Displays

How to cite: Podd, F., Gao, X., van Verre, W., Daniels, D., and Peyton, A.: The effect of geometry on the feed impedance for a PCB-dipole antenna and the time domain radiation emission from the feed point, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21972, https://doi.org/10.5194/egusphere-egu2020-21972, 2020.

Automated processing and extraction of useful information from GPR data is a complicated task, for which various approaches have been developed during the last years. This work examines the introduction of Canny edge detector as a new preliminary step of an advanced algorithm for automated hyperbola detection [1, 2]. The overall algorithm aims to identify radargram portions wherein hyperbolic reflections apices are present and extract the coordinates of such apices.

The newly introduced step utilizing Canny edge detector consists of two main procedures: (1) identification of edge pixels in a radargram and (2) elimination of edge pixels that do not meet specific criteria. The latter procedure aims to accelerate the algorithm by reducing the number of pixels, without compromising the correct detection and localization of hyperbola apices. For the elimination of unnecessary edge pixels, different criteria have been designed and tested; a practical solution has been found, which yields the elimination of the highest number of unnecessary edge pixels without eliminating useful edge pixels. No pixels are eliminated from the close vicinity of hyperbola apices since it is better to keep a higher number of edge pixels than to eliminate useful ones. In the implementation of the algorithm, special attention has been paid to its execution time, thinking of real-time applications.

The upgraded algorithm was tested on experimental radargrams from IFSTTAR (The French Institute of Science and Technology for Transport, Development, and Networks) test field in Nantes, France [3]. That test field consists of vertical sections filled with different materials and hosting many buried objects, such as cables and pipes, or walls and stones, imitating common scenarios in urban areas. Radargram acquisition was done using antennas with different central frequencies. Radargrams containing hyperbolic reflections were selected and used for testing the upgraded algorithm, with promising results.

References

[1] A. Ristić, Ž. Bugarinović, M. Govedarica, L. Pajewski, and X. Derobert, “Verification of algorithm for point extraction from hyperbolic reflections in GPR data,” Proc. 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR 2017), Edinburgh, UK, pp. 1-5, 2017.

[2] A. Ristić, M. Vrtunski, M. Govedarica, L. Pajewski, and X. Derobert, “Automated data extraction from synthetic and real radargrams of district heating pipelines,” Proc. 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR 2017), Edinburgh, UK, pp. 1-5, 2017.

[3] X. Dérobert and L. Pajewski, “TU1208 Open Database of Radargrams: The Dataset of the IFSTTAR Geophysical Test Site,” Remote Sensing, Vol. 10(4), 530, pp. 1-50, 2018.

How to cite: Bugarinović, Ž., Pajewski, L., Ristić, A., Vrtunski, M., and Govedarica, M.: Application of an advanced algorithm for automated hyperbola detection, including Canny edge detector, to GPR data from IFSTTAR test field, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10632, https://doi.org/10.5194/egusphere-egu2020-10632, 2020.

Over the years, the detection and imaging of targets embedded in layered media has become of paramount importance in a diverse set of problems including those in microwave remote sensing, nondestructive testing, ground penetrating radar (GPR), and through-the-wall imaging (TWRI). Specifically, development of imaging techniques for visually inaccessible targets buried under the ground has attracted growing interest in archaeology, underground weapon detection, building safety and durability assessment, geophysical exploration, etc. For high resolution imaging in these applications, usually a long aperture is synthesized using an ultra-wideband transmitted signal; this makes the approach impractical and/or costly in many realistic situations. To reduce the collected data volume in order to accelerate radar data acquisition and processing times such that prompt actionable intelligence would be possible, several research groups in recent years have applied Compressive Sensing (CS) to radar imaging in GPR to reconstruct a sparse target scene from far fewer non-adaptive measurements. The standard CS techniques, however, are mainly based on L₁-norm minimization, which is primarily effective in detecting the presence of targets as it cannot accurately reconstruct the target shape and/or differentiate closely spaced targets from an extended target.

