABSTRACT FROM AUTHOR]

When it comes to hydropower dam safety, continuous and comprehensive monitoring is increasingly important. Especially for aging dams, this can pose a difficult challenge that benefits from a multimethod analysis. Here, we present the use and suitability of a geophysical method, Ground Penetrating Radar (GPR), for the non-invasive assessment of two distinct types of hydropower dams in Romania: Herculane (a concrete arch dam) and Gura Apelor (an embankment dam with a rockfill and clay core). Unlike traditional monitoring methods for dam safety in Romania, which might provide an incomplete overview, GPR offers a broader, non-destructive approach to evaluating some elements of dam integrity. Here, we present the results of surveys carried out with a 200 MHz antenna on the crests of both dams. The aim was to conduct a rapid assessment of the crest condition and identify the potential damage to the crest that may elude standard monitoring techniques. The surveys provide an imaging indicative of the structural integrity, although this is more challenging in the embankment dam, and additionally we provide significant information regarding the deformations in the upper layers. This complements data from routine topo-geodetical surveys, offering a potential explanation for the vertical displacements observed therein. We highlight several areas of potential deformation as well as degradation in subsurface structures such as rebars. The results underscore the value of GPR in supplementing established dam monitoring methods, highlighting its effectiveness in different contexts and dam types, as well as its potential in shaping future standards for dam safety management in Romania. [ABSTRACT FROM AUTHOR]

Ground penetrating radar (GPR) is a vital non-destructive testing (NDT) technology that can be employed for detecting the backfill grouting of shield tunnels. To achieve intelligent analysis of GPR data and overcome the subjectivity of traditional data processing methods, the CatBoost & BO-TPE model was constructed for regressing the grouting thickness based on GPR waveforms. A full-scale model test and corresponding numerical simulations were carried out to collect GPR data at 400 and 900 MHz, with known backfill grouting thickness. The model test helps address the limitation of not knowing the grout body condition in actual field detection. The data were then used to create machine learning datasets. The method of feature selection was proposed based on the analysis of feature importance and the electromagnetic (EM) propagation law in mediums. The research shows that: (1) the CatBoost & BO-TPE model exhibited outstanding performance in both experimental and numerical data, achieving R2 values of 0.9760, 0.8971, 0.8808, and 0.5437 for numerical data and test data at 400 and 900 MHz. It outperformed extreme gradient boosting (XGBoost) and random forest (RF) in terms of performance in the backfill grouting thickness regression; (2) compared with the full-waveform GPR data, the feature selection method proposed in this paper can promote the performance of the model. The selected features within the 5-30 ns of the A-scan can yield the best performance for the model; (3) compared to GPR data at 900 MHz, GPR data at 400 MHz exhibited better performance in the CatBoost & BO-TPE model. This indicates that the results of the machine learning model can provide feedback for the selection of GPR parameters; (4) the application results of the trained CatBoost & BO-TPE model in engineering are in line with the patterns observed through traditional processing methods, yet they demonstrate a more quantitative and objective nature compared to the traditional method. [ABSTRACT FROM AUTHOR]

The analysis of ground-penetrating radar (GPR) data is of vital importance for detecting various subsurface features that might manifest as hyperbolic peaks, which are indicators of a buried object or grayscale variation in the case of contrast in the soil texture. This method focuses on identifying exaggerated patterns through a series of image-processing steps. Two GPR images are initially read and preprocessed by extracting channels, flipping, and resizing. Then, specific regions of interest (ROIs) are cropped, and the Fourier transform is further applied to turn them into the frequency domain. With the help of their frequency signatures, these patterns are extracted from the images, and binary masks are constructed to obtain features of interest. These masked images were reconstructed and merged to make hyperbolic features visible. Finally, Local Binary Pattern (LBP) analysis is used to emphasize these hyperbolic peaks, thereby facilitating their recognition across the whole image. The proposed approach improves the detection of performance subsurface features in GPR data; hence, it is an important tool for geophysical surveys and other related applications. The results prove the high performance of the proposed procedure in improving GPR image characteristics. [ABSTRACT FROM AUTHOR]

Estimates of radar attenuation in the shallow Martian subsurface are retrieved from RIMFAX soundings along the Perseverance rover traverse. Specifically, analyzed data is from the Hawksbill Gap area during the rover's first drives onto the Jezero Western Fan Front. The centroid frequency‐shift method is employed to quantify attenuation in terms of the constant‐Q approximation. Results are then compared with the amplitude decay method, which—in order to calculate attenuation—requires propagation velocities retrieved from radargram analysis. By verifying that results from two separate analyses are consistent, we ensure that quantified radar properties are well constrained. First estimate of constant‐Q is 78.8 ± 11.6. For a subsurface propagation velocity of 0.113 m/ns, that equals an attenuation of −2.1 ± 0.4 dB/m at the RIMFAX 675 MHz center frequency. Results are consistent with dry sedimentary rocks, and are distinguishable from the magmatic lithologies on Jezero Crater Floor. Plain Language Summary: This study presents first estimates of radar attenuation at the Jezero Western Fan Front. Measurements were made with the RIMFAX payload instrument on the Mars 2020 Perseverance rover mission, acquired along the rover drive path. Results indicate low signal losses in the subsurface that are consistent with dry sedimentary rocks, as observed on the surface by other payload instruments. Maximum imaging depths increase compared to imaging over magmatic lithologies on Jezero Crater Floor. By using separate methods of analysis (the centroid frequency‐shift method and the amplitude decay method), we reliably quantify attenuation and maximum penetration depths at the Western Fan Front, and observe differences to the Crater Floor lithologies. Key Points: The first estimate of radar attenuation at the Jezero Western Fan Front is on average −2.1 dB/mFor an average propagation velocity of 0.113 m/ns, returned power and time‐frequency analyses yield similar resultsRadar properties are consistent with dry sedimentary rocks and are distinguishable from the magmatic lithologies on Jezero Crater Floor [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) is often used to detect targets in a construction environment. Due to the different construction environments, the noise exhibits different characteristics on the GPR signal. When the noise is widely distributed on the GPR signal, and its spectrum and the spectrum of the active signal are aliased, it is difficult to separate and suppress the noise by traditional filtering methods. In this paper, we propose a deep learning GPR image noise suppression method based on a recursive guided and dual multi-scale self-attention mechanism neural network (RG-DMSA-NN), which uses a recursive guidance module and a dual multi-scale self-attention mechanism module to improve the feature extraction ability of the image and enhance the robustness and generalization ability in image noise suppression. Through the application of noise suppression on the synthesized test data and the GPR data actually collected by the Macao Science and Technology Museum, the advantages of this method over the traditional filtering, DnCNN and UNet noise suppression methods are demonstrated. [ABSTRACT FROM AUTHOR]

