Ground Penetrating Radar Technique Research Articles

Detection and delineation of cracks and voids in concrete structures using the ground penetrating radar technique

The accurate detection of early-age cracking and voids in concrete structures is vital for assessing their health and preventing deterioration, ultimately saving lives and resources. While Ground Penetrating Radar (GPR) offers a widely used method for concrete inspection and defect detection, its accuracy is subject to various limitations influenced by factors such as software, defect dimensions, moisture, and the analysis and interpretation of data. This study presents comprehensive techniques for detecting, delineating, and analyzing hidden cracks and voids in concrete using GPR, validated through laboratory testing and real-world applications. Introducing “DefectInspectoPy,” Python software, aims to address limitations in traditional GPR data processing software and defect detection methods. Results demonstrate the effectiveness of the proposed methods in accurately locating, analyzing, and delineating defects, aiding in determining coring locations for concrete structures. These findings have significant implications for enhancing safety, reducing maintenance costs, and preserving concrete infrastructure integrity.

Recent Advances in Dielectric Properties-Based Soil Water Content Measurements

Dielectric properties are crucial in understanding the behavior of water within soil, particularly the soil water content (SWC), as they measure a material’s ability to store an electric charge and are influenced by water and other minerals in the soil. However, a comprehensive review paper is needed that synthesizes the latest developments in this field, identifies the key challenges and limitations, and outlines future research directions. In addition, various factors, such as soil salinity, temperature, texture, probing space, installation gap, density, clay content, sampling volume, and environmental factors, influence the measurement of the dielectric permittivity of the soil. Therefore, this review aims to address the research gap by critically analyzing the current state-of-the-art dielectric properties-based methods for SWC measurements. The motivation for this review is the increasing importance of precise SWC data for various applications such as agriculture, environmental monitoring, and hydrological studies. We examine time domain reflectometry (TDR), frequency domain reflectometry (FDR), ground-penetrating radar (GPR), remote sensing (RS), and capacitance, which are accurate and cost-effective, enabling real-time water resource management and soil health understanding through measuring the travel time of electromagnetic waves in soil and the reflection coefficient of these waves. SWC can be estimated using various approaches, such as TDR, FDR, GPR, and microwave-based techniques. These methods are made possible by increasing the dielectric permittivity and loss factor with SWC. The available dielectric properties are further synthesized on the basis of mathematical models relating apparent permittivity to water content, providing an updated understanding of their development, applications, and monitoring. It also analyzes recent mathematical calibration models, applications, algorithms, challenges, and trends in dielectric permittivity methods for estimating SWC. By consolidating recent advances and highlighting the remaining challenges, this review article aims to guide researchers and practitioners toward more effective strategies for SWC measurements.

Mapping and monitoring peatlands in the Belgian Hautes Fagnes: Insights from Ground-penetrating radar and Electromagnetic induction characterization

Peatlands are vital ecosystems providing crucial ecological services such as significant carbon storage in the context of climate change. These sensitive ecosystems are subjected to degradation due to land use change. In this context, it is important to understand the actual state of degraded peatlands and their recovery potential for regaining important functions. This study focuses on a disturbed peatland in the Belgian Hautes Fagnes, previously drained and planted with spruce, and characterized by a topographic gradient. We aimed to elucidate the use of Ground-penetrating radar (GPR) and Electromagnetic induction (EMI) techniques in characterizing such peatlands, with a specific focus on their implications for peat depth and electrical conductivity assessment, related to peatland degradation. The GPR revealed a high spatial heterogeneity in peat depth, ranging from 0.2 to more than 2 m on the site. In contrast, an EMI instrument used with single coil spacing proved to be unsuccessful to deduce peat depth but demonstrated potential for the delineation of zones of mineral soil. It is also shown that the links between soil physical and chemical properties and its bulk soil electrical conductivity (ECa) measured by EMI are complex in zones of shallower peat. Additionally, this study highlights the role of pore water conductivity in influencing temporal variations in ECa. Our findings explain the intricate interplay between peat depth, topography and ECa in disturbed peatlands. The results of this study may be of substantial societal interest, as it provides insights into techniques for the rapid non destructive characterization of the conditions of previously drained peatlands.

