Search

Regular monitoring and inspection of military railroad tracks are necessary to ensure the safe transportation of military freight. Manual railroad inspection has drawbacks and limitations that can impact accuracy and efficiency. This study introduces a novel tool designed to automate Ground Penetrating Radar (GPR) imaging interpretation for railroad ballast condition assessment, aiming to reduce human intervention in inspections. The tool uses advanced signal processing techniques, such as the Short-Time Fourier Transform (STFT) and Wavelet Transform (WT), to quantify ballast fouling levels accurately, enhancing maintenance and safety protocols for railroad tracks. Validation through comprehensive testing, including two case studies, demonstrates the tool’s superior efficacy over traditional manual inspection methods. This research represents a pivotal step towards more efficient and reliable infrastructure management, ensuring critical railroad systems’ safety and operational integrity.

Detecting sub-surface objects poses significant challenges, partly due to attenuation of the ground medium and cluttered environments. The acquisition polarisation and antenna orientation can also yield significant variation of detection performance. These challenges can be mitigated by developing more versatile systems and algorithms to enhance detection and identification. In this study, a novel application of a 3D SAR inverse algorithm and polarisation synthesis was applied to ultra-wideband polarimetric data of buried objects. The principle of polarisation synthesis facilitates an adaptable technique which can be used to match the target’s polarisation characteristics, and the application of this revealed hidden structures, enhanced detection, and increased received power when compared to single polarisation results. This study emphasises the significance of polarimetry in ground-penetrating radar (GPR), particularly for target discrimination in high-lift-off applications. The findings offer valuable insights that could drive future research and enhance the performance of these sensing systems.

Radar polarimetry is a technique that can be used to enhance target detection, identification and classification; however, the quality of these measurements can be significantly influenced by the characteristics of the radar antenna. For an accurate and reliable system, the calibration of the antenna is vitally important to mitigate these effects. This study presents a methodology to calibrate Ultra-Wideband (UWB) dual-polarised antennas in the near-field using a thin elongated metallic cylinder as the calibration object. The calibration process involves measuring the scattering matrix of the metallic cylinder as it is rotated, in this case producing 100 distinct scattering matrices from which the calibration parameters are derived, facilitating a robust and stable solution. The calibration procedure was tested and validated using a Vector Network Analyser (VNA) and two quad-ridged antennas, which presented different performance levels. The calibration methodology demonstrated notable improvements, aligning the performance of both functioning and under-performing antennas to equivalent specifications. Mid-band validation measurements indicated minimal co-polar channel imbalance (

This study addresses the features of the internal structure of the geological layers adjacent to the Polychrome Hall ceiling of the Cave of Altamira (Spain) and their link to the distribution of moisture and geological discontinuities mainly as fractures, joints, bedding planes and detachments, using 3D Ground Penetrating Radar (GPR) mapping. In this research, 3D GPR data were collected with 300 MHz, 800 MHz and 1.6 GHz center frequency antennas. The data recorded with these three frequency antennas were combined to further our understanding of the layout of geological discontinuities and how they link to the moisture or water inputs that infiltrate and reach the ceiling surface where the rock art of the Polychrome Hall is located. The same 1 × 1 m2 area was adopted for 3D data acquisition with the three antennas, obtaining 3D isosurface (isoattribute-surface) images of internal distribution of moisture and structural features of the Polychrome Hall ceiling. The results derived from this study reveal significant insights into the overlying karst strata of Polychrome Hall, particularly the interface between the Polychrome Layer and the underlying Dolomitic Layer. The results show moisture patterns associated with geological features such as fractures, joints, detachments of strata and microcatchments, elucidating the mechanisms driving capillary rise and water infiltration coming from higher altitudes. The study primarily identifies areas of increased moisture content, correlating with earlier observations and enhancing our understanding of water infiltration patterns. This underscores the utility of 3D GPR as an essential tool for informing and putting conservation measures into practice. By delineating subsurface structures and moisture dynamics, this research contributes to a deeper analysis of the deterioration processes directly associated with the infiltration water both in this ceiling and in the rest of the Cave of Altamira, providing information to determine its future geological and hydrogeological evolution.

The primary objective of this case study is to evaluate the effectiveness of drone-based ground penetrating radar (GPR) in detecting and mapping underground water levels and soil-to-rock boundaries. This knowledge is crucial for accurate structural engineering analyses, including foundation engineering and site-specific response evaluations. The paper also considers drone-based GPR to overcome common urban obstacles, topographic variations, and environmental factors by simply flying over them, offering a promising solution to these challenges. The research utilized drone-based GPR equipped with an unshielded 150 MHz dipole antenna and employed filtering procedures to diminish the effect of above-ground obstacles on the interpretation of our results. The study unequivocally demonstrated the feasibility and effectiveness of drone-based GPR in these applications, reassuring the civil engineering community. The findings of this study significantly advance our understanding of drone-based GPR technology for mapping disturbed soil boundaries and water table levels in foundation engineering and site response applications and provide valuable recommendations for optimizing its performance in complicated terrains, thereby inspiring and guiding future research and practice in this field.

Humidity, salt content, and migration in building materials lead to weathering and are a common challenge. To understand damage phenomena and select the right conservation treatments, knowledge on both the amount and distribution of moisture and salt load in the masonry is crucial. It was shown that commercial portable devices addressing moisture are often limited by the mutual interference of these values. This can be improved by exploiting broadband radar reflectometry for the quantification of humidity in historic masonry. Due to the above-mentioned limitations, today’s gold standard for evaluating the moisture content in historic buildings is still conducted by taking drilling samples with a subsequent evaluation in a specially designed laboratory, the so-called Darr method. In this paper, a new broadband frequency approach in the range between 0.4 and 6 GHz with improved artificial-intelligence data analysis makes sure to optimize the reflected signal, simplify the evaluation of the generated data, and minimise the effects of variables such as salt contamination that influence the permittivity. In this way, the amount of water could be determined independently from the salt content in the material and an estimate of the salt load. With new machine learning algorithms, the analysis of the permittivity is improved and can be made accessible for everyday use on building sites with minimal intervention by the user. These algorithms were trained with generated data from different drying studies on single building bricks from the masonries. The findings from the laboratory studies were then validated and evaluated on real historic buildings at real construction sites. Thus, the paper shows a spatially resolved and salt-independent measurement system for determining building moisture.

