Ground-penetrating radar signature of Quaternary faulting: a study from the Mt. Pollino region, southern Apennines, Italy

With the aim of unveiling evidence of Late Quaternary faulting, a series of ground-penetrating radar (GPR) profiles were acquired across the southern portion of the Fosso della Valle–Campotenese normal fault (VCT), located at the Campotenese continental basin (Mt. Pollino region) in the southern Apennines active extensional belt (Italy). A set of 49 GPR profiles, traced nearly perpendicular to this normal fault, was acquired using 300 and 500 MHz antennas and carefully processed through a customized workflow. The data interpretation allowed us to reconstruct a pseudo-3D model depicting the boundary between the Mesozoic bedrock and the sedimentary fill of the basin, which were in close proximity to the fault. Once the GPR signature of faulting was reviewed and defined, we interpret near-surface alluvial and colluvial sediments dislocated by a set of conjugate (W- and E-dipping) discontinuities that penetrate inside the underlying Triassic dolostones. Close to the contact between the continental deposits and the bedrock, some buried scarps which offset wedge-shaped deposits are interpreted as coseismic ruptures, subsequently sealed by later deposits. Our pseudo-3D GPR dataset represented a good trade-off between a dense 3D-GPR volume and conventional 2D data, which normally requires a higher degree of subjectivity during the interpretation. We have thus reconstructed a reliable subsurface fault pattern, discriminating master faults and a series of secondary splays. This contribution better characterizes active Quaternary faults in an area which falls within the Pollino seismic gap and is considered prone to severe surface faulting. Our results encourage further research at the study site, whilst we also recommend our workflow for similar regions characterized by high seismic hazard and scarcity of near-surface geophysical data.

Ground-penetrating radar imaging reveals glacier's drainage network in 3D

Hydrological systems of glaciers have a direct impact on the glacier dynamics. Since the 1950s, geophysical studies have provided insights into these hydrological systems. Unfortunately, such studies were predominantly conducted using 2D acquisitions along a few profiles, thus failing to provide spatially unaliased 3D images of englacial and subglacial water pathways. The latter has likely resulted in flawed constraints for the hydrological modelling of glacier drainage networks. Here, we present 3D ground-penetrating radar (GPR) results that provide high-resolution 3D images of an alpine glacier's drainage network. Our results confirm a long-standing englacial hydrology theory stating that englacial conduits flow around glacial overdeepenings rather than directly over the overdeepening. Furthermore, these results also show exciting new opportunities for high-resolution 3D GPR studies of glaciers.

3D GPR attributes to generate classified facies models: A case study from a dune island

Ground-penetrating radar (GPR) is a standard geophysical technique to image near-surface structures in sedimentary environments. In such environments, GPR data acquisition and processing are increasingly following 3D strategies. However, the processed GPR data volumes are typically still interpreted using selected 2D slices and manual concepts such as GPR facies analyses. In seismic volume interpretation, the application of (semi-)automated and reproducible approaches such as 3D attribute analyses as well as the production of attribute-based facies models are common practice today. In contrast, the field of 3D GPR attribute analyses and corresponding facies models is largely untapped. We develop and apply a workflow to produce 3D attribute-based GPR facies models comprising the dominant sedimentary reflection patterns in a GPR volume which images complex sandy structures on the dune island of Spiekeroog (Northern Germany). After presenting our field site and details regarding our data acquisition and processing, we calculate and filter 3D texture attributes to generate a database comprising the dominant texture features of our GPR data. Then, we perform a dimensionality reduction of this database to obtain meta texture attributes, which we analyze and integrate using composite imaging and (also considering additional geometric information) fuzzy c-means cluster analysis resulting in a classified GPR facies model. Considering our facies model and a corresponding GPR facies chart, we interpret our GPR data set in terms of near-surface sedimentary units, the corresponding depositional environments, and the recent formation history at our field site. Thus, we demonstrate the potential of the proposed workflow, which represents a novel and clear strategy to perform a more objective and consistent interpretation of 3D GPR data collected across different sedimentary environments.

