Search Results (726)

In recent years, digital technologies have become increasingly prevalent in the field of heritage protection. In addition to geomatic techniques like laser scanning (LiDAR) and Structure-from-Motion (SfM), geophysical methods, especially Ground-Penetrating Radar (GPR), offer added value for investigating protected buildings and objects. Additionally, chemical analysis (e.g., X-ray fluorescence, XRF) and mineral magnetic methods can be utilized to investigate specific research topics. All these methods are completely non-invasive and leave the heritage site untouched. Furthermore, they are cost-efficient and fast to use. Within this paper, we want to present an integrated study of a medieval sarcophagus in Bamberg Cathedral. The geophysical surveys via GPR and magnetic susceptibility (MS) measurements should answer open questions regarding the construction and internal layout of the sandstone sarcophagus, dated to the Early or High Middle Ages. The susceptibility data indicated an inner lead coffin in the lower part behind the stone slabs due to an unusual diamagnetic response in these parts. In contrast, the GPR data gave no such indication and revealed that the interior is too small for a direct burial of the bishop. Hence, an additional XRF survey was conducted to help solve this contradiction. The latter data indicate that the lead could be due to remains of a former painting on the sarcophagus with colours containing lead white pigments. Due to the porous sandstone, the moist environmental conditions, and the high weight of the lead elements, these could have accumulated at the bottom of the sarcophagus, creating the diamagnetism detected by the magnetic susceptibility measurements. Full article

Compact antennas with ultra-wideband operation and stable radiation are essential for portable and airborne ground-penetrating radar (GPR), yet miniaturization in the sub 3 GHz region is strongly constrained by the wavelength-driven aperture requirement and often leads to impedance discontinuity and radiation instability. This paper presents a compact aperture-slot antipodal Vivaldi antenna (AS-AVA) designed under a radiation stability-driven co-design strategy, where the miniaturization features are organized along the energy propagation path from the feed to the flared aperture. The proposed structure combines (i) aperture-slot current-path engineering with controlled meandering to extend the low-frequency edge, (ii) four tilted rectangular slots near the aperture to restrain excessive edge currents and suppress sidelobes, and (iii) back-loaded parasitic patches for coupling-based impedance refinement to eliminate residual mismatch pockets. A fabricated prototype on FR-4 (thickness 1.93 mm) occupies $111.15\times 156.82$ mm² and achieves a measured $S_{11}$ below $-10$ dB from 0.63 to 2.03 GHz (fractional bandwidth 105.26%). The measured realized gain increases from 2.1 to 7.5 dBi across the operating band, with stable far-field radiation patterns; the group delay measured over 0.6–2.1 GHz remains within 4–8 ns, indicating good time-domain fidelity for stepped-frequency continuous-wave (SFCW) operation. Finally, the antenna pair is integrated into an SFCW-GPR testbed and validated in sandbox and outdoor experiments, where buried metallic targets and a subgrade void produce clear B-scan signatures after standard processing. These results confirm that the proposed AS-AVA provides a practical trade-off among miniaturization, broadband matching, and radiation robustness for compact sub 3 GHz GPR platforms. Full article

Diffraction-based velocity analysis is a key data interpretation technique in geophysical exploration, typically relying on the geometric characteristics, energy distribution, or propagation paths of diffraction waves. The hyperbola-based method is a classical strategy in this category, which extracts depth-dependent velocity (or dielectric properties) by correlating the hyperbolic shape of diffraction events with subsurface parameters for characterizing subsurface structures and material compositions. In this study, we propose a layer-stripping velocity analysis method applicable to ground-penetrating radar (GPR) and lunar-penetrating radar (LPR) data, with two main innovations: (1) replacing traditional local optimization algorithms with an intuitive parallelism check scheme, eliminating the need for complex nonlinear iterations; (2) performing depth-progressive velocity scanning of radargram diffraction signals, where shallow-layer velocity analysis constrains deeper-layer calculations. This strategy avoids misinterpretations of deep geological objects’ burial depth, morphology, and physical properties caused by a single average velocity or independent deep-layer velocity assumptions. The workflow of the proposed method is first demonstrated using a synthetic rock-fragment layered model, then applied to derive the near-surface dielectric constant distribution (down to 27 m) at the Chang’e-4 landing site. The estimated values range from 2.55 to 6, with the depth-dependent profile revealing lunar regolith stratification and interlayer material property variations. Consistent with previously reported results for the Chang’e-4 region, our findings confirm the method’s applicability to LPR data, providing a new technical framework for high-resolution subsurface structure reconstruction. Full article

