Ground-penetrating Radar Reflection Research Articles

Identifying Ice Wedges in Ground Penetrating Radar data from the CRREL Permafrost Tunnel, Fox Alaska

The warming of Alaska’s permafrost has been leading to thawing within its discontinuous permafrost. This can cause ice wedges to melt resulting in thermokarst formations such as sink holes and landslides which are causing damage to Alaskan infrastructure. To avoid developing further infrastructure in areas containing ice wedges, it is necessary to improve methods of detecting subsurface ground ice. Ground Penetrating Radar (GPR) is a nonintrusive remote sensing method of locating and characterizing permafrost and other subsurface features that are not evident on a cut face or surface. When applied to the detection of ice wedges at the CRREL (Cold Regions Research and Engineering Laboratory) permafrost tunnel in Fox, Alaska, a few identifying features were observed which corresponded with prior research. We first used GPR reflections of areas along the tunnel walls holding known ice wedges to verify the identifying features of an ice wedge within GPR data. We utilized these reflections as test data to identify possible ice wedges in locations where they were not observed on the tunnel walls.

3D ground-penetrating radar data analysis and interpretation using attributes based on the gradient structure tensor

In near-surface geophysics, ground-penetrating radar (GPR) surveys are routinely employed in a variety of applications including those from archaeology, civil engineering, hydrology, and soil science. Thanks to recent technical developments in GPR instrumentation and antenna design, 3D surveys comprising several 100.000 traces can be performed daily. Especially in complex environments such as sedimentary systems, analyzing and interpreting the resulting GPR volumes is a time-consuming and laborious task that is still largely performed manually. In the last decades, several data attributes have been proposed to guide and improve such tasks and assure a higher degree of reproducibility in the resulting interpretations. Many of these attributes have been developed in image processing or computer vision and are routinely used, for example, in reflection seismic data interpretation. Especially in sedimentary systems, variations in the subsurface are accompanied by variations of GPR reflections in terms of amplitudes, continuity, and geometry in view of dip angle and direction. A promising tool to analyze such structural features is known as the gradient structure tensor (GST). Up to today, the application of the GST approach is limited to a few 2D GPR examples. Thus, we take up the basic idea of GST analysis and introduce and evaluate the corresponding attributes to analyze 3D GPR data. We apply the proposed GST approach to one synthetic and two field data sets imaging diverse sedimentary structures. Our results demonstrate that the proposed set of GST-based attributes can be efficiently computed in 3D and that these attributes represent versatile measures to address different typical interpretation tasks and, thus, help for an efficient, reproducible, and more objective interpretation of 3D GPR data.

The challenges of signal interpretation of burials in ground‐penetrating radar

AbstractThe identification of unmarked graves and burials is one of most common applications of ground‐penetrating radar (GPR) in archaeology. Despite a high frequency of use and a long history of experimentation, there appears to be considerable variability on what indicates a burial in GPR data—likely a consequence of heterogeneity in geological contexts, age and in burial practices. Although general statements about uncertainty in GPR interpretation may be acceptable in archaeological applications, the interpretative process becomes more complicated when GPR is used to locate unmarked graves in culturally, politically and legally contested locations such as at former Indian Residential Schools (IRSs) in Canada. In this paper, we review international applications of the technique and identify trends and traits between the authors' use of GPR to identify burials. By categorizing the studies based on the GPR reflection signatures identified, our review demonstrates that there is modest consensus across the 77 documents reviewed for what represents a burial. Interrogating these findings, we identify a range of potential contributors to signal heterogeneity and outline potential steps forward to a higher confidence or more statistically robust identification of unmarked graves using GPR.