Data synergy involves acquiring and combining data from different sensors to achieve better problem analysis and research results. For more comprehensive data analysis, the sensors are not only mounted on one platform. Still, they should also be compatible with software and hardware, e.g. for the same timestamp registration by different sensors. The aim of this article is to propose the synergy between various remote sensing sensors including the ground penetrating radar (GPR), LiDAR (Light Detection and Ranging) sensor and three photogrammetric RGB cameras for damage detection in a pavement in a park alley. The data were acquired with a low-cost platform, in the Pole Mokotowskie Park in Warsaw, Poland. Three drives were made along the same path with the platform, so it was possible to assess the repeatability of the data. Based on the GPR data, orthophotomap, and digital terrain model (DTM) from images, an analysis of the cracks in the pavement was done. The paper proves additive value from the synergy of data collected for the alley also in the form of a common visualization of acquired data. Results presented in the article showed that using mobile mapping platform and technologies describing the situation above and below the ground level enable a more detailed analysis and inspection of the damages in the park alley. [ABSTRACT FROM AUTHOR]

A survey was conducted to investigate buried archaeological remains at Tingambato, a pre‐Tarascan classic‐epiclassic archaeological site located in the north‐central part of the State of Michoacán in western Mexico, using ground‐penetrating radar (GPR) and electrical resistivity tomography (ERT). The aim of this study was to detect the foundations (ancient buried walls) and cavities (tombs), define the geometry of the foundations and correlate construction style and depth with relative chronological buried structures. The survey was carried out on two grids of 15 m × 37 m (Zona Verde) and 10.25 m × 36.5 m (Ballgame court), using a 200 MHz antenna for GPR and Schlumberger‐Wenner arrays for ERT. GPR 3D acquisition was carried out along parallel lines spaced 0.25 m apart in a single direction. In the first area, considering the geometric shape found at a depth of 1.35 m, we can assume the existence of a buried structure, probably wall remains. In the second area, a very diffractive zone coincides with a resistive anomaly (> 2000 ohm·m). In order to refine the GPR results, synthetic modelling and a comparison with real traces were carried out. The 1D GPR modelling allows us to precise the presence of a cavity with a rectangular cross section. Since the type of volcaniclastic avalanche deposits of the subsoil do not allow the formation of cavities of that size, we infer that it may be the remains of a tomb or an anthropogenic cavity. [ABSTRACT FROM AUTHOR]

This study aims to develop a damage-detection algorithm based on the electromagnetic wave properties inside a reinforced concrete structure. The proposed method involves employing two algorithms based on data measured using ground-penetrating radar—a common electromagnetic wave method in civil engineering. The possible defect area was identified based on the energy dissipated by the damage in the frequency-wavenumber domain, with the damage localized using the calculated relative permittivity of the measurements. The proposed method was verified through a finite difference time-domain-based numerical analysis and a testing slab with artificial damage. As a result of verification, the proposed method quickly identified the presence of damage inside the concrete, especially for honeycomb-like defects located at the top of the rebar. This study has practical significance in scanning structures over a large area more quickly than other non-destructive testing methods, such as ultrasonic methods. [ABSTRACT FROM AUTHOR]

Based on the amplitude attribute analysis of ground penetrating radar (GPR) data, this paper applies GPR to the identification of internal damages and abnormal objects in stone walls of Tibetan ruins. The corresponding relationship between the characteristics of internal damages and abnormal objects and the radar data is explored through the Tibetan stone walls (TSWs) simulation test. The identification of location and size of the damages and abnormal objects in TSWs is realized based on the Mahalanobis distance abnormal data discrimination method. Using the normal distribution and the noncentral chi-square distribution, the identification law of types of the damages and abnormal objects is constructed, which takes root mean square (RMS) amplitude and interface reflection coefficient as the characteristic values. The field detection results of TSWs at three Tibetan sites are taken as an extension and supplement to the simulation results, and a set of identification atlas for the location, size and type of the internal damages and abnormal objects in TSWs is established. The application results of the identification atlas were verified by the field detection and the results show that the atlas has a high accuracy, which can significantly improve the efficiency of the identification, and can provide a basis for the performance research, protection and maintenance of TSWs. [ABSTRACT FROM AUTHOR]