In this presentation, we give an overview of our group’s recent works on image reconstruction for both SAR-based and multiple-input multiple-output (MIMO) based GPR targets in a multilayered subsurface medium using CS. In our approach, the subsurface layers are accurately and efficiently accounted for in the sparse-image reconstruction through analytically derived expressions for the Green’s functions of multi-layered lossy dielectric media. In particular, we will discuss the use of total variation minimization (TVM) and its advantages over the L₁-norm minimization which is often used in the standard radar implementation of CS. The TVM technique minimizes the gradient of the image instead of the image itself, and as a result leads to better shape reconstruction of large and/or multiple subsurface targets. In addition, we also discuss the use of group sparsity reconstruction (GPS) technique and compare its performance with that of TVM under various noise levels. Numerical results for sparse imaging in various subsurface scenarios using different reduced sets of SAR and MIMO radar transmit and receive antenna elements as well as reduced number of frequency bins will be given in the presentation.

How to cite: Hoorfar, A.: Advances in Sparse Image Reconstruction of GPR Subsurface Targets, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4231, https://doi.org/10.5194/egusphere-egu2020-4231, 2020.

Artificial subsurface drainage systems are installed in agricultural areas to remove excess water and convert poorly naturally drained soils into productive cropland. Some of the most productive agricultural regions in the world are a result of subsurface drainage practices. Drain lines provide a shortened pathway for the release of nutrients and pesticides into the environment, which presents a potentially increased risk for eutrophication and contamination of surface water bodies. Knowledge of drain line locations is often lacking. This complicates the understanding of the local hydrology and solute dynamics and the consequent planning of mitigation strategies such as constructed wetlands, saturated buffers, bioreactors, and nitrate and phosphate filters. In addition, accurate knowledge of the existing subsurface drainage system is required in designing the installation of a new set of drain lines to enhance soil water removal efficiency. The traditional methods of drainage mapping involve the use of tile probes and trenching equipment which are time-consuming, tiresome, and invasive, thereby carrying an inherent risk of damaging the drain pipes. Non-invasive geophysical sensors provide a potential alternative solution to the problem. Previous research has focused on the use of time-domain ground penetrating radar (GPR) with variable success depending on local soil and hydrological conditions and the center frequency of the specific equipment used. For example, 250 MHz antennas proved to be more suitable for drain line mapping. Recent technological advancements enabled the collection of high-resolution spatially exhaustive data. In this study, we present the use of a stepped-frequency continuous wave (SFCW) 3D-GPR (GeoScope Mk IV 3D-Radar with DXG1820 antenna array) mounted in a motorized survey configuration with real-time georeferencing for subsurface drainage mapping. The 3D-GPR system offers more flexibility for application to different (sub)surface conditions due to the coverage of wide frequency bandwidth (60-3000 MHz). In addition, the wide array swathe of the antenna array (1.5 m covered by 20 measurement channels) enables effective coverage of three-dimensional (3D) space. The surveys were performed on twelve different study sites with various soil types with textures ranging from sand to clay till. While we achieved good success in finding the drainage pipes at five sites with sandy, sandy loam, loamy sand and organic topsoils, the results at the other seven sites with more clay-rich soils were less successful. The high attenuation of electromagnetic waves in highly conductive clay-rich soils, which limits the penetration depth of the 3D-GPR system, can explain our findings obtained in this research.

How to cite: Koganti, T., Van De Vijver, E., J. Allred, B., H. Greve, M., Ringgaard, J., and V. Iversen, B.: Mapping Subsurface Drainage in Agricultural Areas Using a Frequency-Domain Ground Penetrating Radar, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1887, https://doi.org/10.5194/egusphere-egu2020-1887, 2020.

Currently atmospheric carbon has reached 405 ppm or 720 GtC.  As is widely known, this increasing atmospheric carbon dioxide, methane and nitrous oxide are primary contributing factors in increasing global temperatures.  Current measurements show that sources of emission such as the burning of fossil fuels contributes 9.9 GtC/yr, while land use change contributes 1.5 GtC/yr. We have identified that crops possessing a subsurface rhizome in particular, in addition to high root biomass, are essential and capable of increasing crop derived soil carbon sequestration by 10-fold.  If the presence of a high biomass rhizome were bred into the world’s major grain crops wheat, rice, maize, barley, sorghum and millets and grown worldwide in no-tillage conditions, these crops could sequester and offset current carbon emissions by 9Gt carbon on a yearly basis. We have developed a new ground penetrating radar instrument and analytical software, which will be presented, as a needed for high throughput non-destructive phenotyping, selection and speed breeding new high root biomass cultivars of the worlds major cultivated crops and forages as a key component for crop-based carbon sequestration driven climate change mitigation. 