The impact of the Neoglacial and other environmental changes on the raised beaches of Joinville Island, Antarctica

AbstractIn order to reconstruct past environmental conditions along the north-eastern Antarctic Peninsula, we documented changes in grain size, grain roundness, onlap as seen in ground-penetrating radar reflection profiles and ice-rafted debris on a set of 36 raised beaches developed over the last ~7.7 ± 0.9 ka on Joinville Island. The most pronounced changes in beach character occur at ~2.7–3.0 ka. At this time, there appears to have been a reintroduction of less rounded material, the development of stratification within individual beach ridges, an introduction of seaweed and limpets to the beach deposits, a change in clast provenance (although slightly earlier than the change in cobble roundness) and a shallowing of the overall beach plain slope. Prolonged cooling associated with the Neoglacial period may have contributed to these changes, as the readvance of glaciers could have changed the provenance of the beach deposits and introduced more material, leading to the change in roundness of the beach cobbles and the overall slope of the beach plain. This study suggests that late Holocene environmental change left a measurable impact on the coastal zone of Antarctica.

Reconstruction of Holocene relative sea-level from beach ridges of the central west coast of India using GPR and OSL dating

The Holocene sea-level and associated shoreline regression of beach ridges in the central west coast of India have been reconstructed based on internal sedimentary architecture and luminescence chronology. For this purpose, various techniques namely ground penetrating radar (GPR), optically-stimulated luminescence (OSL) dating, and interferometry synthetic aperture radar (InSAR) have been used. The berm and beach-dune boundary of paleo beach ridges have been mapped from the high-resolution sub-surface images and converted into sea-level indicators using modern analogs and OSL ages. GPR reflection data shows a number of seaward dipping radar facies with a few landward dipping facies in paleo beach ridges. In the case of the swale, radar signal has been highly attenuated due to the presence of water and mud causing the appearance of multiple horizontal and parallel positive and negative couplets in the sedimentary layer. The results of the research reveal that the oldest beach ridge was formed around 7.7 kyr BP and sea-level was +2 m above mean sea-level. The average progradation rate of these ridges is 0.14 m/yr. From the grain size analysis, it has been found that the larger share of grain size falls into the classes of fine and moderate sand. The present displacement map of the region, which has been generated from the Sentinel-1 datasets, demonstrates that the average upliftment is 2.5 mm/yr whereas subsidence is 1 mm/yr. The fall of the Holocene relative sea-level with respect to the study region is the consequence of both global and regional events.

Ground Penetrating Radar to detect dinosaur bones within a Cretaceous hard limestone in Sicily

Ground Penetrating Radar (GPR) can be important in facilitating planning for the identification and extraction of buried vertebrate remains, particularly at sites that are difficult to access, where excavation would be costly and labor-intensive. This is the case at Grotta Lunga (northwestern Sicily), one of the southernmost European dinosaur sites, a key site for understanding the relationships between African and European dinosaurs. An incomplete theropod bone was discovered at this site in 2005, and to date there have been no further finds due to the difficulties of excavation in hard rock and in a cave environment. With the aim of exploring deeper into the rock volume around the bone, we tested GPR as a method to investigate the Cretaceous limestone at Grotta Lunga. Despite its potential, GPR has been rarely applied in paleontology and very seldom has led to the successful detection of buried dinosaur bones. Our analysis identified some remarkable GPR reflections on the cave wall, in the vicinity of the dinosaur bone, indicating the existence of reflective objects embedded in a position stratigraphically compatible with the dinosaur remains. Data processing was carried out to show the best result without compromising data quality. For this purpose we used the synthetic hyperbola method, Kirchhoff migration and Hilbert transform. The GPR signals detected at Grotta Lunga in the graphical form of hyperbolas are interpreted as the result of reflections produced by fossil bones embedded in the Cretaceous limestone investigated and indicate the presence of additional dinosaur remains. Our investigation provides useful information for planning future excavations.