An important geological risk to which many towns in Puglia are exposed is sinking cavities in urban areas. For urban centers, studying, mapping, providing geological and speleological descriptions, classifying, and cataloging the forms and types of cavities is essential because cavities are linked to past local anthropic and natural processes at different sites. These circumstances could lead to the enhancement of existing underground cavities in urban areas through conservation and continuous monitoring. Unfortunately, in many cases, these underground cavities have been used as landfills and subsequently abandoned. In late March 2007, one of these cavities collapsed inside Gallipoli's inhabited center, causing damage to the structures but fortunately not human lives. In the area surrounding the collapsed cavity, a series of geophysical investigations were undertaken using ground penetrating radar in an attempt to delimit the area of collapse and develop possible interventions for restoration. In the same area, these measures were repeated 16 years later in December 2022 due to another collapse. The comparison between data acquired in these two periods shows that there were no strong changes apart from an increased presence of subsoil moisture in 2022. [ABSTRACT FROM AUTHOR]

Purpose. The research in this publication reveals a comprehensive analysis of modern electronic technologies for detecting objects in the surface layers of the ground, assessing their efficiency and accuracy, and identifying promising areas for further innovation and research in this area. Methodology. To achieve the research objectives, the theoretical analysis of scientific literature, as well as methods of analyzing and summarizing existing data were used. The main research tools were a comparative analysis and classification of the methods used to detect objects in the surface layers of the ground. The solution of scientific problems was carried out using a systematic approach to the selection of materials, the use of inductive and logical analysis, and observation methods to analyze information obtained from the literature. Findings. The study analyzed the main technologies for detecting objects in the upper layers of the ground: ground penetrating radar (GPR), metal detectors, laser Doppler vibrometry, magnetometry, and optical methods. It was found that the combination of different technologies can significantly improve the accuracy and efficiency of object detection. This work also highlighted the potential of applying machine learning to improve object classification and reduce false positives. Further, it was found that reducing the weight and power consumption of detection systems can facilitate their use on unmanned vehicles, which opens up new prospects for the use of these technologies in remote monitoring and exploration of hard-to-reach areas. Originality. This paper is the first to systematize and analyze in detail the existing technologies for detecting objects in the upper layers of the ground, including GPR, metal detectors, laser vibrometry, magnetometry, and optical methods, based on criteria such as detection depth, equipment cost, and the possibility of integration with other systems. This comprehensive approach allows us to identify white spots in current research and identify areas for further development of each method, including improving accuracy, reducing power consumption and weight of devices for more efficient use on UAVs and ground operations. Practical value. Comparison results of such electronic technologies as GPR, metal detectors, laser vibrometry, multispectral imaging have been obtained. The current trends in the development of these technologies and opportunities for further research have been identified. [ABSTRACT FROM AUTHOR]

The study carried out in different areas of the city of Mérida, Yucatán, has the objectives of locating pre-Hispanic or colonial archaeological remains, register leveled areas from the Mayan times and to verify the existence of karstic areas in the subsoil, among others. For these studies in urban areas, we used ground penetrating radar (GPR), one of the non-invasive geophysical techniques. This technique allows to detect remains below the modern street pavement without interference in urban areas, reducing the need of excavation or other actions that may modify the area to be studied. In the present stage of the project, we selected places where the exploratory lines performed in previous seasons suggested the possibility of having archaeological remains below the city streets. We chose two zones where the bibliographic research indicates the existence of large platforms that were part of the T'Ho Mayan city, in another zone we verify the existence of a sculpture monument, and we also studied an archaeological park in the outskirts of the city. Most results confirmed the hypothesis, so we found extensive horizontal reflections interpreted as ancient leveling in the places where the platforms could be. In the Kambul zone, we found a clear hyperbolic reflection interpreted as a buried, large stone. In Chen Hó archaeological park, we found some cultural features inside the mounds. Besides the cultural features, we found many deep anomalies, interpreted as karstic zones, which are relevant because in the future they might reach the surface. [ABSTRACT FROM AUTHOR]

This work presents the results of an advanced geophysical characterization of a contaminated site, where a correct understanding of the dynamics in the unsaturated zone is fundamental to evaluate the effective management of the remediation strategies. Large-scale surface electrical resistivity tomography (ERT) was used to perform a preliminary assessment of the structure in a thick unsaturated zone and to detect the presence of a thin layer of clay supporting an overlying thin perched aquifer. Discontinuities in this clay layer have an enormous impact on the infiltration processes of both water and solutes, including contaminants. In the case here presented, the technical strategy is to interrupt the continuity of the clay layer upstream of the investigated site in order to prevent most of the subsurface water flow from reaching the contaminated area. Therefore, a deep trench was dug upstream of the site and, in order to evaluate the effectiveness of this approach in facilitating water infiltration into the underlying aquifer, a forced infiltration experiment was carried out and monitored using ERT and ground-penetrating radar (GPR) measurements in a cross-hole time-lapse configuration. The results of the forced infiltration experiment are presented here, with a particular emphasis on the contribution of hydro-geophysical methods to the general understanding of the subsurface water dynamics at this complex site. [ABSTRACT FROM AUTHOR]

Featured Application: Object detection method based on three-dimensional GPR data of railroad tracks using AI, trained solely on simulation data. 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. [ABSTRACT FROM AUTHOR]