Identification of Complex Slope Subsurface Strata Using Ground-Penetrating Radar

Identification of slope subsurface strata for natural soil slopes is essential to assess the stability of potential landslides. The highly variable strata in a slope are hard to characterize by traditional boreholes at limited locations. Ground-penetrating radar (GPR) is a non-destructive method that is capable of capturing continuous subsurface information. However, the accuracy of subsurface identification using GPRs is still an open issue. This work systematically investigates the capability of the GPR technique to identify different strata via both laboratory experiments and on-site examination. Six large-scale models were constructed with various stratigraphic interfaces (i.e., sand–rock, clay–rock, clay–sand, interbedded clay, water table, and V–shaped sand–rock). The continuous interfaces of the strata in these models were obtained using a GPR, and the depths at different points of the interfaces were interpreted. The interpreted depths along the interface were compared with the measured values to quantify the interpretation accuracy. Results show that the depths of interfaces should be interpreted with the relative permittivity, back-calculated using on-site borehole information instead of empirical values. The relative errors of the depth of horizontal interfaces of different strata range within ±5%. The relative and absolute errors of the V–shaped sand–rock interface depths are in the ranges of [−9.9%, 10.5%] and [−107, 119] mm, respectively. Finally, the GPR technique was used in the field to identify the strata of a slope from Tanglang Mountain in China. The continuous profile of the subsurface strata was successfully identified with a relative error within ±5%.

Geological detection of hard rocks by GPR and signal time-frequency characteristics analysis in urban underground trenchless construction

Abstract The hard rocks in the stratum can pose safety risks and hinder the progress of urban underground tunnel construction using shield and jacking methods, thereby reducing construction efficiency and increasing construction costs. This paper utilizes wavelet scale energy spectrum, wavelet packet theory and statistical methods to conduct research on the detection of special geological formations such as hard rocks and voids, as well as the analysis of their signal time-frequency characteristics based on the ground-penetrating radar (GPR) technique. On the basis of calibrating the permittivity of different types of rock blocks, we established a forward model for detecting hard rocks and voids, and the simulated signals were analyzed in the time and frequency domains. Subsequently, laboratory experiments were conducted to perform GPR tests on different types of hard rocks in natural and water-saturated states and voids, to explore the time-frequency characteristics, frequency band energy variations, and statistical patterns of typical single-trace signals. The results show that the granite detection signal contains more low-frequency components, the sandstone detection signal contains more medium-low frequency components, while the limestone detection signal contains more medium-high frequency components in their natural state; the signal from the karst cave has relatively more low-frequency components than the signal from the empty cavity. The geometric shape of the rock has no influence on the dominant frequency and time-frequency distribution of its reflection signal. Generally, rocks with higher rebound values (hardness) also exhibit larger variance and standard deviation in frequency band energy. The research has important theoretical significance and practical value for the measurement and assessment of special geological features such as hard rocks and voids in urban underground trenchless construction.

Unveiling a hidden fortification system at “Faraglioni” Middle Bronze Age Village of Ustica Island (Palermo, Italy) through ERT and GPR prospections

We carried out a geophysical research project in the Middle Bronze Age village of Ustica (Palermo, Sicily, Italy), named “Faraglioni Village” after the stack formations which detach from the coast north of the archaeological site. The investigation, which comprised Electrical Resistivity Tomography (ERT) and Ground Penetrating Radar (GPR) techniques, allowed us to discover the buried foundations of an outwork fortification system never evidenced by previous archaeological studies, only hypothesised from the observation of aerial photography and partially outcropping boulders, which align roughly parallel to the main defensive wall of the Village.Our geophysical prospection involved the entire 250 m-long arc of the outward village defensive wall, with the acquisition of eleven ERT profiles and 27 GPR scans. The techniques were selected based on both favourable logistics and methods applicability: ERT sections allowed us to trace a series of high-resistivity anomalies arranged to form an arc-shaped structure along the perimeter of the defensive wall. GPR investigation was localised in the most accommodating patch of terrain of the site, with the effort of intercepting clear enough sections of the target, to determine more accurately its shape, depth, and overall dimensions. Our discovery paves the way for new investigations, mainly aimed at defining the timing of construction of the fortification system, as well as the function of the remains of other architectural structures identified close to the wall, which could represent the target of further geophysical investigations.