The present work addresses the critical challenge of designing a lightweight antenna suitable for remote sensing applications specifically aimed at the identification of buried objects from Unmanned Aerial Vehicles (UAVs). The stability of the phase center and the radiation pattern are critical factors for enabling synthetic aperture radar (SAR) processing on moving platforms. The presented antenna structure is characterized by a simple, lightweight geometry, and allows for achieving a fractional bandwidth of nearly 100% with an excellent stability of the radiation pattern, that exhibits minimal variation within the operating band of the antenna. Specifically, the gain is in the range 4.4–6.3 dBi and the group delay spread is about 200 ps in the frequency range 1–2 GHz. We illustrate numerical simulations and measurements of an antenna prototype that validate the proposed approach, demonstrating the suitability of the design for the intended operational scenario. Full article

Single-frequency ground penetrating radar (GPR) systems are fundamentally constrained by a trade-off between penetration depth and resolution, alongside issues like narrow bandwidth and ringing interference. To break this limitation, we have developed a multi-frequency data fusion technique grounded in convolutional sparse representation (CSR). The proposed methodology involves spatially registering multi-frequency GPR signals and fusing them via a CSR framework, where the convolutional dictionaries are derived from simulated high-definition GPR data. Extensive evaluation using information entropy, average gradient, mutual information, and visual information fidelity demonstrates the superiority of our method over traditional fusion approaches (e.g., weighted average, PCA, 2D wavelets). Tests on simulated and real data confirm that our CSR-based fusion successfully synergizes the deep penetration of low frequencies with the fine resolution of high frequencies, leading to substantial gains in GPR image clarity and interpretability. Full article

The analysis of ground-penetrating radar data generally relies on the visual identification of structures on selected profiles and their interpretation in terms of buried features. In simple cases, inverse modelling of the acquired data set can facilitate interpretation and reduce subjectivity. These methods suffer from severe restrictions due to antenna resolution limits, which prevent the identification of tiny structures, particularly in forensic, stratigraphic, and engineering applications. Here, we describe a technique to obtain a high-resolution characterization of the underground, based on the forward modelling of individual traces (A-scans) of selected radar profiles. The model traces are built by superposition of Ricker wavelets with different polarities, amplitudes, and arrival times and are used to create reflectivity diagrams that plot reflection amplitudes and polarities versus depth. A thin bed is defined as a layer of higher or lower permittivity relative to the surrounding material, such that the top and bottom reflections are subject to constructive interference, determining the formation of an anomalous peak in the trace (tuning effect). The proposed method allows the detection of ultra-thin layers, well beyond the Rayleigh vertical resolution of GPR antennas. This approach requires a preliminary estimation of the instrumental uncertainty of common monostatic antennas and takes into account the frequency-dependent attenuation, which causes a spectral shift of the dominant frequency acquired by the receiver antenna. Such a quantitative approach to analyzing radar data can be used in several applications, notably in stratigraphic, forensic, paleontological, civil engineering, heritage protection, and soil stratigraphy applications. Full article

This study presents the application of ground-penetrating radar (GPR) in the investigation of historical metal ore mining sites in the Lower Silesia region of Poland. The paper outlines the principles of the GPR method and details the measurement procedures used during fieldwork. GPR has proven to be an effective, non-invasive tool for identifying inaccessible or previously unknown underground mining structures, such as shafts, tunnels, and remnants of mining infrastructure. This capability is particularly valuable in the context of extensive and complex post-mining landscapes characteristic of Lower Silesia. The research presents findings from selected sites, demonstrating how GPR surveys facilitated the detection and subsequent archaeological exploration of historical workings. In several cases, the method enabled the recovery of access to underground features, which were then subjected to detailed documentation and preservation efforts. Following necessary safety and adaptation measures, some of these sites have been successfully opened to the public as part of regional tourism initiatives. The study confirms the utility of GPR as a key instrument in post-mining archaeology and mining heritage conservation, offering a rapid and reliable means of mapping subsurface structures without disturbing the terrain. Full article

The detection of underground cavities and dissolution features is a critical component in assessing geohazards within karst terrains, particularly where natural processes interact with long-term human occupation. This study investigates two contrasting sites in the Sefrou region of northern Morocco: Binna, a rural travertine-dolomite system shaped by Quaternary karstification, and the urban Old Medina of Bhalil, where traditional cave dwellings are carved into carbonate formations. A combined geophysical and geological approach was applied to characterize subsurface heterogeneities and assess the extent of near-surface void development. Vertical electrical soundings (VES) at Binna site delineated high-resistivity anomalies consistent with air-filled cavities, dissolution conduits, and brecciated limestone horizons, all indicative of an active karst system. In the Bhalil old Medina site, ground-penetrating radar (GPR) with low-frequency antennas revealed strong reflection contrasts and localized signal attenuation zones corresponding to shallow natural cavities and potential anthropogenic excavations beneath densely constructed areas. Geological observations, including lithostratigraphic logging and structural cross-sections, provided additional constraints on cavity geometry, depth, and spatial distribution. The integrated results highlight a high degree of subsurface karstification across both sites and underscore the associated geotechnical risks for infrastructure, cultural heritage, and land-use stability. This work demonstrates the value of combining electrical and radar methods with geological analysis for mapping hazardous subsurface voids in cavity-prone Quaternary landscapes, offering essential insights for risk mitigation and sustainable urban and rural planning. Full article