The underground basement of a building is highly affected by anomalous seepage problems. Detection of seepage-prone regions through and around buildings becomes a need in other to sustain their stability. It is of great importance as well to have targeted remedies. However, traditional methods for examining these areas are often destructive and expensive, compelling the use of non-destructive geophysical techniques. This work aims to utilize and demonstrate the hands-on application of ground penetrating radar (GPR) and self-potential (SP) methods as an innovative combination to study seepage-prone zones in the basement of a building. Simulated responses of various seepage zones have been generated based on several significant factors. For better visualization, all 2D radargrams of a block were combined to produce a 3D model using GPR Slice software to distinguish various features at different depths. Higher positive SP values show the presence of high moisture or seepage-prone regions. Conclusively, the combined geophysical method of GPR and SP is trustworthy for conducting a quick and effective inspection of seepage-prone regions and probable source points for detailed characterization of the basement of a building. [ABSTRACT FROM AUTHOR]

A geophysical exploration employing ground‐penetrating radar (GPR) and electrical resistivity tomography (ERT) was conducted at the Western Cemetery, Giza, Egypt, in 2021–23 by a joint research team of Higashi Nippon International University, Tohoku University and the National Research Institute of Astronomy and Geophysics (NRIAG), Helwan, Egypt. We believe we found an anomaly: a combination of a shallow structure connected to a deeper structure. The shallow structure, which is L‐shaped in the horizontal plane, 10 m by 10 m, was clearly imaged by GPR. It seems to have been filled with sand, which means it was backfilled after it was constructed. It may have been an entrance to the deeper structure. Its depth is of up to 2 m, measured from the ground surface. Below this structure, ERT reveals a highly electrically resistive anomaly, which extends over an area of about 10 m by 10 m. The depth of the structure is about 5–10 m below the surface. Electrically resistive material in a sand dune can be a mixture of sand and gravel, including sparse spacing or air voids within it. Neither GPR nor ERT could identify the properties of the anomaly. [ABSTRACT FROM AUTHOR]

Ground penetrating radar (GPR) is one of the most useful non-destructive techniques for locating underground objects. Advancements in this technology have facilitated the development of new sensors over the past decade. In this paper, an accuracy assessment of the location of underground objects using various GPR antennas is presented. To achieve the stated goals, measurements of 5 concrete slabs, reinforced with steel bars of various diameters and located at variable depths were taken. The experiment includes the usage of three GPR antennas to assess the format, characteristics, and differences of extracted data. This set of antennas from different manufacturers varied in terms of operating frequency. Additional lidar data from TLS (terrestrial laser scanning) was utilized in the methodology to provide precise surface measurements and therefore, external orientation of the surveyed data. The experiment allowed for the determination of vertical and horizontal accuracy for three tested antennas and the assessment of increasing errors value with greater depth of the measured items, which is important for surveying accuracy forecasting. [ABSTRACT FROM AUTHOR]

This study aims to assess the impact of the sand-clay ratio on the detection of simulated forensic targets resembling human burial evidence using ground-penetrating radar (GPR). To achieve this goal, we established a controlled site consisting of four experimental graves (SEPs), with each SEP representing a distinct burial scenario. The project's objectives encompass evaluating how varying the clay soil content influences the detection of swine targets using 2D, quasi-3D, and 4D GPR imaging techniques. We observed signal attenuation in the GPR data during the rainy season and after reflection from larger targets, primarily due to the conductive behavior of the soft tissues within the targets. We achieved more precise results in an SEP that was 85% sand and 15% clay material, regardless of seasonality. We obtained better results in the dry season due to the greater penetrability of electromagnetic waves and more explicit reflections. In comparison, we achieved more precise results for SEP03, which was 70% sand and 30% clay material. In conclusion, controlled sites are invaluable tools for geophysical investigations, as they provide a controlled environment where we can meticulously adjust various parameters, leading to a more precise and insightful analysis of the results. By systematically manipulating factors such as the soil composition, target depth, and environmental conditions, researchers can effectively calibrate their instruments and methodologies, enhancing the accuracy and reliability of their findings. Therefore, controlled sites not only facilitate comprehensive data collection but also serve as essential platforms for refining and validating geophysical techniques, ultimately advancing the field of geophysical forensics. [ABSTRACT FROM AUTHOR]

As the transmitter and receiver (Tx and Rx, respectively) are located in close proximity during a typical ground‐penetrating radar (GPR) survey, the powerful signal generated by the Tx and which is then recorded by the Rx at various time delays, can be saturated at early times (i.e., this is the direct wave (DW) signal reaching the Rx). This often causes the masking of shallow targets, complicating data interpretation. In this study, our aim is to examine the spatial distribution of the electromagnetic signals around the Tx, attempting to locate areas where the DW becomes minimum, whereas the signal strength from subsurface targets (i.e., reflected wave – RW) remains ideally unchanged. The position of these local minima in the DW signal could give rise to advantageous Tx–Rx configurations, where clear reflections from subsurface targets lying at shallow depths can be obtained with the least possible involvement of the DW. To perform such a study, we carried out static field measurements over a flat lying reflector as well as numerical simulations in a reflection, common‐offset mode around a transmitting antenna. In the field, we also collected wide‐angle reflection–refraction data to determine the GPR wave velocity in the uppermost layer. GPR signals were recorded by the Rx around the Tx in three concentric circles of various radii (i.e., varying the Tx/Rx separation), using a specific angular step and varying the Tx/Rx polarization each time. The synthetic data were produced using a three‐dimensional finite‐difference time‐domain modelling tool. Field and numerically simulated data were analysed and compared to study the behaviour of both the DW and RW events around the Tx when changing the Tx/Rx distance, their respective angular position, as well as their relative polarization/orientation. [ABSTRACT FROM AUTHOR]