Detection for severe caves and sinkholes in non-clastic rock type using GPR technique

ABSTRACT This study examines the application of Ground Penetrating Radar (GPR) to the detection of severe caverns and sinkholes in non-clastic rock formations. Due to the presence of vertically sloping bedrock, cavities, and sinkholes, geotechnical engineers face significant challenges when designing and constructing foundations in karstic formations such as limestone. The territory under investigation is located close to the Giza limestone plateau, the northern side of which has experienced severe stability issues. The ground-penetrating radar (GPR) method was used to identify the presence and extent of exposed caves and caverns in the studied region. The research area’s geological and geomorphological background is explored, including the creation of primary and secondary caves, as well as solution caves generated by the breakdown of soluble rocks like limestone. Data collecting, processing, and interpretation procedures used in the GPR survey are described. GPR survey findings revealed the existence of a severe cave and many minor sinkholes in the studied region. GPR has shown to be a useful and efficient tool for determining geometric karst features in the subsurface, helping to a better evaluation of the dangers associated with this geological environment.

GPR and Magnetic Techniques to Locate Ancient Mining Galleries (Linares, Southeast Spain)

Old mining districts have created numerous subsurface cavities, often at shallow depths. The resulting subsidence risk is a major territorial planning problem, especially when these holes are in urban expansion areas. Ground-penetrating radar (GPR) and magnetic techniques can help to detect and to characterise these shallow mining structures based on the strong contrast of electromagnetic and magnetic properties (dielectric constant and magnetic susceptibility) between the rock and the backfill of cavities. In the present study, these techniques were used to locate old mining cavities near the city of Linares, located south of Spain and connected to the area’s old mining district. GPR and magnetometry (total magnetic field and vertical magnetic gradient) were performed on a grid in one of the most important veins in the sector. By comparing both working methods, the vein structure within the granite can be detected. On the one hand, the magnetic prospecting technique (magnetic anomalies) has allowed us to detect when the vein is covered by metallic elements of natural or anthropogenic origin. On the other hand, strong reflections and hyperbolic events associated in GPR profiles confirm the presence of cavities related to old mining operations. Shallow magnetic anomalies not associated to GPR variations are related to the slag present in the study area (detected in the outcrop) or to unexploited vein mineralizations.

Probabilistic coastal wetland mapping with integration of optical, SAR and hydro-geomorphic data through stacking ensemble machine learning model

The present study focuses on preparing the wetland map using earth observation data and applying a novel ensemble model. Eight advanced machine learning algorithms were applied to determine the probability of the occurrence of wetlands. The random forest (RF), support vector machine (SVM), and multivariate adaptive regression spline (MARS) models outperformed others. So, these models were further used to create a stacking ensemble for improving precision. The RF-SVM-MARS ensemble model was run with seven various parameters. The results show that the integrated parameter has the highest area under the curve (0.960) followed by optical-hydrogeomorphic (0.953), SAR-hydrogeomorphic (0.940), hydrogeomorphic (0.896), SAR-optical (0.892), optical (0.881), and SAR (0.702). The hydrogeomorphic variables exhibited greater influence than the optical and SAR variables. However, the integration of all selected key variables proved to be the most effective approach for probabilistic wetland mapping. The RF-SVM-MARS ensemble model can improve classification accuracy as compared to a single model. An accuracy of 96% was obtained when the ensemble model output was cross-validated with field data. The ground-penetrating radar (GPR) tool was also successfully employed to study the sub-surface strata and water level conditions in wetland and non-wetland areas. The successful application of a new ensemble approach along with the GPR technique for coastal wetland mapping in this study could encourage researchers to choose it as an appropriate methodology. Moreover, the outcomes of the work will help land-use planners and government agencies for better planning, monitoring, and promoting sustainable development of the coastal area.