How to cite: Hays, D., Wolfe, M., Dobreva, I., and Ruiz, H.: Development of ground penetrating radar for enhanced root phenotyping and carbon sequestration, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1406, https://doi.org/10.5194/egusphere-egu2020-1406, 2020.

In Finland, two large “moraine” ridges (Salpausselka I and Salpausselka II), extending to over 600 km in length, delineate two major stillstand/readvance positions of the Fennoscandian ice sheet during the last deglaciation (Glückert, 1986). They are inferred to be chronologically related to the cold stage known as the Younger Dryas which occurred at the end of the last glaciation. During this time the Baltic ice lobe and the Finnish Lake District ice lobe, constituting a part of the southern margin of the Fennoscandian ice sheet, were grounded in a large proglacial lake, the Baltic ice lake, a predecessor to the modern-day Baltic Sea. The “moraine” ridge is mostly composed of glaciofluvial sands, gravels and boulders rather than diamicton and deposited on crystalline, impermeable bedrock and constitute  freshwater aquifer in southern and eastern Finland. The average thickness of ice-contact deltas sediments is estimated at between 20 and 60 meters and is highly variable.

Outcrop studies are combined with GPR and ERTprofiles to provide insight into the aquifer architecture at different scales and depths of investigation. This study aims to improve our understanding of such deposits in the subsurface, especially about their internal structure, sedimentary facies distribution and potential barriers and/or baffles to fluid flow and poro-perm characteristics.

How to cite: Kurjanski, B., Rea, B., Spagnolo, M., Cornwell, D., Palmu, J.-P., Howell, J., Quiros, A., and Comte, J.-C.: Ice-contact deltas investigation using ground penetrating radar (GPR), sedimentology, electrical resistivity tomography (ERT) and , Salpausselka I and II near Lahti, Finland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3033, https://doi.org/10.5194/egusphere-egu2020-3033, 2020.

Recent field research at White Sands National Park, New Mexico, USA, has used ground-penetrating radar to detect the footprints of Pleistocene humans, mammoths, and ground sloths. The technique has been succesful with a range of antenna frequencies and for detecting footprints of many different sizes. Perhaps more importantly, the method has been shown to successfully detect fooprints that are not visible to the human eye, often with sufficent detail to differntiate species. This work raises an obvious question about whether GPR could be used to detect footprints in a range of other contexts, or whether the circumstances seen at White Sands are unique. 

How to cite: urban, T.: Detecting footprints with GPR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21096, https://doi.org/10.5194/egusphere-egu2020-21096, 2020.

Ground Penetrating Radar (GPR) systems need to be calibrated on a recurrent basis and their performance shall be periodically verified, in accordance with manufacturer recommendations and specifications. Nevertheless, most GPR owners in Europe employ their radar units and antennas for years without ever having them verified by manufacturers, unless major flaws or issues become evident. In this framework, Members of COST Action TU1208 have recently carried out a critical analysis of the few existing procedures for the calibration and performance verification of GPR systems; and, they have proposed four improved experimental tests to evaluate the signal-to-noise ratio, short-term stability, linearity in the time axis, and long-term stability of the GPR signal [1]. In this work, we present the results of the tests executed in Novi Sad, Serbia, on a GSSI SIR 3000 control unit equipped with GSSI ground-coupled antennas having central frequencies of 400 MHz and 900 MHz. We have experienced that the execution of the tests helps to attain stronger awareness about the behaviour and limits of owned GPR equipment. It is also interesting to check how the results of the tests change over time and in different environmental conditions, to analyze the performance evolution of the equipment. Main aim of this abstract is to spread the voice and encourage GPR owners and manufacturers to execute the tests. If a wide variety of control units and antennas are tested, of older and more recent conception, with different numbers of working hours, reliable thresholds for the tests can be established and the proposed procedures can be further refined and upgraded. Moreover, the results of the tests can be translated into accuracy levels of measured physical and geometrical quantities, to get some awareness about the uncertainty of results of a GPR survey (e.g., achieved accuracy levels in the estimation of layer thicknesses).