This study focused on the detection of water inrush in tunnels excavated by full-section hard rock tunnel boring machines (TBMs) and employed ground penetrating radar methods for conducting research on radar signal processing algorithms. The research demonstrates that conventional techniques are inadequate for eliminating the interference of TBM equipment on radar signal propagation. This study employs a radar antenna array method for signal transmission, utilizing a wavelet double-threshold filtering algorithm and wave propagation theory to suppress clutter. These methods exhibit strong signal reception capabilities and are effective in eliminating 13.1% of the direct wave components. The adoption of a novel, efficient radar signal imaging algorithm simplifies the imaging process. Results of verification indicate that the synthetic aperture algorithm, enhanced with cross-correlation calculation, yields the optimal imaging effect. This investigation, which was conducted in conjunction with the construction of a diversion tunnel in a specific region, has confirmed the applicability of the ground penetrating radar method for the detection of water inrush in TBM tunnels by conducting a comparative analysis of the direct wave removal algorithm and the integration of the optimal imaging algorithm. The innovative application of ground penetrating radar within TBM tunnels, along with a targeted technology to mitigate signal interference from metal equipment, has led to the selection of an appropriate algorithm for both signal processing and imaging. This approach offers a novel solution for the detection of water source disasters in TBM tunnels.

Quantitative inversion of GPR data opens the door to precise characterization of underground environments. However, in order to make the inverse scattering problem solution easier from a computational viewpoint, simplifying assumptions are often applied, i.e., two-dimensional approximations or the consideration of idealized field probes and electromagnetic sources. These assumptions usually produce modeling errors, which can degrade the dielectric reconstruction results considerably. In this article, a processing step based on long short-term memory cells is proposed for the first time to correct the modeling error in a multiantenna GPR setting. In particular, time-domain GPR data are fed into a neural network trained with couples of finite-difference time-domain simulations, where a set of sample targets are simulated in both realistic and idealized configurations. Once trained, the neural network outputs an approximation of multiantenna GPR data as they are collected by an ideal two-dimensional measurement setup. The inversion of the processed data is then accomplished by means of a regularizing Newton-based nonlinear scheme with variable exponent Lebesgue space formulation. A numerical study has been conducted to assess the capabilities of the proposed inversion methodology. The results indicate the possibility of effectively compensating for modeling error in the considered test cases.

The conservation of Cultural Heritage in cave environments, especially those hosting cave art, requires comprehensive conservation strategies to mitigate degradation risks derived from climatic influences and human activities. This study, focused on the Polychrome Hall of the Cave of Altamira, highlights the importance of integrating remote sensing methodologies to carry out effective conservation actions. By coupling a georeferenced Ground Penetrating Radar (GPR) with a 1.6 GHz central-frequency antenna along with photogrammetry, we conducted non-invasive and high-resolution 3D studies to map preferential moisture pathways from the surface of the ceiling to the first 50 cm internally of the limestone structure. In parallel, we monitored the dynamics of surface water on the Ceiling and its correlation with pigment and other substance migrations. By standardizing our methodology, we aim to increase knowledge about the dynamics of infiltration water, which will enhance our understanding of the deterioration processes affecting cave paintings related to infiltration water. This will enable us to improve conservation strategies, suggesting possible indirect measures to reverse active deterioration processes. Integrating remote sensing techniques with geospatial analysis will aid in the validation and calibration of collected data, allowing for stronger interpretations of subsurface structures and conditions. All of this puts us in a position to contribute to the development of effective conservation methodologies, reduce alteration risks, and promote sustainable development practices, thus emphasizing the importance of remote sensing in safeguarding Cultural Heritage.

The S-transform is a fundamental time–frequency (T-F) domain analysis method in ground penetrating radar (GPR) data processing and can be used for identifying targets, denoising, extracting thin layers, and high-resolution imaging. However, the S-transform spectrum experiences energy leakage near the instantaneous frequency. This phenomenon causes frequency components to erroneously spread over a wider range, impacting the accuracy and precision of GPR data processing. Synchrosqueezing is an effective method to prevent spectrum leakage. In this work, we introduce the synchrosqueezing generalized phase-shifting S-transform (SS-GPST). Initially, it resolves the compatibility issue between the S-transform and the synchrosqueezing strategy through phase-shifting. Subsequently, the SS-GPST accomplishes spectral energy focusing and resolution enhancement via a generalized parameter and synchrosqueezing. A synthetic signal test shows that the SS-GPST excels over other methods at focusing degree, spectral resolution, and signal reconstruction accuracy and speed. In actual GPR tunnel detection data processing, we assess the adaptability of the SS-GPST from three aspects: spectral energy distribution, thin layer identification, and data denoising. The results indicate: (1) compared to other methods, the SS-GPST accurately expresses spectral components with a strong focusing degree and fewer interference components; (2) high-frequency slices of the SS-GPST accurately detect the top and bottom interfaces of a 3.0–3.5 cm reinforcement protection layer; and (3) due to fewer interference components in the SS-GPST spectrum, reconstructing GPR profiles through the SS-GPST inverse transform is an efficient denoising technique. The SS-GPST demonstrates adaptability to different data processing purposes, offers high-resolution T-F spectra, and shows potential to supersede the S-transform.

The paper deals with a combined time–depth conversion strategy able to improve the reconstruction of voids embedded in an opaque medium, such as cavities, caves, empty hypogeal rooms, and similar targets. The combined time–depth conversion accounts for the propagation velocity of the electromagnetic waves both in free space and in the embedding medium, and it allows better imaging and interpretation of the underground scenario. To assess the strategy’s effectiveness, ground penetrating radar (GPR) data referred to as an experimental test in controlled conditions are accounted for and processed by two different approaches to achieve focused images of the scenario under test. The first approach is based on a classical migration algorithm, while the second one faces the imaging as a linear inverse scattering approach. The results corroborate that the combined time–depth conversion improves the imaging in both cases.

With the rapidly growing interest in using structural timber, a need exists to inspect and assess these structures using non-destructive testing (NDT). This review article summarizes NDT methods for wood inspection. After an overview of the most important NDT methods currently used, a detailed review of Ground Penetrating Radar (GPR) and Ultrasonic Testing (UST) is presented. These two techniques can be applied in situ and produce useful visual representations for quantitative assessments and damage detection. With its commercial availability and portability, GPR can help rapidly identify critical features such as moisture, voids, and metal connectors in wood structures. UST, which effectively detects deep cracks, delaminations, and variations in ultrasonic wave velocity related to moisture content, complements GPR’s capabilities. The non-destructive nature of both techniques preserves the structural integrity of timber, enabling thorough assessments without compromising integrity and durability. Techniques such as the Synthetic Aperture Focusing Technique (SAFT) and Total Focusing Method (TFM) allow for reconstructing images that an inspector can readily interpret for quantitative assessment. The development of new sensors, instruments, and analysis techniques has continued to improve the application of GPR and UST on wood. However, due to the hon-homogeneous anisotropic properties of this complex material, challenges remain to quantify defects and characterize inclusions reliably and accurately. By integrating advanced imaging algorithms that consider the material’s complex properties, combining measurements with simulations, and employing machine learning techniques, the implementation and application of GPR and UST imaging and damage detection for wood structures can be further advanced.