The use of ground penetrating radar (GPR) method in the evaluation of soil moisture content of parts of cross river central soil for precision agriculture in South-south Nigeria

Using a single offset of the GPR technique, the soil moisture content in the study areas has been satisfactorily characterized. The average water content of selected soils in the Central region of Cross-River State ranges from 0.24m3m-3 to 0.35m3m-3. The majority of the soil in the research area is loamy soil, which has little sand and silt particles, claims the study. The majority of loamy soil is made up of sand, silt, and a small amount of clay. When dry, loamy soil has the consistency of concrete and when wet, it turns into a sticky mess. The majority of plants and vegetables can be grown on loam soil rather than other types of soil. Since loam contains almost equal amounts of all three of these components, it is the best type of soil. In conclusion, some of the Central Cross River State's soils would be suitable for farming.

Using InSAR and GPR Techniques to Detect Subsidence: Application to the Coastal Area of “A Xunqueira” (NW Spain)

Climate change represents an important cause of subsidence, especially in coastal cities affected by changes in surface water level and water table. This paper presents a complementary study of Interferometric Synthetic Aperture Radar (InSAR) and Ground Penetrating Radar (GPR) for the early detection of subsidence and sinkhole phenomena. The methodology was applied to a coastal urban area in Galicia, northwest Spain (humid region), showing apparent signs of subsidence and building settlement during the last two years. Two different InSAR methods are compared for the period from June 2021 to March 2022: PSI (Persistent Scatterer Interferometry) and SBAS (Small Baseline Subsets), and the average deformation velocities obtained resulted in −3.0 mm/yr and −4.1 mm/yr, respectively. Additional GPR data were collected in January 2022 to validate the InSAR results, which detected subsidence in agreement with the persistent scatters obtained from the PSI method. This is crucial information to plan preventive maintenance.

GAN-Based Inversion of Crosshole GPR Data to Characterize Subsurface Structures

The crosshole ground-penetrating radar (GPR) technique is widely used to characterize subsurface structures, yet the interpretation of crosshole GPR data involves solving non-linear and ill-posed inverse problems. In this work, we developed a generative adversarial network (GAN)-based inversion framework to translate crosshole GPR images to their corresponding 2D defect reconstruction images automatically. This approach uses fully connected layers to extract global features from crosshole GPR images and employs a series of cascaded U-Net structures to produce high-resolution defect reconstruction results. The feasibility of the proposed framework was demonstrated on a synthetic crosshole GPR dataset created with the finite-difference time-domain (FDTD) method and real-world data from a field experiment. Our inversion network obtained recognition accuracy of 91.36%, structural similarity index measure (SSIM) of 0.93, and RAscore of 91.77 on the test dataset. Furthermore, comparisons with ray-based tomography and full-waveform inversion (FWI) suggest that the proposed method provides a good balance between inversion accuracy and efficiency and has the best generalization when inverting actual measured crosshole GPR data.