[1] L. Pajewski, M. Vrtunski, Ž. Bugarinović, A. Ristić, M. Govedarica, A. van der Wielen, C. Grégoire, C. Van Geem, X. Dérobert, V. Borecky, S. Serkan Artagan, S. Fontul, V. Marecos, and S. Lambot, "GPR system performance compliance according to COST Action TU1208 guidelines,"  Ground Penetrating Radar, Volume 1, Issue 2, Article ID GPR-1-2-1, July 2018, pp. 2-36, doi.org/10.26376/GPR2018007.

How to cite: Vrtunski, M., Pajewski, L., Ristić, A., Bugarinović, Ž., and Govedarica, M.: Results of experimental tests for the evaluation of the signal-to-noise ratio, short-term stability, linearity in the time axis, and long-term stability of the GPR signal - according to COST Action TU1208 guidelines, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18836, https://doi.org/10.5194/egusphere-egu2020-18836, 2020.

This paper presents a method for the automated detection and elimination of horizontal reflections from ground penetrating radar (GPR) profiles after Canny edge filtering. Horizontal reflections are generated by interfaces between different media parallel to the air-soil interface. The recognition of horizontal layers is a crucial task when the number of layers and their thicknesses need to be estimated (e.g., in GPR road surveys). Identifying and deleting horizontal reflections from a radargram is also useful to facilitate the subsequent automated extraction of hyperbolic reflections [1-3]. It has to be noted that the removal of horizontal layers can increase the level of radargram segmentation.

In the proposed method, the first segmentation step is the application of Canny edge detector to the entire radargram. Then, horizontal layer recognition is done by carefully choosing boundary values. These values are varied many times until optimal values, depending on data acquisition parameters, are adopted. Special attention is paid to time efficiency of both segmentation steps, to investigate the possibility of employing the proposed solution in near real-time applications. The final result is an image where edge pixels arranged horizontally are removed.

Testing of this algorithm is done in MATLAB software environment, on a set of data with different levels of complexity, by varying the acquisition parameters.

References

[1]  A. Ristić, Ž. Bugarinović, M. Govedarica, L. Pajewski, and X. Derobert, “Verification of algorithm for point extraction from hyperbolic reflections in GPR data,” Proc. 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR 2017), Edinburgh, UK, pp. 1-5, 2017.

[2]  A. Ristić, M. Vrtunski, M. Govedarica, L. Pajewski, and X. Derobert, “Automated data extraction from synthetic and real radargrams of district heating pipelines,” Proc. 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR 2017), Edinburgh, UK, pp. 1-5, 2017.

[3]  Ž. Bugarinović, S.  Meschino, M. Vrtunski, L. Pajewski, A. Ristić, X. Derobert, and M. Govedarica, “Automated Data Extraction from Synthetic and Real Radargrams of Complex Structures,” Journal of Environmental and Engineering Geophysics, Vol. 23(4), pp. 407-421, 2018.

How to cite: Vrtunski, M., Bugarinović, Ž., Pajewski, L., Ristić, A., and Govedarica, M.: Recognition of horizontal layers in a segmented radargram after the application of Canny edge detector, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7909, https://doi.org/10.5194/egusphere-egu2020-7909, 2020.

In the last decades, ever growing efforts have been devoted to the development of techniques for extracting information from Ground Penetrating Radar (GPR) measurements. In particular, the processed data are used to retrieve two different kinds of features. The first kind includes the so-called qualitative properties of buried targets, which are typically related to the location and/or the shape of the objects. The second kind of features is related to the quantitative dielectric characterization of the underground targets. Both strengths and weaknesses of qualitative and quantitative approaches are well known in the scientific community. Despite the more complex mathematical structure of quantitative techniques, their use is attracting an increasing attention in multiple geophysical and engineering applications.

In this contribution, the full dielectric characterization of the region of interest is retrieved by a quantitative inversion approach that works in the mathematical framework of Lebesgue spaces with variable exponents. The most important parameter of this algorithm is represented by the map of the exponent function inside the investigation domain. Here, different strategies for obtaining and refining this map in an adaptive fashion iteration-by-iteration are proposed. Numerical results are presented to check the effectiveness of the inversion approach.