Ground-penetrating radar (GPR) is an established technology with a wide range of applications for civil engineering, geological research, archaeological studies, and hydrological practices. In this regard, this study applies bibliometric and scientometric assessment to provide a systematic review of the literature on GPR-related research. This study reports the publication trends, sources of publications and subject categories, cooperation of countries, productivity of authors, citations of publications, and clusters of keywords in GPR-related research. The Science Citation Index Expanded (SCI-EXPANDED) and the Social Sciences Citation Index (SSCI), which can be accessed through the Web of Science Core Collection, are used as references. The findings report that the number of publications is 6880 between 2001 and 2021. The number of annual publications has increased significantly, from 139 in 2001 to 576 in 2021. The studies are published in 894 journals, and the annual number of active journals increased from 68 in 2001 to 215 in 2021. Throughout the study, the number of subject categories involved in GPR-related research fluctuated, ranging from 38 in 2001 to 68 in 2021. The research studies originated from 118 countries on 6 continents, where the United States and the People’s Republic of China led the research articles. The top five most common keywords are ground-penetrating radar, non-destructive testing, geophysics, electrical resistivity tomography, and radar. After investigating the clusters of keywords, it is determined that civil engineering, geological research, archaeological studies, and hydrological practices are the four main research fields incorporating GPR utilization. This study offers academics and practitioners an in-depth review of the latest research in GPR research as well as a multidisciplinary reference for future studies.

The georadar method was used to try to find some anthropic structures in a large square inside the Carabinieri barracks in the former military complex of San Giacomo degli Spagnoli in Palermo (Italy). These investigations are part of a broader context of a study of the entire area. The purpose of the investigations is to try to understand if under the ground there are the remains of an ancient horse passage that connected the Royal Palace of Palermo with the sea gate of the city. Furthermore, in the Middle Ages, on the site of the present square, there were most likely two churches, which no longer exist, as evidenced by numerous historical testimonies. One of the two, San Giacomo la Mazara, is known to have was placed right in front of the church of San Paolo, the subject of previous investigations. The investigations carried out on the main square of the military district allowed us to reconstruct a 3D georadar model in which numerous anomalies are highlighted. Some superficial anomalies have been attributed to the presence of sub-services, the deeper ones could be caused by the remains of the medieval underground way or those of the no longer existing medieval churches, but identifying their true nature requires further investigations and archaeological tests.

The restoration of historic buildings and structures involves a wide range of scientific and technical fields. The grouting process is among an array of rehabilitation and preservation interventions and aims to homogenize the structure after the implementation of strengthening measures. The process can provide important information regarding the state of preservation of the examined structure and correlate the progress of the process with the pathology of the monument. To achieve this, the analysis of typical raw grouting data is progressively fused with additional information from the diagnostic studies, non-destructive testing, geospatial information, and from the calculation and analysis of grouting indices. The restoration project of the Katholikon of the Monastery of Panagia Varnakova in Fokida, Greece was selected as the case study, due to its large scale and the severe earthquake damage it has sustained, which has necessitated comprehensive strengthening interventions and extensive grouting. The implementation of an integrated methodological approach validated the enhanced level of co-analysis, revealing information that is not readily deduced from a typical approach. Selected sub-areas of the Katholikon are presented, demonstrating how the observed pathology can be correlated with the results of the grouting process, while incorporating 3D data, and findings from structural and non-destructive analyses.

The Lieth Moor area, located in the district of Pinneberg, Schleswig-Holstein, Germany, is a hotspot of Late Palaeolithic settlement activity. The exceptional abundance of archaeological sites is commonly attributed to the presence of a large palaeolake. However, in the Weichselian Late glacial, there were numerous large lakes in Schleswig-Holstein. Thus, a well-founded explanation for the find concentration in Lieth Moor is still lacking, and forming a research desideratum until today. To improve our understanding of this Late Pleistocene landscape and its appeal to hunter–gatherer groups of that time, we conducted a large-scale archaeogeophysical study focusing on a possible ford of the potential palaeolake. We employed Ground-Penetrating Radar and Electromagnetic Induction measurements, supplemented by existing legacy drill-probing data, to identify and map limnic gyttja (organic lake mud) sediments and their spatial distribution within the area. The findings of our study indicate that during the Late Pleistocene to Early Holocene, the Lieth Moor area comprised a cluster of small ponds rather than a continuous lake. These ponds likely interconnected during periods of increased water levels. The presence of dry islands within the region corresponds with archaeological evidence, suggesting that Late Palaeolithic communities visited some of these islands. The absence of the previously postulated palaeolake places the known findings within a completely new palaeoenvironmental context: instead of the previously suspected ford, we assume that the proximity to the Elbe Palaeovalley played a decisive role in the repeated habitation of Lieth Moor. This area, rich in fresh water and fish, along with the dune chain situated to the west, serving as both a vantage point and windbreak, presented an ideal location for awaiting animals migrating along the river Elbe and/or as a resting place within the settlement system of mobile hunter–fisher–gatherer groups.

The church of S. Mary of the Admiral in Palermo, known as “La Martorana” and very famous for its Byzantine mosaics, has been a World Heritage site since 2015. The mosaic system of the church includes several groups of figures and scenes from the life of the Virgin Mary. From the western part of the ancient church only two mosaics survive, detached from their original position, and are now located in two internal chapels. On the occasion of several restoration works, these two mosaic panels were investigated with non-invasive techniques, in order to provide diagnostic support to the restoration and consolidation interventions. The investigations were aimed at detecting any air pockets that could cause the detachment of the tesserae or of possible differences between cement mortars under the tesserae. For this purpose, the integrated use of two non-invasive techniques namely infrared thermography (IRT) and ground penetrating radar (GPR) was considered. The joint analysis of IRT and GPR data allowed the interpretative uncertainties inherent in each technique to be reduced. Furthermore, for both techniques differentiated analyses were performed for layers at different depths under the mosaic surface. The results of these analyses were found to be more reliable regarding GPR data, compared to infrared thermography, the latter being more influenced by the reflectivity of the tesserae. However, the results partially confirmed the restorers’ diagnosis, also allowing the identification of further critical areas that could be affected by deterioration or compositional differences in the layers supporting the mosaics

In classical radar imaging, such as in Earth remote sensing, electromagnetic waves are usually assumed to propagate in free space. However, in numerous applications, such as ground penetrating radar or non-destructive testing, this assumption no longer holds. When there is a multi-material background, the subsurface image reconstruction becomes considerably more complex. Imaging can be performed in the spatial domain or, equivalently, in the wavenumber domain (k-space). In subsurface imaging, to date, objects with a non-planar surface are commonly reconstructed in the spatial domain, by the Backprojection algorithm combined with ray tracing, which is computationally demanding. On the other hand, objects with a planar surface can be reconstructed more efficiently in k-space. However, many non-planar surfaces are partly planar. Therefore, in this paper, a novel concept is introduced that makes use of the efficient k-space-based reconstruction algorithms for partly planar scenarios, too. The proposed algorithm forms an image from superposing sub-images where as many image parts as possible are reconstructed in the wavenumber domain, and only as many as necessary are reconstructed in the spatial domain. For this, a segmentation scheme is developed to determine which parts of the image volume can be reconstructed in the wavenumber domain. The novel concept is verified by measurements, both from monostatic synthetic aperture radar data and multiple-input–multiple-output radar data. It is shown that the computational efficiency for imaging irregularly shaped geometries can be significantly augmented when applying the proposed concept.