GPR Clutter Reflection Noise-Filtering through Singular Value Decomposition in the Bidimensional Spectral Domain

Usually, in ground-penetrating radar (GPR) datasets, the user defines the limits between the useful signal and the noise through standard filtering to isolate the effective signal as much as possible. However, there are true reflections that mask the coherent reflectors that can be considered noise. In archaeological sites these clutter reflections are caused by scattering with origin in subsurface elements (e.g., isolated masonry, ceramic objects, and archaeological collapses). Its elimination is difficult because the wavelet parameters similar to coherent reflections and there is a risk of creating artefacts. In this study, a procedure to filter the clutter reflection noise (CRN) from GPR datasets is presented. The CRN filter is a singular value decomposition-based method (SVD), applied in the 2D spectral domain. This CRN filtering was tested in a dataset obtained from a controlled laboratory environment, to establish a mathematical control of this algorithm. Additionally, it has been applied in a 3D-GPR dataset acquired in the Roman villa of Horta da Torre (Fronteira, Portugal), which is an uncontrolled environment. The results show an increase in the quality of archaeological GPR planimetry that was verified via archaeological excavation.

GPR Clutter Reflection Noise Filtering Through Singular Value Decomposition in the Bidimensional Spectral Domain

Usually, in ground-penetrating radar (GPR) datasets the user defines the limits between the useful signal and the noise through standard filtering to isolate the effective signal as much as possible. However, there are true reflections that mask the coherent reflectors that can be considered noise. In archaeological sites these clutter reflections are caused by scattering with origin in subsurface elements (e.g., isolated masonry, ceramic objects and archaeological collapses). Its elimination is difficult because the wavelet parameters similar to coherent reflections and there is a risk of creating artifacts. In this study a procedure to filtering the clutter reflection noise (CRN) from GPR datasets is presented. The CRN filter is a singular value decomposition-based method (SVD), applied in the 2D spectral domain. This CRN filtering was tested in a dataset obtained from a controlled laboratory environment, to establish a mathematical control of this algorithm. Also, it has been applied in a 3D-GPR dataset acquired in the Roman villa of Horta da Torre (Fronteira, Portugal), which is an uncontrolled environment. The results show an increase in the quality of archaeological-GPR planimetry that were verified via archaeological excavation.

Ground-penetrating radar imaging reveals glacier’s drainage network in 3D

Hydrological systems of glaciers have a direct impact on the glacier dynamics. Since the 1950’s, geophysical studies have provided insights into these hydrological systems. Unfortunately, such studies were predominantly conducted using 2D acquisitions along a few profiles, thus failing to provide spatially unaliased 3D images of englacial and subglacial water pathways. The latter has likely resulted in flawed constraints for the hydrological modelling of glacier drainage networks. Here, we present for the first time 3D ground-penetrating radar (GPR) results that provide unprecedented high-resolution 3D images of an alpine glacier’s drainage network. Our results confirms a long-standing englacial hydrology theory stating that englacial conduits flow around glacial overdeepenings rather than directly over the overdeepening. Furthermore, these results also show exciting new opportunities for high-resolution 3D GPR studies of glaciers.

GPR Monitoring of Artificial Debonded Pavement Structures throughout Its Life Cycle during Accelerated Pavement Testing

The paper gives an overview of a ground penetrating radar (GPR) experiment to survey debonding areas within pavement structure during accelerated pavement tests (APT) conducted on the university Gustave Eiffel’s fatigue carrousel. Thirteen artificial defect sections composed of three types of defects (Tack-free, Geotextile, and Sand-based) were embedded during the construction phase between the top and the base layers. The data were collected in two stages covering the entire life cycle of the pavement structure using four GPR systems: An air-coupled ultra-wideband GPR (SF-GPR), two wideband 2D ground coupled GPRs (a SIR-4000 with a 1.5 GHz antenna and a 2.6 GHz-StructureScan from GSSI manufacturer), and a wideband 3D GPR (from 3D-radar manufacturer). The first stage of the experiments took place in 2012–2013 and lasted up to 300 K loadings. During this stage, the pavement structure presented no clear degradation. The second stage of experiments was conducted in 2019 and continued until the pavement surface demonstrated a strong degradation, which was observed at 800 K loadings. At the end of the GPR experiments, several trenches were cut at various sections to get the ground truth of the pavement structure. Finally, the GPR data are processed using the conventional amplitude ratio test to study the evolution of the echoes coming from the debonded areas.

Application of Combining YOLO Models and 3D GPR Images in Road Detection and Maintenance

Improving the detection efficiency and maintenance benefits is one of the greatest challenges in road testing and maintenance. To address this problem, this paper presents a method for combining the you only look once (YOLO) series with 3D ground-penetrating radar (GPR) images to recognize the internal defects in asphalt pavement and compares the effectiveness of traditional detection and GPR detection by evaluating the maintenance benefits. First, traditional detection is conducted to survey and summarize the surface conditions of tested roads, which are missing the internal information. Therefore, GPR detection is implemented to acquire the images of concealed defects. Then, the YOLOv5 model with the most even performance of the six selected models is applied to achieve the rapid identification of road defects. Finally, the benefits evaluation of maintenance programs based on these two detection methods is conducted from economic and environmental perspectives. The results demonstrate that the economic scores are improved and the maintenance cost is reduced by $49,398/km based on GPR detection; the energy consumption and carbon emissions are reduced by 792,106 MJ/km (16.94%) and 56,289 kg/km (16.91%), respectively, all of which indicates the effectiveness of 3D GPR in pavement detection and maintenance.