Integrating GPR with ArcGIS Pro to map the Central Arkansas Water pipelines beneath the old Broadway Bridge, Little Rock

Central Arkansas Water (CAW) supplies fresh water to nearly 500,000 people in Arkansas. To prevent service interruptions and costly damages, the pipes and other potential utilities must be precisely located and mapped in three areas designated by the Arkansas Department of Transportation (ARDOT) prior to any excavation work. This research aimed to integrate Ground Penetrating Radar (GPR) with ArcGIS Pro to assist with locating, mapping, and analyzing the utility lines. The results of this study indicate that integrating GPR with ArcGIS Pro can be an efficient tool to locate, map, and analyze utility lines with great precision. The GPR technique was effective in locating the CAW pipelines and other subsurface utility lines at depths ranging from a few centimeters to less than two meters at the selected sites. ArcGIS Pro was highly effective in accurately mapping and analyzing both the detected and existing utilities in 2D and 3D spaces, providing comprehensive visualizations and analysis tools for the CAW service area. The findings of this study suggest that GPR, with ArcGIS Pro, could help protect utility infrastructure, reduce the cost of maintenance, and help with implementing mitigation strategies.

Ground-Penetrating Radar and Electromagnetic Induction: Challenges and Opportunities in Agriculture

Information on the spatiotemporal variability of soil properties and states within the agricultural landscape is vital to identify management zones supporting precision agriculture (PA). Ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques have been applied to assess soil properties, states, processes, and their spatiotemporal variability. This paper reviews the fundamental operating principles of GPR and EMI, their applications in soil studies, advantages and disadvantages, and knowledge gaps leading to the identification of the difficulties in integrating these two techniques to complement each other in soil data studies. Compared to the traditional methods, GPR and EMI have advantages, such as the ability to take non-destructive repeated measurements, high resolution, being labor-saving, and having more extensive spatial coverage with geo-referenced data within agricultural landscapes. GPR has been widely used to estimate soil water content (SWC) and water dynamics, while EMI has broader applications such as estimating SWC, soil salinity, bulk density, etc. Additionally, GPR can map soil horizons, the groundwater table, and other anomalies. The prospects of GPR and EMI applications in soil studies need to focus on the potential integration of GPR and EMI to overcome the intrinsic limitations of each technique and enhance their applications to support PA. Future advancements in PA can be strengthened by estimating many soil properties, states, and hydrological processes simultaneously to delineate management zones and calculate optimal inputs in the agricultural landscape.

Radar Observation of the Lava Tubes on the Moon and Mars

The detection of lava tubes beneath the surfaces of the Moon and Mars has been a popular research topic and challenge in planetary radar observation. In recent years, the Moon–based ground penetrating radar (GPR) carried by the Chinese Chang’e–3/–4 mission, the RIMFAX radar carried by the Mars mission Perseverance, and the RoSPR radar and MOSIR radar carried by China’s Tianwen–1 orbiter have extensively promoted the exploration of the underground space of extraterrestrial bodies, which is crucial for the future utilization and development of these spaces. This paper expounds on the principles, methods, and detection results of using GPR to detect lava tubes on the Moon and Mars. First, lava tubes’ formation mechanism and morphological characteristics are outlined, followed by an introduction to GPR’s working principles and classification. The advantages, disadvantages, and prospects of different types of radar in detecting the lava tubes are analyzed. Finally, the distribution of lava tubes on the Moon and Mars is briefly summarized, and the potential utilization of lava tubes is discussed. We believe that the GPR technique is an effective geophysical method for exploring the underground structures of the Moon and Mars, and the lava tubes beneath the surface of extraterrestrial bodies can provide important references for selecting future Moon and Mars bases.

Three-Dimensional Modeling and Non-Invasive Diagnosis of a Huge and Complex Heritage Building: The Patriarchal Basilica of Santa Maria Assunta in Aquileia (Udine, Italy)