Integrating geomatics remote sensing technologies, including 3D terrestrial laser scanning, unmanned aerial vehicles, and ground penetrating radar enables the generation of comprehensive 2D, 2.5D, and 3D documentation for caves and their surroundings. This study focuses on the Altamira Cave’s karst system in Spain, resulting in a thorough 3D mapping encompassing both cave interior and exterior topography along with significant discontinuities and karst features in the vicinity. Crucially, GPR mapping confirms that primary vertical discontinuities extend from the near-surface (Upper Layer) to the base of the Polychrome layer housing prehistoric paintings. This discovery signifies direct interconnections helping with fluid exchange between the cave’s interior and exterior, a groundbreaking revelation. Such fluid movement has profound implications for site conservation. The utilization of various GPR antennas corroborates the initial hypothesis regarding fluid exchanges and provides concrete proof of their occurrence. This study underscores the indispensability of integrated 3D mapping and GPR techniques for monitoring fluid dynamics within the cave. These tools are vital for safeguarding Altamira, a site of exceptional significance due to its invaluable prehistoric cave paintings.

The present study evaluated the application of Ground Penetrating Radar and Electromagnetic Induction geophysical tools combined with sedimentology for the description of the subsurface of sites destined for the installation of ponds for an extensive freshwater fish farming system. Two areas with similar topographic characteristics (flat land near bodies of water) were investigated in the Amazon region of northern Brazil: Area 1—the future site of an aquaculture research center, and Area 2—an established fish farming operation. These tools performed well in the evaluation of the suitability of the terrain for the installation of aquaculture ponds. The application of these tools can, thus, be recommended for aquaculture projects, given that it provides advanced knowledge on the characteristics of the local soils, which is extremely important to guarantee the sustainability of any aquaculture operation. These data can help minimize the environmental impacts of the process, while maximizing the economic returns to the installation of an aquaculture operation.

In the framework of the IH-AT (Invisible Heritage Analysis and Technology) project, a cluster of churches ranging from the 11th to the 16th centuries, located in the Troodos Mountain range of Cyprus, designated by UNESCO as World Heritage monuments, were investigated using Non-Destructive-Techniques (NDT) (geophysical and topographic survey), 3D modelling and visualisation methods, contextualised and interpreted by art-historical and archaeological research. A geophysical survey, performed using a Ground Penetrating Radar (GPR), specifically aimed to confirm the presence or absence of buried features of archaeological interest at each of these sites, in particular, evidence of monastic complexes and buildings that used to surround preserved churches. This paper describes the preliminary results of this survey and some initial interpretations concerning what new information can be discerned about the now lost monastery complexes, in advance of future excavation.

Grouting of historic structures is a common procedure in many restoration projects, as the masonry in many cases requires additional strengthening. However, grouting of complex historic structures can also provide important information regarding the construction phases and the state of preservation of the internal structure of a monument, which may not be visible by the naked eye. This requires an innovative approach in order to reveal these aspects. In the current research, the data recorded from the grouting of the Holy Aedicule are implemented and analyzed, in order to obtain information regarding the construction phases of the complex Holy Aedicule structure, as well as information regarding the state of preservation of the internal structure behind the marble cladding that encloses it. The correlation of detailed grouting data with geospatial information allows for a more detailed analysis, which, coupled with ground-penetrating radar prospections, can provide critical information regarding the features of the internal structure. The results highlight the importance of this correlation to reveal information that may not be obtained through a typical approach. Thus, this study allowed for the development of an evolved interdisciplinary approach for the management of grouting data in a 2.5D environment, which can be applied in other historic structures and buildings.

As a fundamental part of ground penetrating radar (GPR) data processing, reverse time migration (RTM) can correctly position reflection waves and focusing diffraction waves on the proper spatial position. Least-squares reverse-time migration (LSRTM) is widely used in the seismic field for its ability to suppress artifacts and generate high-resolution images in comparison to conventional RTM. However, in the particular case of GPR detection methods, LSRTM is extremely susceptible to aliasing artifacts caused by under-sampling. In pursuit of enhanced precision in underground structure characterization, this paper presents the development of a new LSRTM based on modified total variation (MTV) regularization to improve imaging resolution. Initially, the objective function of LSRTM is derived by combining the Born approximation in 2-D transversal magnetic mode. Next, the adjoint equations and their gradients are solved using the Lagrange multiplier method. The objective function is then constrained by MTV regularization to ensure the precision and convergence of the LSRTM, which delivers a refined edge with reconstruction details. In the numerical experiments, in comparison to the conventional LSRTM method, the LSRTM-MTV algorithm demonstrated a 30.4% increase in computational speed and a 21.1% reduction in mean squared error (MSE). The outperformance of the proposed method is verified in detail through the image resolution and amplitude preservation in the test of synthetic data and laboratory data. Future research efforts will center on applying the proposed method to models featuring dispersive or anisotropic media that closely mimic real-world conditions and extending the application to various imaging techniques involving objective function minimization.

The inspection and monitoring of structural conditions are crucial for the maintenance of semi-rigid base pavement. To achieve the inverse calculation of material parameters and obtain the mechanical response of asphalt pavement, a method of modulus correction by reducing the error between tested and simulated strains was first developed. The relationship between the temperature at various depths within the pavement structure and atmospheric temperature was effectively demonstrated using a dual sinusoidal regression model. Subsequently, pavement monitoring data illustrated that as loading weight and temperature increased and loading speed decreased, the three-way strain of the asphalt layer increased. Thus, the relationship model between loading conditions and three-way strain was established with a good fitting degree (R2 > 0.95). The corrected modulus was obtained by approximating the error between simulated and measured strains. Then, the finite element analysis was performed to calculate key mechanical index values under various working conditions and predict the fatigue life of asphalt and base layers. Finally, ground-penetrating radar (GPR) detection was performed, and the internal pavement condition index was defined for quantitative assessment of structure conditions. The results show that there is a good correlation between the internal pavement condition index (IPCI) and remaining life of pavement structure. Therefore, our works solve the problems of the parameter reliability of pavement structures and quantitative assessment for structural conditions, which could support the performance prediction and maintenance analysis on asphalt pavement with a semi-rigid base.