Prediction of porosity and water saturation of chalks from combined refraction seismic and reflection ground-penetrating radar measurements

The prediction of porosity and water content of near-surface chalks is important for agricultural, environmental, hydrologic, and geologic engineering investigations. However, current methods based on laboratory measurements or crosshole ground-penetrating radar (GPR) are typically costly and applicable to only a limited area. We have combined the refraction seismic and reflection GPR data sets measured on the ground surface along a 96 m long profile line to predict the porosity and water saturation simultaneously. Using integrated rock-physics templates, we develop and apply a quantitative method that combines acoustic and electromagnetic velocities to estimate the petrophysical parameters of chalks. The seismic and GPR data are processed independently and subsequently combined to invert the porosity and water saturation. Field data tests demonstrate that the predicted results are consistent with laboratory measurements and field observations, demonstrating that the integration of seismic and GPR data facilitates efficient and reliable estimates of the porosity and saturation of chalks on scales relevant to regional field mapping. Hence, this method allows the petrophysical parameters of near-surface chalks to be evaluated efficiently at a regional scale.

Fast 3D ground penetrating radar simulations for glaciers

Modeling ground penetrating radar (GPR) reflection data on glaciers with methods that require the discretization of the full subsurface domain is extremely computationally expensive because of the combination of a large domain size and the comparatively short wavelength of the signal. To address this issue, we build on and extend a previously proposed approach based on the assumption of a homogeneous background medium (ice) in which various scattering objects (e.g., crevasses, channels, boulders) are embedded far from each other such that multiple scattering can be ignored. The glacier bed, below which no scatterers are assumed to exist, represents the lower limit of the modeling domain. With this method, the two-way propagation of the radar waves through the ice is simulated in a semi-analytical way, whereby scattering surfaces are represented with a set of planar elements of different electric and reflective properties, allowing a wide range of objects to be simulated. As we also take the antenna radiation pattern at the air-ice interface into account, this simple algorithm is able to produce realistic 3D GPR data in a fast and memory efficient way. In this study, we validate the presented algorithm with an analytical solution for a layered model, and we simulate radar data for a model of the Otemma glacier in Switzerland featuring a realistic topography of the glacier bed and a subglacial channel.

Inference of geostatistical hyperparameters with the correlated pseudo-marginal method

We consider non-linear Bayesian inversion problems targeting the geostatistical hyperparameters of a random field describing hydrogeological or geophysical properties given hydrogeological or geophysical data. This problem is of particular importance in the non-ergodic setting as there are no analytical upscaling relationships linking the data to the hyperparameters, such as, mean, standard deviation, and integral scales. Full inversion of the hyperparameters and the local properties of the field (typically involving many thousands of unknowns) brings substantial computational challenges, such that simplifying model assumptions (e.g., homogeneity or ergodicity) are typically made. To prevent the errors resulting from such simplified assumptions while also circumventing the burden of high-dimensional full inversions, we use a pseudo-marginal Metropolis–Hastings algorithm that treats the random field as latent variables. In this random effects model, the intractable likelihood of observing the data given the hyperparameters is estimated by Monte Carlo averaging over realizations of the random field. To increase the efficiency of the method, low-variance approximations of the likelihood ratio are obtained by using importance sampling and by correlating the samples used in the proposed and current steps of the Markov chain. We assess the performance of this correlated pseudo-marginal method by considering two representative inversion problems involving diffusion-based and wave-based physics, respectively, in which we infer the hyperparameters of (1) hydraulic conductivity fields using apparent hydraulic conductivity data in a data-poor setting and (2) fracture aperture fields using borehole ground-penetrating radar (GPR) reflection data in a more data-rich setting. For the first test case, we find that the correlated pseudo-marginal method generates similar estimates of the geostatistical mean as classical rejection sampling, while an inversion assuming ergodicity provides biased estimates. For the second test case, we find that the correlated pseudo-marginal method estimates the hyperparameters well, while rejection sampling is computationally unfeasible and a simplified model assuming homogeneity leads to biased estimates.