How to cite: Fedeli, A., Pastorino, M., and Randazzo, A.: Full-waveform inversion of Ground Penetrating Radar data for target characterization in multilayer environments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22361, https://doi.org/10.5194/egusphere-egu2020-22361, 2020.

In the field of pavement monitoring, Ground Penetrating Radar (GPR) methods are gaining prominence due to their ability to perform non-destructive testing of the subsurface. In this context, the detection and characterization of subsurface debondings at an early stage is recommended to avoid further degradation and to maintain the lifespan of these structures. To mitigate the limited time resolution of the conventional GPR devices, this paper develops the detection of thin debonding (of millimeter-order) by monitoring small changes in the time domain GPR data by specific data processing techniques (with certain automatic capabilities).

In this paper, we propose to use the supervised machine learning method, namely Two-class Support Vector Machines (SVM) to achieve the objectives. In addition, by means of time domain GPR signal features, we aim at reducing the computational burden and also increase the efficiency of SVM. The method is implemented to process independent 1D GPR A-scan data.

Furthermore, the performance assessment of Two-class SVM is carried out on both simulated and field data by means of Sensitivity Analysis to identify the parameters that affect its performance. While simulated data is generated using the analytic Fresnel data model, the field data are UWB Stepped-Frequency GPR (SF-GPR) data which were collected over artificially embedded debondings. The data was acquired during the Accelerated Pavement Tests (APTs) conducted at the IFSTTAR's fatigue carousel to survey debonding growth in the defect-affected zones at various stages of fatigue.

Two-class SVM presented the ability to detect thin millimetric debondings. Whereas, sensitivity analysis demonstrated a quick and efficient way to assess the pavement conditions.

How to cite: Todkar, S. S., Baltazart, V., Ihamouten, A., Dérobert, X., and Simonin, J.-M.: Performance analysis of Two-class SVM to detect thin interlayer debondings within pavement structures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22503, https://doi.org/10.5194/egusphere-egu2020-22503, 2020.

In this paper an application of GPR in the analysis of concrete structure is presented. Scanning is done as a part of preparation for mitigation works of dam ’Grančarevo’. The goal was to inspect existing small cracks and leakages. The dam is arc-shaped concrete dam with double curvatures. It is operational since 1968, and is situated 18km downstream from the wellspring of Trebišnjica river and 17km upstream from the town Trebinje, in Bosnia and Herzegovina. Relative height of the dam is 123m, while its width along the crown is 439m. Continuous monitoring of dam’s construction and surrounding terrain is conducted at over 800 measuring points. In order to determine precise position, geometry and propagation of cracks, this was the first time GPR was used.

GPR scanning was done on several important locations: on the crown, downstream face, internal galleries, down- and upstream walls, using antennas with 900 and 400MHz central frequencies. Based on scanning results, position and geometry of cracks within the concrete are successfully determined. Lateral scanning (on downstream face of the dam) are correlated with the results obtained on the crown. Also, at several locations, zones with higher humidity are noticed. These zones are significant since they present areas of higher priority during mitigation and they are often found in the vicinity of junctions between two concrete segments of the dam.

Obtained results indicate that GPR technology is rather useful tool for structure health monitoring which provides information that are significant in planning mitigation measures and extending a lifetime of a concrete object.

How to cite: Ristic, A., Bugarinović, Ž., Vrtunski, M., Govedarica, M., and Pajewski, L.: Application of GPR in assessing of concrete dam structures health, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7797, https://doi.org/10.5194/egusphere-egu2020-7797, 2020.

In the field of civil engineering, and more particularly in the road building, it is necessary to control some physical parameters with standard methods. These controls ensure the implementation is performed according to the technical specifications. They also allow to optimize the structure dimensions  with the best safety/cost ratio and an optimal lifetime. Compactness related to density and therefore indicative of mechanical strength necessary to support traffic solicitations is a key parameter to control. Currently, density control in the laboratory is done using bench with nuclear sources on pavement cores, based on the emission and reception of gamma rays. Its replacement has now become a major issue since this method generates increasingly high costs and constraints (use, storage, transport and exposure to ionizing radiation). The objective of this work is to find an alternative non-nuclear solution to control the pavement compactness with an accuracy equivalent to the gamma-bench method . The proposed solution is an electromagnetic bench (EM), allowing cores tomography to measure permittivity. The density will then be evaluated by means of mixing rules. The EM bench consists of a vector network analyzer (Agilent E8362B) and two Ultra-Wide Band antennas [1.4-15 GHz] which are developed in this project in order to have the best performances (accuracy, dimensions…).