Frequency-domain electromagnetic induction (EMI) methods are commonly used to map vast areas quickly and with minimum logistical efforts. Unfortunately, they are often characterized by a very limited number of frequencies and severe ill-posedness. On the other hand, electrical resistivity tomography (ERT) approaches are usually considered more reliable; for example, they do not require specific calibration procedures and can be easily inverted in 2D/3D. However, ERT surveys are, by far, more demanding and time consuming, allowing for the deployment of a few acquisition lines per day. Ideally, the optimal would be to have the advantages of both approaches: ease of acquisition while keeping robustness and reliability. The present work raises from the necessity to cope with this issue and from the importance of enforcing realistic constraints to the data inversion without being limited to (over)simplistic spatial constraints (for example, characterizing the smooth and/or sharp regularization). Accordingly, the present research demonstrates, by means of synthetic and field data, how the EMI inversion—based on realistic prior models—can be further enhanced by incorporating additional pre-existing pieces of information. While the proposed scheme is quite general, in the specific examples discussed here, these additional pieces of information are, respectively, a reference model along a line across the survey area, and an ERT section. The field EMI results were verified against extensive ground penetrating radar (GPR) measurements and boreholes.

With global warming, Arctic sea ice, as one of the important factors regulating climate, has put forward new requirements for research. At present, the ground penetrating radar (GPR) is a powerful tool to obtain the structure of Arctic sea ice. Traditional offset imaging techniques no longer meet research requirements, and the two-parameter full waveform inversion (FWI) method has received widespread attention. To solve the high nonlinearity and ill-posed problem of FWI, the L-BFGS optimization algorithm and Wolfe criterion of inexact line search were used to update the model. The parameter scale factor, multiscale inversion strategy, and total variation (TV) regularization were introduced to optimize the inversion results. Finally, the inversion of anomalous bodies with different scales and different physical parameters is carried out, which verifies the reliability of the proposed method for dual-parameter imaging of Arctic sea ice and provides a powerful tool for the study of Arctic sea ice.

Industrial hemp cultivation has the potential to be an environmentally friendly and highly sustainable crop and it can fit well in crop rotation practices to increase soil fertility. For this study, two commercial varieties of industrial hemp with low tetrahydrocannabinol (THC) content were used to test its reintroduction chance in the study area and to evaluate its response in terms of yield with respect to the soil and drought conditions of the area. During the vegetative period, non-invasive measures of the soil’s water status were performed using Watermark probes and ground penetrating radar. In addition, hemp crops vigour monitoring was performed by means of Sentinel 2 multispectral optical remote sensing data. In the absence of precipitation and/or irrigation, and with high consumption of soil water by the hemp crop due to evapotranspiration, the crop has completed its cycle thanks to its resistance to water stress conditions. From the soil water and satellite monitoring results, there is a good agreement with the field results in terms of water stress and its effects on crop vigour. This study contributes to a better understanding of the possibility of hemp crop reintroduction in areas where water deficit occurs, which could open up the opportunity for selecting hemp crop cultivars that can be grown under different agro-ecological conditions and are also of great commercial interest for decision makers involved in sustainable crop management and in the reduction of fertilizers and pollutants released into the environment.

For the investigation of moisture and salt content in historic masonry, destructive drilling samples followed by a gravimetric investigation is still the preferred method. In order to prevent the destructive intrusion into the building substance and to enable a large-area measurement, a nondestructive and easy-to-use measuring principle is needed. Previous systems for moisture measurement usually fail due to a strong dependence on contained salts. In this work, a ground penetrating radar (GPR) system was used to determine the frequency-dependent complex permittivity in the range between 1 and 3 GHz on salt-loaded samples of historical building materials. By choosing this frequency range, it was possible to determine the moisture in the samples independently of the salt content. In addition, it was possible to make a quantitative statement about the salt level. The applied method demonstrates that with ground penetrating radar measurements in the frequency range selected here, a salt-independent moisture determination can be carried out.

This paper presents the design of a high-voltage pulse-based radar and a supervised data processing method for soil moisture estimation. The goal of this research was to design a pulse-based radar to detect changes in soil moisture using a cross-hole approach. The pulse-based radar with three transmitting antennas was placed into a 12 m deep hole, and a receiver with three receive antennas was placed into a different hole separated by 100 m from the transmitter. The pulse generator was based on a Marx generator with an LC filter, and for the receiver, the high-frequency data acquisition card was used, which can acquire signals using 3 Gigabytes per second. Used borehole antennas were designed to operate in the wide frequency band to ensure signal propagation through the soil. A deep regression convolutional network is proposed in this paper to estimate volumetric soil moisture using time-sampled signals. A regression convolutional network is extended to three dimensions to model changes in wave propagation between the transmitted and received signals. The training dataset was acquired during the period of 73 days of acquisition between two boreholes separated by 100 m. The soil moisture measurements were acquired at three points 25 m apart to provide ground truth data. Additionally, water was poured into several specially prepared boreholes between transmitter and receiver antennas to acquire additional dataset for training, validation, and testing of convolutional neural networks. Experimental results showed that the proposed system is able to detect changes in the volumetric soil moisture using Tx and Rx antennas.

In order to solve the current problems that conventional video inspection can only detect, as an internal pipeline defect and drainage pipeline radar inspection device detects in a single direction and at radar frequency in water pipeline defect detection, a three-channel drainage pipeline ground penetrating radar (GPR) inspection device was designed and developed, the assembly and commissioning of the device prototype were completed, and an actual engineering test application was carried out. Focusing on the problem that the detection direction and depth of the single-channel detection device are limited, a three-channel drainage pipeline GPR inspection device is designed to realize the synchronous detection of the inside of the pipeline, the pipeline body, and the external environment of the pipeline, improving the detection depth and efficiency. According to the design scheme of the three-channel drainage pipeline GPR inspection device, the assembly of the device prototype was completed. The device contains three radar channels, the top of the main frequency of the antenna is 1.4 GHz, the two sides are 750 MHz, the video camera has a pixel count of 4 million, and the positioning accuracy is less than 1 mm, the waterproof grade is IP68, the detection accuracy of pipe deformation (slope) is 0.1°, the detection depth outside the pipe is 1.2 m, and the detection accuracy of corrosion thickness is 15 mm. In a practical application of the device, the Jianguomenqiao sewage pipeline in Beijing, China, was tested, resulting in the discovery of 87 defects, including 39 loose soil areas at the bottom of the pipe exterior, 40 void areas, and 8 cavities.