Structurally constrained inversion by means of a Minimum Gradient Support regularizer: examples of FD-EMI data inversion constrained by GPR reflection data

SUMMARYMany geophysical inverse problems are known to be ill-posed and, thus, requiring some kind of regularization in order to provide a unique and stable solution. A possible approach to overcome the inversion ill-posedness consists in constraining the position of the model interfaces. For a grid-based parameterization, such a structurally constrained inversion can be implemented by adopting the usual smooth regularization scheme in which the local weight of the regularization is reduced where an interface is expected. By doing so, sharp contrasts are promoted at interface locations while standard smoothness constraints keep affecting the other regions of the model. In this work, we present a structurally constrained approach and test it on the inversion of frequency-domain electromagnetic induction (FD-EMI) data using a regularization approach based on the Minimum Gradient Support stabilizer, which is capable to promote sharp transitions everywhere in the model, i.e., also in areas where no structural a prioriinformation is available. Using 1D and 2D synthetic data examples, we compare the proposed approach to a structurally constrained smooth inversion as well as to more standard (i.e., not structurally constrained) smooth and sharp inversions. Our results demonstrate that the proposed approach helps in finding a better and more reliable reconstruction of the subsurface electrical conductivity distribution, including its structural characteristics. Furthermore, we demonstrate that it allows to promote sharp parameter variations in areas where no structural information are available. Lastly, we apply our structurally constrained scheme to FD-EMI field data collected at a field site in Eastern Germany to image the thickness of peat deposits along two selected profiles. In this field example, we use collocated constant offset ground-penetrating radar (GPR) data to derive structural a priori information to constrain the inversion of the FD-EMI data. The results of this case study demonstrate the effectiveness and flexibility of the proposed approach.

Weighted Diffraction-Based Migration Velocity Analysis of Common-Offset GPR Reflection Data

Migration focusing analysis of diffractions is an increasingly important tool for estimating the large-scale subsurface velocity structure from surface-based common-offset ground-penetrating radar (GPR) reflection data. We present a weighting strategy, whose aim is to improve the reliability of estimations of the root-mean-square (rms) velocity obtained using a local semblance focusing measure. In this regard, we increase the resolution of the inferred semblance spectra through a weighting function that varies in accordance with the sensitivity of a diffraction curve to changes in velocity. The weighting function is derived from coherency and slope attributes of the diffracted wavefield components. To demonstrate the viability of our proposed method, we consider its application in two synthetic test cases and one field GPR dataset. Compared with conventional unweighted local semblance spectra, their weighted counterparts allow for a significantly increased resolution and correspondingly reduced picking uncertainty.

Estimating porosity distribution of a heterogeneous alluvial aquifer by GPU-accelerated 3D conditional stochastic inversion of common-offset GPR reflection data

Three-dimensional (3D) high-resolution and accurate characterization of the heterogeneity in an alluvial aquifer is critical to predicting the groundwater flow and contaminant transport. In this study, we extend the previous 2D conditional stochastic inversion method with respect to common-offset ground-penetrating radar (GPR) data to 3D for the estimation of 3D porosity distribution in a heterogeneous alluvial aquifer. First, 3D stochastic realizations of subsurface properties can be obtained using the fast Fourier transform moving average (FFT-MA) method, and the realizations are conditioned to borehole porosity measurements available in the 3D survey area, as well as to the geostatistical parameters derived from the borehole logs and the processed 3D GPR data. Next, the realizations are constantly modified and regenerated via a localized simulated annealing optimization strategy, which ultimately makes their corresponding synthetic data offer an acceptable fit to the GPR data. To accelerate the computational speed of 3D inversion, we design and implement the multi-GPUs multi-node parallelization of the 3D conditional stochastic inversion algorithm. The proposed 3D inversion algorithm is positively verified through the application to field GPR data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA. Our results indicate that the proposed 3D inversion method has the potential to effectively recover the fine-scale porosity distribution of a heterogeneous alluvial aquifer.