The antennas are placed facing each other, separated by a distance D.  A cylindrical sample (core) extracted from stratified road medium of diameter d to be tested is placed in the middle of the system and both antennas move with a given step (ranging from a few mm to 1 cm) along the sample to measure by stratification the core EM properties. The entire EM bench is motorized and driven by software developed in the laboratory. At each step, a measurement of S₂₁ -parameter is recorded. Then signals are processed in the time domain to evaluate the relative permittivity.

The first results of modeling and measurements on laboratory asphalt samples show that the system makes it possible to evaluate the relative permittivity of different stratified materials. Accuracy, resolution and perspectives will be discussed.

key words : density, asphalt concrete, radar, electromagnetic bench

How to cite: boughanmi, I., Fauchard, C., Benjelloun, N., and Riah, Z.: Alternative solution to the gamma bench for the dielectric characterization of materials, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8900, https://doi.org/10.5194/egusphere-egu2020-8900, 2020.

The Aegyssus archaeological site is located on the Monument Hill in the North-Eastern section of Tulcea, the fortress was built at the end of the 4^th century B.C. Its name, of Celtic origin, derived from a legendary founder, Caspios Aegyssos. At the beginning of 2^nd century, the town was included in the Danubian limes (boundary). Then, starting with the 3^rd century, it became an important military headquarters. The 6^th century finds it as an episcopal residence. Urban life knows an end in the first quarter of the 7^th century and a revival in the 10^th and 11^th centuries.

The geophysical investigation has been performed by means of the integrated use of three different high resolution and non invasive geophysical techniques: magnetic mapping, ground penetrating radar profiling (GPR) and magnetic susceptibility measurements.

Magnetic and ground penetrating radar methods are widely used for archaeological prospecting as very effective methods able to detect buried structures at small depths. These methods were applied for the investigation of two perimeters within the site of the ancient city of Aegyssus, an ancient Roman fortress from North Dobrudja, Romania, which was built in the first century. The primary objective was to determine the extension in the underground of a partially excavated wall. The maximum magnetic anomalies revealed the possible location of the buried wall.

The magnetometric investigation has been carried out using a protonic magnetometer G-856 GEOMETRICS in gradiometric mode, with the two magnetic sensors set in a vertical direction separated by a distance of 1 m.

A total of 20 ground penetrating radar profiles were acquired with 250 MHz antenna aiming in identifying geological and archaeological anomalies in order to assist archaeologists in an excavation program.

The GPR results indicated clear geophysical anomalies characterized by hyperbolic reflections. These anomalies were confirmed by the excavation of test units, allowing the identification anthropogenic features such as a fire-hearth structure and wooden artifact, and natural features.

The results showed the efficiency of GPR and magnetometric methods in identifying potential buried archaeological targets, and they are oriented towards reducing costs and increasing the probability of finding archaeological targets.

Our geophysical results helped to define spatial pattern of the buried remains, to define the geometry of the anthropogenic settlements and to obtain detailed information about the composition and the manufacturing processes of different building materials.

This work was supported by Romanian Ministry of Research and Innovation through the Project “Fluvimar” (Program 1. Development of the National Research-Development System. Subprogram 1.2. Institutional Performance) and Core Programme PN 19 20 05 01. 

How to cite: Anghel, S., Dragos, A. G., Iordache, G., and Pop, I. C.: Magnetometric and ground penetrating radar investigations in the Aegyssus archaeologic site, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3031, https://doi.org/10.5194/egusphere-egu2020-3031, 2020.