We deployed field-based high-throughput phenotyping (HTP) techniques to acquire trait data for a subset of a peanut chromosome segment substitution line (CSSL) population. Sensors mounted on an unmanned aerial vehicle (UAV) were used to derive various vegetative indices as well as canopy temperatures. A combination of aerial imaging and manual scoring showed that CSSL 100, CSSL 84, CSSL 111, and CSSL 15 had remarkably low tomato spotted wilt virus (TSWV) incidence, a devastating disease in South Georgia, USA. The four lines also performed well under leaf spot pressure. The vegetative indices showed strong correlations of up to 0.94 with visual disease scores, indicating that aerial phenotyping is a reliable way of selecting under disease pressure. Since the yield components of peanut are below the soil surface, we deployed ground penetrating radar (GPR) technology to detect pods non-destructively. Moderate correlations of up to 0.5 between pod weight and data acquired from GPR signals were observed. Both the manually acquired pod data and GPR variables highlighted the three lines, CSSL 84, CSSL 100, and CSSL 111, as the best-performing lines, with pod weights comparable to the cultivated check Tifguard. Through the combined application of manual and HTP techniques, this study reinforces the premise that chromosome segments from peanut wild relatives may be a potential source of valuable agronomic traits.

Archeological prospection and 3D reconstruction are increasingly combined in large archeological projects that serve both site investigation and dissemination of results. This paper describes and validates a method for using multispectral imagery captured by unmanned aerial vehicles (UAVs), subsurface geophysical surveys, and stratigraphic excavations to evaluate the role of 3D semantic visualizations for the collected data. The information recorded by various methods will be experimentally reconciled using the Extended Matrix and other original open-source tools, keeping both the scientific processes that generated them and the derived data separate, transparent, and reproducible. This structured information makes immediately accessible the required variety of sources useful for interpretation and reconstructive hypotheses. The application of the methodology will use the first available data from a five-year multidisciplinary investigation project at Tres Tabernae, a Roman site near Rome, where numerous non-destructive technologies, as well as excavation campaigns, will be progressively deployed to explore the site and validate the approaches.

Stratigraphy is a fundamental classification tool for archaeology on which modern excavation techniques are based, and essentially consists of a sedimentological, pedological and archaeological interpretation of the multiple cultural layers found while digging; this concept can be adopted when studying monumental buildings and, in particular, their hidden parts or elements. The precious and delicate surfaces of monuments need non-invasive techniques such as geophysical methods and in the present article, the use of GPR technique has been exploited through a dataset collected over the nave of the church of San Leonardo de Siete Fuentes in Sardinia. First, the georadar results have been jointly analyzed by means of the B- and C-scans, in which some most significant patterns were detected and analyzed by looking at their signal features over the investigated volume. Following the analysis, elements from the signal attribute analysis and horizon detection and visualization, with a 3D approach, were used. To strengthen the reliability of the GPR results, a thermal infrared survey was simultaneously carried out. Thanks to the integrated geophysical and historical analysis of the monument, the ancient layout of the church has been reconstructed and other targets of potential archaeological interest identified

The three-dimensional (3D) ground-penetrating radar (GPR) has been widely applied in subsurface surveys and imaging, and the quality of the resulting C-scan images is determined by the spatial resolution and visualisation contrast. Previous studies have standardised the suitable spatial resolution of GPR C-scans; however, their measurement normalisation remains arbitrary. Human bias is inevitable in C-scan interpretation because different visualisation algorithms lead to different interpretation results. Therefore, an objective scheme for mapping GPR signals after standard processing to the visualisation contrast should be established. Focusing on two typical scenarios, a reinforced concrete structure and an urban underground, this study illustrated that the essential parameters were greyscale thresholding and transformation mapping. By quantifying the normalisation performance with the integration of image segmentation and structural similarity index measure, a greyscale threshold was developed in which the normalised standard deviation of the unit intensity of any surveyed object was two. A transformation function named “bipolar” was also shown to balance the maintenance of real reflections at the target objects. By providing academia/industry with an object-based approach, this study contributes to solving the final unresolved issue of 3D GPR imaging (i.e., image contrast) to better eliminate the interfering noise and better mitigate human bias for any one-off/touch-based imaging and temporal change detection.

Determining the material properties and existing capacity of concrete infrastructure using nondestructive techniques is challenging due to evolving design requirements, unknown as-built conditions, and ongoing maintenance and deterioration. Concrete’s material properties, including density, porosity, and compressive strength, are usually determined by mechanical testing, but being able to measure these properties noninvasively could aid engineers in maintaining and designing concrete infrastructure. Research into nondestructive methods for determining material properties of concrete has shown relationships between mechanical properties and ground penetrating radar (GPR) properties such as dielectric constant, attenuation, and instantaneous amplitude. We investigated direct relationships between dielectric constant and the density, porosity, and compressive strength of 23 mature concrete samples with varying mix designs using a commercial 1 GHz GPR. In normal-weight concrete, weak trends were seen between a dielectric for compressive strength (R2=0.76) and one for density (R2=0.64), whereas no significant trend was found with porosity (R2=0.52). The GPR unit used provides acceptable data but has limited resolution for analyses and utility. The dielectrics showed distinct clustering by mix type—particularly the inclusion of materials such as blast furnace slag. While demonstrating that the dielectric constant is a candidate for rapid concrete comparisons, there is also a demonstrated need for further investigation of the complex relationships between mechanical and electromagnetic properties in concrete.

The necropolis of El Toro is characterised as a space of prolonged use in northern Oretania. Several important archaeological finds were made in 1975 and 2012, leading to the excavation of six test pits in 2017. Based on the existing legacy data, an extension of the state of knowledge was carried out by combining several geophysical tools. The geophysical tools chosen for this sample consist of a combination of data from two different georadar systems, to which data from a magnetometer survey is added. A series of post-processes are applied to the preliminary results to improve the visualisation and interpretation of the data. The combination of these techniques used at the site is an improvement that helps us to understand these spaces and their interaction with the historical landscape of La Mancha.

High-resolution topographic and stratigraphic datasets have been increasing applied in active fault investigation and seismic hazard assessment. There is a need for the comprehensive analysis of active faults on the basis of the correlating geomorphologic features and stratigraphic data. The integration of TLS and GPR was adopted to characterize the 3D geometry of the fault on the Maoyaba segment of Litang fault. The TLS was used to obtain the high-resolution topographic data for establishing the 3D surficial model of the fault. The 2D 250 MHz and 500 MHz GPR profiles were carried out to image the shallow geometry of the fault along four survey lines. In addition, the 3D GPR survey was performed by ten 2D 500 MHz GPR profiles with 1 m spacing. From the 2D and 3D GPR results, a wedge-shaped deformation zone of the electromagnetic wave was clearly found on the GPR profiles, and it was considered to be the main fault zone with a small graben structure. Three faults were identified on the main fault zone, and fault F1 and F3 were the boundary faults, while the fault F2 was the secondary fault. The subsurface geometry of the fault on the GPR interpreted results is consistent with the geomorphologic features of the TLS-derived data, and it indicates that the Maoyaba fault is a typical, normal fault. For reducing the environmental disruption and economic losses, GPR was the most optimal method for detecting the subsurface structures of active faults in the Litang fault with a non-destructive and cost-effective fashion. The 3D surface and subsurface geometry of the fault was interpreted from the integrated data of TLS and GPR. The fusion data also offers the chance for the subsurface structures of active faults on the GPR profiles to be better understood with its corresponding superficial features. The study results demonstrate that the integration of TLS and GPR has the capability to obtain the high-resolution micro geomorphology and shallow geometry of active faults on the Maoyaba segment of the Litang fault, and it also provides a future prospect for the integration of TLS and GPR, and is valuable for active fault investigation and seismic hazard assessment, especially in the Qinghai-Tibet Plateau area.