Cost‐effective computing capabilities have paved the road for the use of numerical modelling to develop advanced methods and applications of ground‐penetrating radar (GPR). Realistic synthetic data and the corresponding modelling techniques, respectively, should consider all subsurface and above‐ground aspects that influence GPR wave propagation and the characteristics of recorded signals. Critical aspects that can be realized in modern GPR modelling tools include heterogeneous and frequency‐dependent material properties, complex structures and interface geometries as well as three‐dimensional antenna models, including the interaction between the antenna and the subsurface. However, realistic noise related to the electronic components of a GPR system or ambient electromagnetic noise is often not considered, or simplified by assuming a white Gaussian noise model which is added to the modelled data. We present an approach to include realistic noise scenarios as typically observed in GPR field data into the flow of modelling synthetic GPR data. In our approach, we extract the noise from recorded GPR traces and add it to the modelled GPR data via a convolution‐based process. We illustrate our methodology using a modelling exercise, where we contaminate a synthetic two‐dimensional GPR dataset with frequency‐dependent noise recorded in an urban environment. Comparing our noise‐contaminated synthetic data with field data recorded in a similar environment illustrates that our method allows the generation of synthetic GPR with realistic noise characteristics and further highlights the limitations of assuming pure white Gaussian noise models. [ABSTRACT FROM AUTHOR]

Ground penetrating radar (GPR) is a commonly used tool for railway trackbed inspection due to its ability to collect information about subsurface materials at high resolution and high speed. Although GPR recording systems allow for the collection of vast quantities of data (hundreds of kilometres per day), accurate ground truth information is difficult to obtain. Models of trackbed can be used to generate synthetic radargrams to provide a better understanding and predictability of GPR responses to a wide range of trackbed conditions. In this research, we produced models of ballast using randomly shaped 3D particles, with a range of particle size distributions to represent various stages of ballast breakdown. Additionally, void spaces are partially filled with a constant dielectric material to represent ballast contamination. We used gprMax to simulate the GPR response for a 2 GHz horn antenna over the trackbed models. These simulations resulted in radargrams that are visually indistinct from real recorded data in known conditions. These radargrams, along with their formative models, have provided valuable insights into how variations in trackbed conditions can impact GPR data. [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) is a rapid and non-destructive geophysical technique widely employed to detect and quantify subsurface structures and characteristics. Its capability for time lapse (TL) detection provides essential insights into subsurface hydrological dynamics, including lateral flow and soil water distribution. However, during TL-GPR surveys, field conditions often create discrepancies in surface geometry, which introduces mismatches across sequential TL-GPR images. These discrepancies may generate spurious signal variations that impede the accurate interpretation of TL-GPR data when assessing subsurface hydrological processes. In responding to this issue, this study introduces a TL-GPR image alignment method by employing the dynamic time warping (DTW) algorithm. The purpose of the proposed method, namely TLIAM–DTW, is to correct for geometric mismatch in TL-GPR images collected from the identical survey line in the field. We validated the efficacy of the TLIAM–DTW method using both synthetic data from gprMax V3.0 simulations and actual field data collected from a hilly, forested area post-infiltration experiment. Analyses of the aligned TL-GPR images revealed that the TLIAM–DTW method effectively eliminates the influence of geometric mismatch while preserving the integrity of signal variations due to actual subsurface hydrological processes. Quantitative assessments of the proposed methods, measured by mean absolute error (MAE) and root mean square error (RMSE), showed significant improvements. After performing the TLIAM–DTW method, the MAE and RMSE between processed TL-GPR images and background images were reduced by 96% and 78%, respectively, in simple simulation scenarios; in more complex simulations, MAE declined by 27–31% and RMSE by 17–43%. Field data yielded reductions in MAE and RMSE of >82% and 69%, respectively. With these substantial improvements, the processed TL-GPR images successfully depict the spatial and temporal transitions associated with subsurface lateral flows, thereby enhancing the accuracy of monitoring subsurface hydrological processes under field conditions. [ABSTRACT FROM AUTHOR]

A tremendous number of landmines has been buried during the last decade. In recent years, various autonomous platforms equipped with ground-penetrating radars (GPRs) have been proposed for the detection of landmines. These systems have already demonstrated their performance in controlled environments with known ground truth. However, it has been observed that the influence of surface conditions in the form of vegetation and roughness as well as soil moisture content significantly reduce the detection probability. The influence of these individual factors on a ground-offset GPR is presented and discussed in this work. Each of these factors significantly degrades the backscattered signal. With increasing soil moisture, the signal gets attenuated more strongly; however, the signature is maintained in the phase of the C-Scans. An increase in surface roughness deteriorates the target pattern making it difficult to detect buried objects unambiguously. Vegetation, especially with irregular leaf structures, can appear as a ghost target and scatter the electromagnetic waves. In most cases, the target is easier to detect in the phase of the B- or C-Scan. [ABSTRACT FROM AUTHOR]

Over the past few years, remote sensing, radar, and imaging applications have all utilized Ultra-Wideband (UWB) technology. This work provides a parametric study on monopole antennas for Ground Penetrating Radar (GPR) systems. The intended antenna has an incomplete ground plane and two circular radiating patches, known for their compact design, notable high gain, and high efficiency. Furthermore, it provides an advantageous bandwidth. The suggested antenna design show-cases its appropriateness for lower frequencies, attributed to its compact dimensions. The proposed design for antenna characteristics in ground-penetrating radar systems emphasizes a requirement for large bandwidth and high gain to achieve optimal image resolution. This article delineates the design methodology and simulation of a monopole antenna developed specifically for applications in Ground Penetrating Radar (GPR). In this design, we utilize the Roger RT Duroid 5880 substrate, characterized by a relative permittivity of 2.2, a height (h) of 1.575 mm, and a loss tangent of 0.0009. The dimensions of the substrate are miniaturized to 42 mm × 40 mm × 1.575 mm. The antenna results are obtained using CST computer simulation technology software to derive the results for this antenna, and the simulations yielded favorable outcomes. The proposed array antenna demonstrates commendable characteristics at an operating frequency of 5.6 GHz, with a reflection coefficient (S11) of – 46 dB, a bandwidth of 1.6 GHz, a gain of 8.302 dB, VSWR of 1.009, and an efficiency of 99.9 %. The obtained results are highly competitive, suggesting that the proposed antenna is well-positioned to fulfill the requirements associated with Ground Penetrating Radar (GPR) applications. [ABSTRACT FROM AUTHOR]