The town of Santo Amaro, in the state of Bahia, Brazil, presents a history of contamination, mainly of lead (Pb) originating from the intense activity of metallurgical extraction by the mining company “Plumbum-Mineração e Metalurgia Ltda.” between the years of 1956 and 1993. Over this period, the lead slag was deposited carelessly in the factory area, creating a huge hazardous waste site. Subsequently, the problem increased when this slag was used as the basis for the paving of city streets, gardens, and school yards due to its granular characteristic and good support capacity. However, the ongoing need to remove the street paving for work on the water and sewage networks requires the exposure of the slag, making it a source of active contamination. In this context, the Ground Penetrating Radar (GPR) method was used as a tool to support and guide the evaluation of the existence of anomalous areas associated with the source of local contamination (slag) under the paving. In this work the data was acquired by moving the GPR using the of constant offset technique and a sampling interval of 5 cm between the traces. The shoots and trace records were registered continuously with the use of a calibrated wheel. The results obtained by this study show the potential of applying the GPR method to the environmental characterization of the subsoil of paved streets, making it possible to identify the resistive material contaminants (lead slag) as well as the various layers: paving, soil-slag, and massapê soil. These layers are characterized by distinct reflection patterns. The first observed reflection pattern has high amplitude with horizontal and continuous reflectors, which correspond to a characteristic pattern of urban street paving. The second reflection pattern is characterized by reflectors with amplitude variations (horizontal and inclined, continuous and discontinuous), which indicate the heterogeneity of the medium and corresponds to the soil pattern mixed with the resistive slag material. The third reflection pattern is characterized by low amplitude with chaotic and totally discontinuous reflectors, and occurs just below the second reflection pattern. This pattern of reflection marks the region in which the electromagnetic GPR signal is absorbed by the medium. This absorption is an effect of the attenuation of the electromagnetic signal by the presence of electrically conductive layers of the characteristic massapê soil (clayey to very clayey) of the study area. GPR data also enabled the identification of reflectors associated with anthropogenic interferences (manholes, train lines, pipelines, etc.). Borehole samples confirmed the existence of the contaminant (lead slag). Anomalous concentrations of heavy metals, mainly lead, were observed in the locations indicated by geophysical results using the GPR method, showing the importance of the use of geophysics in environmental characterization programs.

How to cite: Lago, A., Costa, I., and Cunha, F.: Geophysical investigation using the GPR method: a case study of a lead contamination in Santo Amaro, Bahia, Brazil, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5310, https://doi.org/10.5194/egusphere-egu2020-5310, 2020.

During the last two decades, ground-penetrating radar (GPR) methods, have grown in popularity for acquiring high-resolution images of the stratigraphy, internal structure and wider context of geomorphology, as well as the reconstruction and evolution of buried landscapes. GPR offers centimetre-scale resolution of the subsurface, allowing 3D visualization of abrupt changes in palaeo-environments. Although often complemented by core data, GPR interpretations can also be extended beyond regions of ground-truth control. However, for all these advantages, GPR data interpretation can be non-intuitive and ambiguous, with the technique seldom giving images that immediately resemble the expected subsurface geometry. Interpretation can be made yet more onerous when handling the large 3D data volumes that are commonly available with modern GPR technology.

In this paper, we outline the development of a semi-automated GPR feature-extraction tool, based on the image processing techniques ‘Edge Detection’ and ‘Thresholding’. Developed initially for medical image analysis, we investigate them as a means of assisting the analysis of GPR data for subsurface geomorphic features. Given that GPR reflectivity can be related to changes in lithology and/or pore fluids, the structure and extent of subsurface depositional environments can be efficiently estimated using these algorithms. When benchmarked against representative core control, the 3D architecture of the palaeo-landscape can be reconstructed from the GPR dataset.

We present a 500 MHz GPR dataset collected over a buried Holocene coastal dune system in Llanbedr, Gwynedd, North Wales, which has since been reclaimed for use as an airfield. Core data, with maximum depth 2 m, suggest rapid vertical changes from sand to silty-organic units, and GPR profiles suggest that similar lateral complexity is likely across the dataset. By applying thresholding methods to top-down depth slices, the environment is effectively characterised. Furthermore, automatic extraction of the local reflection power with depth yields a strong correlation with the vertical variation of organic content. Similar analyses away from core control could, therefore, deliver a powerful proxy for parameters derived from invasive core logging.

How to cite: Rees-Hughes, L., Barlow, N., Booth, A., West, J., Tuckwell, G., and Grossey, T.: Drowned Dunes: Integrating 3D GPR and core data to reconstruct a late Holocene buried dune environment., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9019, https://doi.org/10.5194/egusphere-egu2020-9019, 2020.