After the completion of open-pit coal mining, land reclamation is implemented to restore the disturbed eco–hydrological system, for which accurate soil moisture characterization is essential. We evaluated the feasibility and performance of an Auto-Regressive Moving Average (ARMA)-based ground-penetrating radar (GPR) inversion scheme for estimating soil moisture in a reclaimed mine area. GPR data were acquired over a reconstructed three-layer soil profile in a reclaimed open-pit coal mine, and soil moisture content was independently determined using the oven-drying method on core samples. An ARMA model was used to describe the relationship between the GPR reflections and soil electromagnetic properties and to invert the vertical distribution of soil moisture. The ARMA-derived GPR estimates reproduced the measured moisture profile well within the depth interval of 1.4–3.0 m and revealed the clear vertical zonation of soil moisture associated with the engineered layering. Correlation coefficients between the ARMA-inverted GPR estimates and oven-drying measurements ranged from 0.64–0.78 for 0–1.4 m, 0.84–0.93 for 1.4–2.2 m, and 0.98–0.99 for 2.2–3.0 m, indicating that inversion accuracy improves systematically with depth. These results demonstrate that ARMA-based GPR inversion provides a reliable and non-destructive approach for quantifying soil moisture in reclaimed mine soils and offers practical support for monitoring and assessing the effectiveness of reclamation in open-pit coal mining areas. Full article

In this paper, the combined use of Ground Penetrating Radar (GPR) and a Terrestrial Laser Scanner (TLS) is illustrated to highlight multiple advantages arising from the integration of these two distinct Non-Destructive Testing (NDT) techniques in the investigation of a historical wall. In particular, thanks to the TLS point cloud, a precise evaluation of the medium’s thickness, as well as its irregularities, was carried out. Based on this accurate geometrical constraint, a first-order velocity model, to be used for a time-to-depth conversion and for a post-stack GPR data migration, was computed. Moreover, a joint visualization of both datasets (GPR and TLS) was achieved in a novel tridimensional workspace. This solution provided a more straightforward and efficient way of testing the reliability of the combined results, proving the efficiency of the proposed method in the estimation of a velocity model, especially in comparison to conventional GPR methods. This demonstrates how the integration of different remote sensing methodologies can yield a more solid interpretation, taking into account the uncertainties related to the geometrical irregularities of the external wall’s surface and the inner structure generating complex GPR signatures. Full article

The detection of subsurface stromatolites remains challenging due to their complex morphology and heterogeneous composition. This study assesses the combined application of Electrical Resistivity Tomography (ERT) and Ground Penetrating Radar (GPR) for identifying microbialites in two contrasting geological and climatic settings: the Neoproterozoic Salitre Formation in Brazil and the Mesozoic microbialite-bearing limestones in northern Spain. High-resolution ERT profiles processed with raster-based blob detection algorithms revealed subcircular high-resistivity anomalies consistent with the studied microbialite morphologies, with strong resistivity contrasts observed between microbialites and host matrices despite variations in absolute values linked to lithology and soil moisture. In parallel, GPR surveys analyzed with a peak detection algorithm delineated domal reflectors and clusters of high-amplitude reflections that directly captured the internal architecture of stromatolitic buildups. With decimetric vertical resolution, GPR offered unrivaled insights into internal morphology, complementing the broader-scale imaging capacity of ERT. The complementary strengths of both methods are clear: ERT excels at mapping distribution and stratigraphic context, while GPR provides unparalleled resolution of internal structures. Crucially, this work advances previous efforts by explicitly demonstrating that integrated ERT-GPR approaches, when combined with algorithm-based interpretation, can resolve microbialite morphology, distribution and internal architecture with a level of objectivity not previously achieved. Beyond methodological refinement, these findings open new avenues for reconstructing microbialite development and preservation in ancient carbonate systems and hold strong potential for application in other geological contexts where complex carbonate structures challenge traditional geophysical imaging. Full article

This paper presents DeepMask-GPR, a novel deep learning framework for automatic detection and geometric estimation of buried cylindrical objects in ground-penetrating radar (GPR) B-scan images. Built upon Mask R-CNN, the proposed method integrates hyperbola detection, apex localization, and real-world coordinate mapping in an end-to-end architecture. A curvature-enhanced dual-channel input improves the visibility of weak hyperbolic patterns, while a quadratic regression loss guides the network to recover precise geometric parameters. DeepMask-GPR eliminates the need for raw signal data or manual post-processing, enabling robust and scalable deployment in field scenarios. On two public datasets, DeepMask-GPR achieves consistently higher TPR/IoU for spatial localization than baselines. On an in-house B-scan set, it attains low MAE/RMSE for radius estimation. Full article