THE CAESAREA GERMANICIA (?) OF ARCHEOGEOPHYSICAL INVESTIGATIONS

The remains unearthed in the Dulkadiroğlu district, one of the central districts of Kahramanmaraş, are thought to belong to Caesarea Germanicia, which was founded in the Roman Period. Research and excavations carried out by the Kahramanmaraş Museum and us in the region have revealed that the spread of archaeological cultural remains is more than 150 hectares. Although the concentration of Roman Period cultural remains in the research and excavations was remarkable, the discovery of Byzantine, Seljuk, and Ottoman Period ceramic pieces indicates an uninterrupted settlement in the research area for centuries. However, as can be seen in the images, the dense residential texture in the region is one of the biggest obstacles to archaeological research and excavations. Because, in order to carry out archaeological excavations of the identified structures, expropriations are required. However, the expropriation period covers an average of 2-4 years, which makes it difficult to conduct scientific research. Archeogeophysical methods provide information about the location, depth, and dimensions of the archaeological remains by applying them from the surface, without causing any damage to the archaeological remains sought. In this context, Ground Penetrating Radar (GPR) measurements were carried out to determine the quality of the mosaic-based structure on 445 layout, which were previously unearthed through illegal excavations in 2019, and the parcels on which it extends. GPR was carried out along 6 profiles. The obtained results were compared both with each other and with the existing surface conditions, and GPR depth maps were created. When the GPR depth sections were examined, 4 important reflections were found. It has been interpreted that 3 of these reflections belong to the archaeological building remains and 1 of them originates from a metal material (pipe). It was determined that the depth of the archaeological remains identified in the GPR sections started at a depth of approximately 20 cm. As a result of the excavation, it was seen that the reflections determined in the GPR sections belonged to the wall remains and metal pipe. As a result of archaeological excavations, it was determined that the GPR reflections belong to the remains of the walls of the Villa Rustica of the Early Byzantine Period or a Roman bath, as well as a metal pipe. In the measurements of the ground radar, it was determined that other walls cut the building walls in parallel. As a result of archaeological excavations, it was understood that these walls were made of rubble stone with mud additives. It was discovered during archaeological excavations and was discovered in the 11th-13th centuries AD. One of the ceramic fragments indicates that this structure was used again in the Middle Byzantine Period.

Analysis of subsurface velocity using CMP gathers picked up by unshielded GPR system: results from an experimental NAPL contaminated test site

Adequate knowledge of velocity is required for accurate data imaging and depth conversion, as well as for quantifying the distribution of soil water content. Without complementary borehole information in the form of dielectric permittivity and/or porosity logs along the profile, it is currently impossible to reliably estimate the high-frequency electromagnetic velocity distribution in the probed subsurface region. Here, we present a new method for calculating the precise subsurface velocity structure from ground penetrating radar (GPR) reflection data that does not require boreholes or log data. This study investigates the ability of the pulse_EKKO PRO GPR system to predict a vertical profile for the possible velocity estimation of a layered and contaminated geophysical test site in Hangzhou, China. All data were acquired and saved on the GPR system in various files (projects) before analysis using GPR software to obtain approximated velocity modelling using common midpoint (CMP) gathers. Using the velocity spectrum analysis, a vertical profile of the interval velocities can be derived from each CMP gather. The findings of this study indicate that the proposed method is effective and sustainable. Furthermore, owing to the efficacy of the method in terms of field effort and computational complexity, it can easily be expanded to 3D GPR velocity exploration, increasing its importance in comparison to standard offset-based techniques for estimating velocity using GPR.

Ground‐penetrating radar investigations of the Asaviec 2 archaeological site, Northern Belarus

AbstractAsaviec 2 in the Kryvina wetland is one of the best known and the most thoroughly investigated Stone and Bronze Age lake settlement sites in Northern Belarus. Previously, research on the site used excavations and coring, typological analysis and radiocarbon dating of the find material, as well as stratigraphic, lithological and palynological analyses. However, geophysical methods were not used. This study was carried out to test the use of ground‐penetrating radar (GPR) both at this particular site and in peaty sediments generally. The main goal was to determine the lateral spread of the occupation layer and traces of ancient habitation activity. The GPR reflection profiles have been correlated with coring data and previously excavated archaeological profiles. The chaotic pattern in the GPR reflection profiles has been interpreted as disturbed peat, thereby indicating human activity. The areas of disturbed peat and the lower boundary of the peat body were traced and mapped. The occupation layer and signs of human activity are irregularly distributed and largely coincide with the high and intermediate forms of the subsoil relief, but not with the low forms. As a result, we have concluded that GPR is a valuable tool for determining occupational layers in wetlands when verified by excavations and coring.