Enhancement of 3D GPR datasets using singular value decomposition applied in 2D the spectral domain for clutter noise removal

<p>The ground-penetrating radar (GPR) datasets obtained in archaeological environments have substantial problems related the presence of clutter noise. These noisy reflections are generated by the heterogeneities of the ground and by the collapses of structures buried in the ground, that can prevent a good assessment of the subsurface with this method. The classic filtering operations available can fail to remove it effectively. This work presents an approach to filtering the GPR data in the 2D spectral domain through the singular value decomposition (SVD) factorization technique. The spectral domain present advantages such as the circular symmetry of the transformed data that turns easy the filter parametrisation and the constant computational effort whatever the amount of data considered. SVD allows the decreasing of the user dependency to parametrize the filter. The main propose of this method is to classify automatically the datasets into useful information, corresponding to buried structures, and noise, to remove the last. This approach was conceived based on the study of the GPR signal in the 2D spectral domain and the manual filter design. The tests were performed with different datasets, one from a laboratory experiment (controlled environment) and the other from a field acquisition in an archaeological site (uncontrolled environment) with subsequent excavation to proof the results. The proposed approach is effective to remove the clutter noise in the GPR datasets and constitutes a complementary operation to those already existing in the commercial software.</p><p> </p><p>Acknowledgment: The work was supported by the Portuguese Foundation for Science and Technology (FCT) project UIDB/04683/2020 - ICT (Institute of Earth Sciences) and by the INTERREG 2014-2020 Program, through the "Innovación abierta e inteligente en la EUROACE" Project, with the reference 0049_INNOACE_4_E.</p>

Integrated reflection seismics, 3D-GPR, leveling, DInSAR to detect and characterize high-risk sinkholes in urban cover evaporite karst. A NE Italian case study.

<p>Sinkholes linked to cover evaporite karst in urban environments still represent a challenge in terms of clear identification and mapping considering the anthropic rehash and the presence of man-made structures.</p><p>We propose and tested a methodology to identify the subsiding features in an urban area within a cover evaporite karst environment, through an integrated and non-invasive multi-scale approach combining seismic reflection, DInSAR, leveling and full 3D GPR.</p><p>The analysis was conducted in a small village in the Tagliamento valley (Friuli Venezia Giulia region, NE Italy) named Quinis, where sinkholes are reported since a long time as well as the hazard linked to their presence: within the years, several houses have been demolished and at present many of them are damaged.</p><p>First we applied each methodology independently and after we compared, combined and integrated them to obtain more coherent and cross-validates results. Seismic reflection imagined the covered karst bedrock identifying three depocenters; DInSAR investigation allowed to identify an area with higher vertical velocities; leveling data presented a downward displacement comparable with DInSAR results; 3D GPR, applied here for the first time in the study and characterization of sinkholes, clearly defined shallow sinking features imaging also under a shallow dense pipe network. Combining all the obtained results with accurate field observations we identified and map the highest vulnerable zones.</p><p>The final result is the combining of the geophysical, DInSAR and leveling information, while also locating the damaged buildings, the local asphalt pavement breaks or renovation and the buildings which are nowadays demolished, by using vintage photographs and historical maps. The data are consistent, being the most relevant present damages and the demolished building within the zones with higher sinking velocity on the base of both leveling and DInSAR. Geophysically imaged depocenters lie within the most critical area and perfectly correlate with the local pavement damages.</p><p>In a complex geological and hydrological framework, as in the study area, a multidisciplinary and multi-scale approach is mandatory to identify and map the zone most affected by sinking phenomena. While punctual data such as borehole stratigraphy, local groundwater level variations with time, extensometers measurements and geotechnical parameters are useful to highlight local hazard due to occurring deformation, the proposed integrated methodology addresses a complete and quantitative assessment of the vulnerability of the area. It’s fundamental, especially in anthropized environments, using different integrated techniques, without forgetting the role of the fieldwork of the geologists who can detect the precursors or already occurred, even elusive, signs of the ongoing or incipient sinking.</p>