Infrastructure bridges play a crucial role in fostering economic and social development. However, the adverse effects of natural hazard and weather degradation, coupled with escalating rates of traffic, pose a significant threat. The resultant strain on the structure can lead to undue stress, elevating the risk of a critical asset failure. Hence, non-destructive testing (NDT) has become indispensable in the surveillance of bridge infrastructure. Its primary objectives include ensuring safety, optimizing structural integrity, minimizing repair costs, and extending the lifespan of bridges. NDT techniques can be applied to both existing and newly constructed bridge structures. However, it is crucial to recognize that each NDT method comes with its own set of advantages and limitations tailored to specific tasks. No single method can provide an effective and unequivocal diagnosis on its own. Among the various NDT methods, Ground Penetrating Radar (GPR) has emerged as one of the most widely employed techniques for monitoring bridges. In fact, recent technical regulations now mandate the use of GPR for bridge monitoring and characterization, underscoring its significance in ensuring the structural health and longevity of these critical infrastructures. Ground Penetrating Radar (GPR) stands out as one of the most highly recommended non-destructive methods, offering an efficient and timely assessment of the structural conditions of infrastructure. Recognizing the pivotal role of non-destructive testing (NDT) in this context, this paper aims to elucidate recent scientific endeavors related to the application of GPR in bridge engineering structures. The exploration will commence with a focus on studies conducted both at the model level within laboratory settings and on real cases. Subsequently, the discussion will extend to encompass the characterization and monitoring of the bridge's main elements: slab, beam, and pillar. By delving into these scientific experiences, this paper intends to provide valuable insights into the efficacy and applicability of GPR in assessing and ensuring the structural integrity of bridges. This paper provides a concise survey of the existing literature on the application of Ground Penetrating Radar (GPR) in the assessment of bridges and viaducts constructed with masonry and reinforced concrete, taking into account papers of journal articles and proceedings available on open databases. Various approaches employed in both laboratory and field settings will be explored and juxtaposed. Additionally, this paper delves into discussions on novel processing and visualization approaches, shedding light on advancements in techniques for interpreting GPR data in the context of bridge and viaduct evaluations. [ABSTRACT FROM AUTHOR]

Stope design is an important part of mine planning, and it aims to balance ore recovery, ore dilution, and production costs without compromising the safety aspects. This paper summarizes the main results from the research, which aims to introduce new techniques to describe the ore body and surrounding rock mass at the tunnel face prior to stope excavation. The research comprises a literature review and a survey among mining professionals to assess current stope design practices. The study identifies geotechnical data, software improvements, and integration of design into mine planning as the most critical areas for improvement. The empirical part of the study proposes new techniques for fast data acquisition. The laser-induced breakdown spectrometry (LIBS) technique is developed for measurements at the tunnel face and from core boxes to provide mineralogical and geometallurgical data. Ground-penetrating radar (GPR) studies are conducted to improve discontinuity characterization, and rapid photogrammetric methods are proposed for efficient tunnel geometry characterization. The techniques discussed in this paper already have many industrial applications. This study reveals their potential to be adopted and further developed to serve ore and rock mass characterization for stope design. [ABSTRACT FROM AUTHOR]

Moisture is one of the main causes of degradation of heritage buildings. Early detection of zones affected by moisture is crucial information for preservation and maintenance of those structures. Ground-penetrating radar (GPR) is an effective survey method to assess damage in civil engineering and structures. Several methodologies involving this technique have been applied to determine the extension of damping in concrete, stone, and brick structures. This article summarizes the different signal analysis techniques generally used to detect moisture from GPR data. Four different case studies are included, covering different types of buildings. The case studies include the description of the problem, the results, the methodology (data acquisition, survey parameters, and processing), and the limits and advantages. Comparing the different studies, the limitations and advantages are associated with each type of problem and a final discussion describes other non-destructive testing techniques, numerical simulations and methodologies that could provide more reliable understanding when combined with GPR data. [ABSTRACT FROM AUTHOR]

Settlements represent one of the most dangerous causes of degradation of the stability and preservation of buildings. This work presents a Ground-Penetrating Radar (GPR) survey aiming to investigate settlement problems that compromise the structural integrity of an Indiana-style house built in 1933–36 (Cabanas, northwest of Spain). From a simple visual inspection, it was possible to observe external damage like cracking, subsidence and bulging in the building façades, retaining walls and pavements. The GPR survey was conducted using a ProEx system with a 500 MHz antenna, which allowed for the production of an overall image of the subsoil until a depth of 3–4 m. The GPR data allowed for the detection of subsidence, voids and poor soil compaction, which made easier the identification of building settlements. The GPR interpretation was then validated with geotechnical prospection (sampling and dynamic probing superheavy (DPSH) tests), which showed good agreement between techniques. The better knowledge of this settlement phenomena was promising for the engineers and architects engaged in the design of conservation activities for such a singular architectural heritage. [ABSTRACT FROM AUTHOR]