The Deserted Manor of Noer, Schleswig-Holstein, Germany. Geophysical Prospection Methods in Comparison

Manors are an important component of the cultural-economic history of Northern Germany and Southern Scandinavia. We present the results of a geophysical prospection that led to the identification of a previously unknown manor near the village of Noer, Schleswig-Holstein, Northern Germany. Although magnetic gradiometry provides a fast way to cover large areas, it does not provide accurate depth estimates, is affected by magnetic blanking and is unable to detect differences in water content. Therefore, we applied a combination of different geophysical methods to optimize the non-invasive reconstruction of the target and its surroundings not only with respect to building structures but also in relation to the surrounding landscape. In particular, a combination of magnetics, ground-penetrating radar (GPR), electromagnetic induction (EMI), electrical resistivity tomography (ERT), and soil samples were carried out to determine: (1) the object's exact location; (2) the building structure and state of preservation; and (3) any additional structures in the surrounding area. We detected a tripartite building of 22 by 27 m, with several inner walls, which was located underneath a topographic high on the surveyed field. The bulk structure is identifiable most clearly in the magnetic and EMI inphase component maps. GPR profiles and soil samples indicate flooring or foundations in part of the building. Their shallow depths of less than 2 m below the surface and debris clusters close to the surface indicate at least partial demolition. A surrounding wall was found about 5 m outside the building. The area in between shows no magnetic anomalies, lower resistivities in EMI and ERT, and low GPR reflection amplitudes. Soil samples suggest a moat or other water feature. Archaeological artifacts found at the location characterize the building as a 16th to 17th century brick manor. Other objects, like a suspected farmyard and access path could not be found. A comparison with historical sources suggest that the mansion is in relation to the manor Grönwohld. After a change of the owner it was degraded to a Meierhof, and subsequently the building decayed and was forgotten.

High-resolution velocity estimation from surface-based common-offset GPR reflection data

SUMMARY Surface-based common-offset ground-penetrating radar (GPR) reflection profiling is a popular geophysical exploration technique for obtaining high-resolution images of the shallow subsurface in a cost-effective manner. One drawback of this technique is that, without complementary borehole information in form of dielectric permittivity and/or porosity logs along the profile, it is currently not possible to obtain reliable estimates of the high-frequency electromagnetic velocity distribution of the probed subsurface region. This is problematic because adequate knowledge of the velocity is needed for accurate imaging and depth conversion of the data, as well as for quantifying the distribution of soil water content. To overcome this issue, we have developed a novel methodology for estimating the detailed subsurface velocity structure from common-offset GPR reflection measurements, which does not require additional conditioning information. The proposed approach combines two key components: diffraction analysis is used to infer the smooth, large-scale component of the velocity distribution, whereas the superimposed small-scale fluctuations are inferred via inversion of the reflected wavefield. We test and validate our method on two synthetic data sets having increasing degrees of complexity and realism before applying it to a field example from the Boise Hydrogeophysical Research Site, where independent control data in the form of neutron–neutron porosity logs are available for validation. The results obtained demonstrate the viability and robustness of the proposed approach. Further, due to its efficiency, both in terms of field effort and computational cost, the method can be readily extended to 3-D, which further enhances its attractiveness compared to multi-offset-based GPR velocity estimation techniques.