Over the recent period, there has been an increasing interest in the use of pulsed infrared thermography (PT) for the non-destructive evaluation of Cultural Heritage (CH). Unlike other techniques that are commonly employed in the same field, PT enables the depth-resolved detection of different kinds of subsurface features, thus providing helpful information for both scholars and restorers. Due to this reason, several research activities are currently underway to further improve the PT effectiveness. In this manuscript, the specific use of PT for the analysis of three different types of CH, namely documentary materials, panel paintings–marquetery, and mosaics, will be reviewed. In the latter case, i.e., mosaics, passive thermography combined with ground penetrating radar (GPR) and digital microscopy (DM) have also been deepened, considering their suitability in the open field. Such items have been selected because they are characterized by quite distinct physical and structural properties and, therefore, different PT (and, in some cases, verification) approaches have been employed for their investigations.

Railway Tunnel SubSurface Inspection (RTSSI) is essential for targeted structural maintenance. ‘Effective’ detection, localisation and characterisation of fully concealed features (i.e., assets, defects) is the primary challenge faced by RTSSI engineers, particularly in historic masonry tunnels. Clear conveyance and communication of gathered information to end-users poses the less frequently considered secondary challenge. The purpose of this review is to establish the current state of the art in RTSSI data acquisition and information conveyance schemes, in turn formalising exactly what constitutes an ‘effective’ RTSSI visualisation framework. From this knowledge gaps, trends in leading RTSSI research and opportunities for future development are explored. Literary analysis of over 300 resources (identified using the 360-degree search method) informs data acquisition system operation principles, common strengths and limitations, alongside leading studies and commercial tools. Similar rigor is adopted to appraise leading information conveyance schemes. This provides a comprehensive whilst critical review of present research and future development opportunities within the field. This review highlights common shortcomings shared by multiple methods for RTSSI, which are used to formulate robust criteria for a contextually ‘effective’ visualisation framework. Although no current process is deemed fully effective; a feasible hybridised framework capable of meeting all stipulated criteria is proposed based on identified future research avenues. Scope for novel analysis of helical point cloud subsurface datasets obtained by a new rotating ground penetrating radar antenna is of notable interest.

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

Unmanned aerial vehicle (UAV) ground-penetrating radar (GPR) is an important research topic for target detection in many fields. In this paper, we develop a UAV-mounted GPR system with a frequency band at 150 MHz–309 MHz. However, the received signal in the complex background is covered by various clutter and interference, leading to the serious obscuring of the target. To meet this challenge, a cross-correlation-based background subtraction (CCBS) method and an interference suppression technique are adopted in combination for more accurate detection. The CCBS method processes the raw echo by establishing a background-removal model and using the similarity between each A−Scan and a reference wave. In addition, a Butterworth filter is adopted to get rid of the active electromagnetic interference beyond the working frequencies of the system; then, a lateral Doppler filtering (LDF) technique is introduced to suppress the passive interference generated by the rotation of the UAV rotor itself. Moreover, a practical method for estimating the dielectric constant is introduced by the calibration process of the measured radar echo. Numerical simulations and experimental results by our UAV-GPR system demonstrate that the proposed method has presented a better performance than the traditional methods, and the system has great potential in detecting deeply buried targets.

This paper describes the results obtained using an archaeogeophysical-based approach for discovering new Roman structures belonging to the ancient settlement of Forentum, currently identifiable by a well-preserved sanctuary from the third century BC. The investigated area has been affected by invasive anthropic activities that have partially damaged the Roman structures. Extensive geophysical measurements, including detailed ground-penetrating radar investigations supported by magnetometric data, have allowed for the identification of an impressive complex of structures composed of various buildings. Magnetometric and electromagnetic anomalies suggest the existence of an “urban” dimension close to the Gravetta Sanctuary, totally unearthed and unknown until now, organized into regular patterns in a similar way to the most famous site in the vicinity of Bantia, or the famous Apulian archaeological sites of Ordona and Arpi.

The Borre Monitoring Project investigated how environmental factors, in particular, precipitation and soil moisture variation as well as different soil and sediment types, affect the quality of GPR data collected for archaeological purposes. To study these questions, regular GPR surveys were conducted over a period of 14 months across a test area covering a hall building at the Iron and Viking Age site of Borre in Norway. In order to obtain in situ measurements of environmental factors relevant for electromagnetic wave propagation including volumetric water content, bulk electrical conductivity, ground temperature, and precipitation, three monitoring stations were erected at the test site. Soil and sediment samples taken from the profiles at the respective monitoring stations were analysed to gain a basic description of their physical and chemical properties. Twelve GPR surveys were conducted roughly once a month between August 2016 and September 2017 and the results clearly indicated differences in the quality of the data collected. To better understand the underlying causes for this variation, GPR data were compared against and integrated with the in situ measurements gathered using the monitoring stations. The results of this analysis emphasised the benefit of dry conditions, which, if prevailing over a longer period of time, proved to generate GPR data of the highest quality. Seasonality could not be attested; instead, data quality was governed by small-scale weather patterns, where the time and intensity of rainfall events prior to the surveys as well as sudden changes in air temperature played a decisive role. While the results of this study are only valid for sites with similar settings such as Borre, they emphasise the importance of considering the environmental factors during all stages of a GPR survey and highlight the need for further studies investigating other settings.

Ground penetrating radar (GPR) is a well-established technique used in archaeological prospection and it requires a number of specialized routines for signal and image processing to enhance the data acquired and lead towards a better interpretation of them. Computer-aided techniques have advanced the interpretation of GPR data, dealing with a wide range of operations aiming towards locating, imaging, and diagnosis/interpretation. This article will discuss the novel and recent applications of machine learning (ML) and deep learning (DL) techniques, under the artificial intelligence umbrella, for processing GPR measurements within archaeological contexts, and their potential, limitations, and possible future prospects.