Different engineering geological and geophysical investigations were performed at the Sopu promontory in the island of Gozo (Malta), involved in an impressive lateral spreading process due to the superimposition of a stiff limestone (ULC) on a ductile clay (BC). The applied techniques include: traditional geological and engineering geological surveys, unmanned aerial vehicles (UAV) survey, electrical resistivity tomography (ERT) survey, ground-penetrating radar (GPR) investigations, single-station seismic ambient noise measurements, and array seismic ambient noise measurements. The integration of the obtained results allowed us to reconstruct a subsoil model of the promontory that includes features related to the local geology of the slope and to the landslide process, as well as to define a conceptual model that describes the main evolution phases of the expansion process. The presence of back-tilted rock blocks with no features of polarization of Rayleigh waves evidenced the different failure mechanism of the rigid UCL plateau at the Sopu promontory with respect to the Selmun promontory, located in the close island of Malta, where the lateral spreading due to the same geological setting tends to produce unstable rock blocks with a toppling mechanism. This result encourages further future observations and analyses of this topic. [ABSTRACT FROM AUTHOR]

Improving the exploration of deep‐seated mineral deposits and assessing the stability of the mine pillars require that geophysical techniques are deployed in a fast and cost‐effective manner with minimal environmental impact. This research presents results from in‐mine reflection seismic experiments and a ground penetrating radar (GPR) survey conducted at the Maseve platinum mine, South Africa. The research aims to develop and implement methods to image platinum group metal (PGM) deposits and geological structures near mine tunnels and assess the stability of pillars. The seismic experiments were conducted using a sledgehammer source (10 lb), conventional cabled geophones (14 Hz), and a landstreamer with 4.5 Hz vertical component geophones. The GPR survey was conducted using a Noggin 500 GPR system with 500 MHz centre frequency. An image of the underlying orebody and geological structures down to 100 m from the mine tunnel floor (∼500 m below ground surface) was produced. We correlated the coherent reflections beneath the tunnel floor with a known Upper Group (UG2) PGM orebody. The final seismic section shows that the UG2 mineralisation is dissected by near‐vertical dykes, faults and fractures. These structures, faults in particular, are interpreted to have been active post‐mineralisation, implying that they may have contributed to the current complex geometry of the deposit. Four GPR profiles were collected around a stability pillar adjacent to the seismic lines. The radargram sections were processed to improve the signal‐to‐noise ratio (S/N). The results show different patterns of fracturing and stress‐induced structures. These fractures were shown to be sub‐vertical and, possibly, constitute complex micro‐structures within the pillar, which could compromise the pillar stability and integrity. The study demonstrates that in‐mine seismic and GPR surveys can be cost‐effective and valuable for mineral exploration. [ABSTRACT FROM AUTHOR]

In the field of the restoration of monumental heritage, non-destructive geophysical techniques have gained an already widely acknowledged importance. The possibility to understand the state of preservation of the artefacts without resorting to a destructive action is extremely useful in identifying unknown or presumed emergencies in order to better lead the restoration operations. At present geophysics is underutilised and furthermore, common techniques may not be optimal for some specific targets or sites. Therefore, more controlled research is needed to better understand the applicability of these methodologies when searching for cultural heritage applications in various material types. The purpose of this paper is to provide a new approach that involves the joint use of several geophysical methods for the study of the probable causes of deterioration on a monument of considerable historical and artistic importance. The monument is the Basilica of Santa Croce in Lecce. It is a baroque church internationally well-known. The starting point of this research was the evidence that some structures of the façade are more damaged and present signs of subsidence. The study of the causes of damage was dealt with a geophysical survey using ground-penetrating radar and electrical resistivity tomography. The results demonstrate the effectiveness of the choice of the two methods and allow to obtain information on buried structures both inside the church and on the façade and to locate and identify anomalies related to a restoration intervention carried out in the 80s. Furthermore, a microclimatic analysis performed inside the Basilica shows a probable connection between the humidity present on the surface and the conductive layers present in the subsoil and highlighted with the electrical method. [ABSTRACT FROM AUTHOR]

The condition of the wood structure and its components should be carefully recorded before considering any action. The diagnosis of wood structures in heritage should precede any intervention. It is important to know preliminarily the construction and structural system, the decay condition and the causes. Furthermore, damage or structural failure should be considered. The diagnosis must be based principally on measurements of physical parameters using non-destructive testing, and if necessary on laboratory testing. Water is one of the principal causes of wood decay. In this study, ground-penetrating radar and time domain reflectometry were used to estimate the dielectric permittivity and successively the volumetric water content of several types of wood. An empirical relationship was found between the dielectric constant and volumetric water content. Results were applied to two case studies: the Cathedral of Foggia and the Castle of Carosino. [ABSTRACT FROM AUTHOR]

Research in many forensic science fields commonly uses domestic pigs (Sus spp.) as proxies for human remains, due to their physiological and anatomical similarities, as well as being more readily available. Unfortunately, previous research, especially that which compares the decompositional process, has shown that pigs are not appropriate proxies for humans. To date, there has not been any published research that specifically addresses whether domestic pigs are adequate human proxies for the geophysical detection of clandestine graves. As such, the aim of this paper was to compare the geophysical responses of pig cadavers and human donor graves, in order to determine if pigs can indeed be used as adequate human proxies. To accomplish this, ground penetrating radar (GPR) and electrical resistivity tomography (ERT) responses on single and multiple pig cadaver graves were compared to single and multiple human donor graves, all of which are in known locations within the same geological environment. The results showed that under field conditions, both GPR and ERT were successful at observing human and pig burials, with no obvious differences between the detected geophysical responses. The results also showed that there were no differences in the geophysical responses of those who were clothed and unclothed. The similarity of the responses may reflect that the geophysical techniques can detect graves despite what their contents are. The study implications suggest that experimental studies in other soil and climate conditions can be easily replicated, benefiting law enforcement with missing persons cases. [ABSTRACT FROM AUTHOR]