Geophysical investigations in the Radovna River Spring area (Julian Alps, NW Slovenia)

vodeAbstractThe Radovna River Valley is located in the north-western part of Slovenia in the Julian Alps, where there is an extensive intergranular aquifer whose depth to pre-Quaternary bedrock is unknown. Therefore, to obtain information about the depth of the valley and the geometry of the aquifer two geophysical methods were used in our study; ground penetrating radar (GPR) and seismic reflection method. The low-frequency GPR method has shown to be useful for determining the depth of the groundwater and the predominant groundwater recharge. Also, the high-resolution seismic method provided an insight about the morphology of the pre-Quaternary basement with the deepest point at 141 meters below surface. Measurements of hydrogeological parameters such as groundwater level and river discharge measurements were carried out in the study area. Both data analyses showed that groundwater level and river discharge are highly fluctuating and rapidly changing, indicating a well-permeable aquifer, implying that such an aquifer is extremely sensitive and vulnerable to extreme climate events. Both the geophysical methods and the hydrogeological information have provided important information about the morphology of the valley and the alluvial aquifer, as well as increasing the knowledge about the Radovna springs system, which will contribute very important information for future hydrogeological studies.

GEO-RADAR LNAPL MODEL BY ARTIFICIAL INTELLIGENT

Ground Penetrating Radar (GPR) as non-destructive measurement of full-wave electromagnetic(EM) backscatter completely relies on dielectric permittivity. Interpreting GPR reflection configuration is a complex qualitative with positioning and depth determination would be misleading due to severe polarization and velocity mismatch in travelling-wave. As a result of these studies, a GPR signal segmentation algorithm model was developed to map and identify light non-aqueous liquid (LNAPL) contaminated in laterite soil utilizing dielectric permittivity prediction. Simultaneous registration of a Global Positioning System (GPS) signal was performed while acquiring georeferenced GPR data sets to pinpoint the appropriate location of the soil layers. In this way, georeferenced GPR dispersion was assessed and dielectric permittivity was retrieved by velocity extraction. Empirical model relationship was established by the higher-order regression. Calibration function used verification measurement with root mean square error (RMSE) and calibrated Performance Network Analyzer (PNA). Segmentation and classification using Support Vector Machine (SVM) classifier as Artificial Intelligence (AI) was executed using predicted dielectric permittivity to construct the GPR automated recognition model. The model was compared with actual data and logistic regression classification. The result shows both classification techniques have provided good quality with root mean square errors (RMSE), which were 0.1391 and 0, respectively. The classification produces correct instances classified above 98% for SVM and 100% for logistic regression.

Integrating electrical resistivity tomography and ground‐penetrating radar methods to map archaeological walls near northern Ishtar gate, ancient Babylon city, Iraq

AbstractElectrical resistivity tomography (ERT) and ground‐penetrating radar (GPR) were collected on the eastern side of the northern Ishtar gate in ancient Babylon, Iraq, to locate the palace wall and other surrounding walls. Due to the presence of a low resistivity (highly conductive) top layer associated with brick rubble and other debris, the GPR reflection profiles show a high‐energy attenuation, but a series of processing and filtering steps produced coherent reflections of about 2 m depth. Profile analysis shows the geometry and layering of the walls and the surrounding matrix. With the ERT, the surface conductive zone produces various distortions in ERT inverse models, making identifying the features' lower boundaries difficult. Here, we suggest that instead of analysing these two data sets independently, the integration of both reveals not just the walls but their composition and defines material in the surrounding units. This integration shows how the interpretation of the shallow features on the 3D ERT maps is improved by comparison and interpretation in conjunction with the reflections visible on both reflection profiles and the 3D GPR amplitude slices. The orientation of these features and reflections emphasizes the existence of one series of buried walls at a depth of 90–150 cm. The thickness of these walls varies between 0.25 and 1 m. Another wall‐like feature is visible only on 3D ERT maps and not with the 3D GPR slices at 2 m depth, which indicates a thickness of 11 m. It is interpreted as the palace wall, which is consistent with earlier archaeological excavations. An analysis of the geometry and composition of both wall components, perhaps of different ages, and constructed for different reasons, indicates that some shallower walls may be the remains of rooms built as residences for soldiers, or they may belong to the other ruins of northern Ishtar gate.