An ultrawide bandwidth (UWB) antenna for ground-penetrating radar (GPR) applications is designed to check soil moisture and provide good-quality images of metallic targets hidden in the soil. GPR is a promising technology for detecting and identifying buried objects, such as landmines, and investigating soil in terms of moisture content and contamination. A paddle-shaped microstrip antenna is created by cutting a rectangular patch at one of its diametrical edges fed by the coplanar waveguide technique. The antenna is loaded by stubs, shorting pins, and a split-ring resonator (SRR) metamaterial structure to increase the antenna’s gain and enhance the bandwidth (BW) towards both the lower and higher end of the working BW. The antenna’s performance in soil inspection is studied in terms of the operating frequency range, different types of soil, different distances (e.g., 50 cm) between the antenna arrays and soil, S-parameters, and gain. Following this, the antenna’s ability to find a metallic target in the soil is tested, considering different array numbers, multi-targets, and locations. The antenna is designed on a thin layer of economic polytetrafluoroethylene (PTFE) substrate with dimensions 50 × 39 × 0.508 mm3 and works in the frequency range 1.9–9.2 GHz. In addition, two more resonances at 0.9 and 1.8 GHz are also achieved; hence, the antenna works for more than two application bands, such as the ISM- and L-bands. The measurement results validated excellent agreement with the simulated results. Furthermore, the recommended antenna offering a high gain of about 10.8 dBi and maximum efficiency above 97% proved able to discriminate between hidden objects and even recognize their shapes. Moreover, the reconstructed images show that the antenna can detect an object in the soil at any location.

It is critical to estimate and eliminate the wavelets of ground penetrating radar (GPR), so as to optimally compensate the energy attenuation and phase distortion. This paper presents a new wavelet extraction method based on a two-layer Long Short-Term Memory (LSTM) network. It only uses several random A-scan echoes (i.e., single channel detection echo sequence) to accurately predict the wavelet of any scene. The layered detection scenes with objects buried in different region are set for the 3D Finite-Difference Time-Domain simulator to generate radar echoes as a dataset. Additionally, the simulation echoes of different scenes are used to test the performance of the neural network. Multiple experiments indicate that the trained network can directly predict the wavelets quickly and accurately, although the simulation environment becomes quite different. Moreover, the measured data collected by the Qingdao Radio Research Institute radar and the unmanned aerial vehicle ground penetrating radar are used for test. The predicted wavelets can perfectly offset the original data. Therefore, the presented LSTM network can effectively predict the wavelets and their tailing oscillations for different detection scenes. The LSTM network has obvious advantages compared with other wavelet extraction methods in practical engineering.

In this study, the degree of corrosion of steel reinforcement is compared to the reflected voltage of electromagnetic waves and the ASTM C876 specification. This study conducted some tests on steel bars with different degrees of corrosion by transmitting electromagnetic waves in the reinforced concrete. In the test, a corrosion potentiometer was used to analyze and compare the experimental results. The electromagnetic wave reflection signals from the image generated by the ground penetrating radar were used to capture the different media in the concrete components. The reflection coefficient method was used to analyze the calculated relative dielectric constant of the media and to obtain the reflection energy and phase changes on the medium interface. We compared and discussed the corrosion potential and the reflected voltage from the corroded steel bars in the reinforced concrete. The reflected voltage analysis of the ground penetrating radar showed that the average corrosion potential on the corroded plate on the 3rd floor was −280 m V (Area C). According to ASTM C876, the steel bars in the concrete were moderately corroded. The reflected voltage analysis of the electromagnetic waves concluded that areas A and B were moderately corroded, which is consistent with the conclusion from ASTM C876. Using the innovative method, this study has established a reference standard for the degree of corrosion of steel bars based on ASTM C876 and has calculated the quantitative state of corroded steel bars. The variations of the electromagnetic wave reflected voltage of the ground penetrating radar can mark the changes in the corrosion interface of concrete and steel reinforcement with different degrees of corrosion and different thicknesses of the protective layer.

The non-invasive detection and digital documentation of buried archaeological heritage by means of geophysical prospection is increasingly gaining importance in modern field archaeology and archaeological heritage management. It frequently provides the detailed information required for heritage protection or targeted further archaeological research. High-resolution magnetometry and ground-penetrating radar (GPR) became invaluable tools for the efficient and comprehensive non-invasive exploration of complete archaeological sites and archaeological landscapes. The analysis and detailed archaeological interpretation of the resulting large 2D and 3D datasets, and related data from aerial archaeology or airborne remote sensing, etc., is a time-consuming and complex process, which requires the integration of all data at hand, respective three-dimensional imagination, and a broad understanding of the archaeological problem; therefore, informative 3D visualizations supporting the exploration of complex 3D datasets and supporting the interpretative process are in great demand. This paper presents a novel integrated 3D GPR interpretation approach, centered around the flexible 3D visualization of heterogeneous data, which supports conjoint visualization of scenes composed of GPR volumes, 2D prospection imagery, and 3D interpretative models. We found that the flexible visual combination of the original 3D GPR datasets and images derived from the data applying post-processing techniques inspired by medical image analysis and seismic data processing contribute to the perceptibility of archaeologically relevant features and their respective context within a stratified volume. Moreover, such visualizations support the interpreting archaeologists in their development of a deeper understanding of the complex datasets as a starting point for and throughout the implemented interactive interpretative process.

Currently, ground penetrating radar is the major technology for the detection of urban road collapses and disaster sources. Vehicle-mounted GPR collects tens of GB of data on site every day, but the present interpretation of abnormal regions detected by radar relies on manual interpretation with low process efficiency. The abnormal region images of GPR are different from the surrounding normal images. In terms of the features of abnormal regions in GPR images with an obvious brightness change and obvious directional characteristics, an abnormal region detection algorithm based on visual attention mechanism is proposed. Firstly, the complex background noise in the GPR images is suppressed by wavelet denoising and gamma transform, and the brightness and directional characteristics of the abnormal regions are enhanced. Secondly, by building a multi-scale image brightness and orientation feature pyramid model, the features of abnormal regions of interest are continuously enhanced, and the rapid screening of abnormal regions has been achieved. The effectiveness of the algorithm has been verified by actual tests on different types of abnormal radar image data.

In the past 20 years, many studies have been performed on ballast layer inspection and condition evaluation with ground penetrating radar (GPR). GPR is a non-destructive means that can reflect the ballast layer condition (fouling, moisture) by analysing the received signal variation. Even though GPR detection/inspection for ballast layers has become mature, some challenges still need to be stressed and solved, e.g., GPR indicator (for reflecting fouling level) development, quantitative evaluation for ballast fouling levels under diverse field conditions, rapid GPR inspection, and combining analysis of GPR results with other data (e.g., track stiffness, rail acceleration, etc.). Therefore, this paper summarised earlier studies on GPR application for ballast layer condition evaluation. How the GPR was used in the earlier studies was classified and discussed. In addition, how to correlate GPR results with ballast fouling level was also examined. Based on the summary, future developments can be seen, which is helpful for supplementing standards of ballast layer evaluation and maintenance.