Debris‐covered glaciers (DCG) and rock glaciers have been increasingly studied in recent years because of the role they play within local watersheds, glacial ablation models due to climate change, and as analogs for buried ice features on planetary bodies such as Mars. Characterizing the supraglacial debris layer is a large part of these efforts. Geophysical exploration of DCG has mostly excluded active seismic methods, with the exception of refraction studies, due to the attenuating properties of the debris cover and field survey efficiency. We evaluate the accuracy, field efficiency, and effectiveness of seismic refraction, reflection, and surface‐wave surveys for determining the elastic properties of the debris layer and any underlying layers on DCG using the Sourdough Rock Glacier in Southcentral Alaska as a test site. We provide evidence for imaging an ultra‐shallow seismic reflection from the bottom of the loose debris layer using ultra‐dense receiver arrays and compare it to ground‐penetrating radar (GPR) images taken along the same profiles. We also detail how reliable dispersion curve images can be extracted from the surface wave package of the seismic data using the multi‐channel analysis of surface waves technique, which allows for the (s)‐wave profile to be inverted for. We find this could be a valuable addition to the toolbox of future geophysical investigations on DCG. Plain Language Summary: Debris‐covered glaciers and rock glaciers are glaciers with a loose rock layer covering all or most of their surface. This layer can be several meters thick and plays an important role in how fast the glacier melts. These types of glaciers are an important analog to similar buried ice features observed on other planetary bodies, such as Mars. Typically, the subsurface of these glaciers is studied using the geophysical method of ground‐penetrating radar (GPR), though in this paper we explore how active‐source seismic methods could be utilized in future surveys. We demonstrate that using active‐seismic techniques can provide information on the "stiffness" of the debris layer, which can add context to a GPR survey and ultimately aid in interpreting glacial features. Key Points: We use ultra‐dense receiver spacing to image a seismic reflection from the bottom of the loose debris layer on a debris‐covered glacierWe demonstrate that we can obtain the shear‐wave velocity structure (stiffness) observations for debris cover on glaciers [ABSTRACT FROM AUTHOR]

This study aims to assess the impact of the sand-clay ratio on the detection of simulated forensic targets resembling human burial evidence using ground-penetrating radar (GPR). To achieve this goal, we established a controlled site consisting of four experimental graves (SEPs), with each SEP representing a distinct burial scenario. The project’s objectives encompass evaluating how varying the clay soil content influences the detection of swine targets using 2D, quasi-3D, and 4D GPR imaging techniques. We observed signal attenuation in the GPR data during the rainy season and after reflection from larger targets, primarily due to the conductive behavior of the soft tissues within the targets. We achieved more precise results in an SEP that was 85% sand and 15% clay material, regardless of seasonality. We obtained better results in the dry season due to the greater penetrability of electromagnetic waves and more explicit reflections. In comparison, we achieved more precise results for SEP03, which was 70% sand and 30% clay material. In conclusion, controlled sites are invaluable tools for geophysical investigations, as they provide a controlled environment where we can meticulously adjust various parameters, leading to a more precise and insightful analysis of the results. By systematically manipulating factors such as the soil composition, target depth, and environmental conditions, researchers can effectively calibrate their instruments and methodologies, enhancing the accuracy and reliability of their findings. Therefore, controlled sites not only facilitate comprehensive data collection but also serve as essential platforms for refining and validating geophysical techniques, ultimately advancing the field of geophysical forensics.

Detection of the tie bars in concrete pavement has been a challenging task. To address the purpose, ground penetrating radar (GPR) was used to acquire a large amount of image data along the longitudinal construction joints of plain concrete pavement in the field. The GPR image data was filtered to construct the dataset, containing 2185 tie bar reflected waves in 670 GPR images. Then, the YOLO series models, as the deep learning algorithms applied in inspecting the tie bars from GPR images, were well trained with the GPR training and validation sets. The comprehensive detection accuracy of the YOLOv4 model outperforms the YOLOv3, YOLOv3-tiny, and YOLOv4-tiny models in the test set. The mAP@0.5 value of the YOLOv4 model can reach 99.74%. All the signatures of tie bars in the testing GPR images, no matter whether they are incomplete, compressed, blurry with missing signal, or strong background noise, can be correctly and completely anchored using the bounding box based on the YOLOv4 model. Meanwhile, the detection speed of the YOLOv4 model for GPR data video is 50.8 frames per second. Therefore, the YOLOv4 model is reliable for automatically detecting the tie bars from GPR data in real-time. [ABSTRACT FROM AUTHOR]

The Ground Penetrating Radar method is used to study a three-layered model of the surrounding rock–void–lining interface with regard to variation in the void thickness and in the electromagnetic properties of the void filler. The numerical modeling uses the method of finite differences in the time domain. The numerical modeling data are compared with the results of the physical simulation implemented using SIR-3000 GPR with the Model 52600 antenna having the working frequency of 2.6 GHz (S-band). It is found that the size of the void behind concrete lining and the electromagnetic properties of a material filling the void have influence on the accuracy of ranging to the lower boundary of the void and to the discontinuity in the form of a steel bolt located immediately behind the void in surrounding rock mass. [ABSTRACT FROM AUTHOR]