Ground-penetrating radar (GPR) is widely used for thickness or compaction degree detection of asphalt pavement layers, where the dielectric properties of asphalt mixtures serve as a key parameter influencing detection accuracy. These properties are closely related to the composition of the mixture and are susceptible to environmental factors such as water or ice. To clarify the influence of various factors on the dielectric behavior of asphalt mixtures, an experimental study was conducted under controlled environmental conditions. Asphalt mixture specimens with different air void contents (5.49~10.29%) were prepared, and variables such as void fraction, moisture, and ice presence were systematically controlled. Air-coupled GPR was employed to measure the specimens, and the relative permittivity was calculated using both the reflection coefficient method (RCM) and the thickness inversion algorithm (TIA). Discrepancies between the two methods were compared and analyzed. Results indicate that the RCM is significantly influenced by surface water or ice and is only suitable for dielectric characterization under dry pavement conditions. In contrast, the TIA yields more reliable results across varying surface environments. A unified model (the optimized shape factor u = −4.5 and interaction coefficient v = 5.1) was established to describe the relationship between the dielectric properties of asphalt mixtures and their volumetric parameters (bulk specific density, air void content, voids in mineral aggregate, and voids filled with asphalt). This study enables quantitative analysis of the effects of water, ice, and mixture composition on the dielectric properties of asphalt mixtures, providing a scientific basis for non-destructive and accurate GPR-based evaluation of asphalt pavements. Full article

This study examines the feasibility of incorporating cathode-ray tube (CRT) panel glass as a partial replacement of natural aggregate in concrete, aiming to promote sustainable material utilization without compromising structural performance. Nine mixtures were prepared using three cement types—Normal 42.5 N, PC 50M(S-V-L) 42.5 N; Profi 42.5 R, PC 20M(S-L) 42.5 R; and Cement without additions, CEM I 42.5 R—and three CRT contents (0%, 5%, and 10%). A comprehensive experimental program was conducted, including tests on natural aggregates, mortars, and concrete in both fresh and hardened states, as well as flexural testing of reinforced concrete beams, supported by ground-penetrating radar (GPR) and digital image correlation (DIC) measurements. The results revealed that replacing up to 5% of natural aggregate with CRT glass had negligible effects on workability and density while slightly improving compressive and flexural strength. At 10% replacement, a minor reduction in strength and ductility was observed. Durability-related parameters, such as water absorption and carbonation depth, increased slightly but remained within acceptable limits. Flexural tests confirmed that beams with 5% CRT content exhibited comparable load capacity and crack propagation to reference beams. This study represents the first combined application of Digital Image Correlation (DIC) and Ground-Penetrating Radar (GPR) in evaluating reinforced concrete beams with CRT-modified concrete across different cement types. The results showed that incorporating 5% CRT glass increased flexural tensile strength by up to 15% compared with the control mix, confirming both the structural feasibility and sustainability of such composites. Overall, the findings indicate that CRT panel glass can be effectively utilized up to a 5% replacement level, offering both environmental and structural advantages for sustainable concrete production. Based on the experimental results, a replacement level of up to 5% CRT glass is recommended for structural concrete applications under the tested conditions, where CRT particles replaced the 4–8 mm medium aggregate fraction, as it ensures a balance between strength, ductility, and durability. Full article

Coal mining faces critical challenges due to variable geological conditions that affect intelligent mining and safe production. Ground-penetrating radar (GPR), a high-resolution and non-destructive sensing technology, is essential for precise geological detection. However, underground electromagnetic interference, multiple reflections, and complex media significantly degrade the signal-to-noise ratio (SNR), causing reflection signals to be obscured and geological interfaces to become blurred, thereby hindering accurate subsurface interpretation. Traditional denoising methods struggle to extract weak reflection signals under such complex noise conditions. To address these challenges, this study proposes a physics-guided conditional diffusion model that integrates physical constraints with deep learning to achieve intelligent denoising and weak-signal recovery for high-noise GPR data. Specifically, a dual-path GMM probabilistically models both feature signals and complex noise, while incorporating the wave equation ensures physical consistency with electromagnetic propagation. Experiments using a hybrid dataset combining field-measured noisy data and simulated features—evaluated using SSIM, PSNR, MAE, peak alignment, and structural continuity—demonstrate that the proposed method outperforms existing techniques in both noise suppression and signal reconstruction. Field tests in underground coal mines further confirm its practical applicability. Full article