Three-dimensional modeling and non-invasive diagnosis are fundamental prerequisites for planning reliable assessments of the seismic vulnerability, renovation and conservation of heritage buildings. In the case of multi-layered, huge and complex ancient constructions, various problems can be encountered in the early design phases of interventions, among which there is often a lack of an adequate building documentation. Such issues include drawings that are without a metric scale, not detailed, not updated or not reflecting the real situation. In addition, the fragility of these constructions requires an accurate census of every sign of deterioration in order to prepare an ad hoc intervention for the site. As an example, in this paper, the results of a survey regarding the Patriarchal Basilica of Santa Maria Assunta (Aquileia, Italy) are reported. The basilica has a rich history of about two thousand years. in which each era has marked the actual architectural layout with its own culture and art. The result is an intricate association of complementary and/or interdependent elements that make the building very complex. Given the need to obtain accurate documentation, a realistic representation and a simulation of the criticalities of the structure, which previously did not exist or were not sufficiently accurate, a multi-methodological and multi-scale diagnosis was performed. In detail, the ground-penetrating radar (GPR) technique was applied to verify the presence of structures still buried under some internal surfaces, and a topographic survey, terrestrial laser scanning (TLS), and structure for motion (SfM) aerial and terrestrial photogrammetry were integrated for the detailed survey of the entire internal and external macro-structure. The resulting outcome provided the comprehensive information needed for preparing projects for the preservation, management and restoration of the basilica and the buildings connected to it.

Machine learning-based detection of transportation infrastructure internal defects using ground-penetrating radar: a state-of-the-art review

Abstract Early detection of internal defects is crucial to ensure the long-term performance and stability of transportation infrastructure. Researchers and practitioners have developed various nondestructive testing (NDT) methods for this purpose. Among them, the ground-penetrating radar (GPR) technique has been widely implemented due to its advantages such as large coverage, traffic-speed survey, and rich subsurface information. In addition, machine learning (ML) algorithms have been frequently applied to achieve automatic GPR data interpretations, which are essential for field applications. However, the fundamental concepts, architectures, and appropriate application scenarios of these algorithms are often questionable to practitioners and researchers. This paper presents a state-of-the-art review of ML applications in the internal defect detection of transportation infrastructure using GPR. In particular, pavements and bridges are covered. The basic knowledge of GPR working principles and ML algorithms is documented. The critical features of the ML algorithms for each detection task are presented. The drawbacks that may hinder the application of ML algorithms using GPR are indicated, including the insufficiency of labeled GPR data, unavailability of GPR dataset, customized ML architecture, and field validation. Finally, possible transfer learning, integrated robotic platform, and data fusion with other NDT methods are discussed. This review paper is expected to serve as a reference for practitioners to choose appropriate ML algorithms to detect internal defects in transportation infrastructure using GPR.

Detection and quantitative evaluation of pumping distress on bridge deck pavement through field and laboratory experiments

Pumping distress refers to the phenomenon of dynamic water entering a pavement, soaking the cement concrete layer to form slurry, and being pumped out of the pavement void under the action of traffic loading. Pumping distress is frequently reported in high temperature and rainy regions, such as Sichuan province in China. Various factors contribute to pumping distress on bridge decks, but most of these factors have merely been subjected to qualitative assessment. The aim of the study is to conduct a comprehensive quantitative analysis through three years of field investigations and laboratory experiments. The field investigations include ground penetrating radar (GPR), pavement permeability tests, skid resistance tests, and drainage facilities surveys. The quantitative analysis of the field and laboratory inspections revealed that the formation reason, deterioration rate, and damage degree of pumping distress were different between the truck and emergency lanes. The occurrence of pumping distresses was significantly related to the uneven construction of the bridge deck leveling layer, compaction segregation, and poor drainage. Additionally, the influence of pavement thickness uniformity on pumping distress was evaluated by incorporating GPR techniques. Failure in the waterproof adhesion layer resulted in the barrier between the cement concrete deck and the asphalt mixture breaking, which allowed alkaline sources to move and transfer to the pavement layer easily. The outcomes of this study can help bridge authorities and construction contractors choose appropriate design and construction measures to prevent pumping distress.

Archaeological prospection of a prehistoric lithic workshop site using ground penetrating radar with a high‐frequency antenna unit

AbstractWe surveyed in detail the Chalcolithic lithic workshop Fofanovo XIII an East Fennoscandian region by ground‐penetrating radar (GPR). A high‐frequency antenna unit was applied to map small‐scale features, mainly waste flakes. To substantiate the efficiency of the GPR technique, we performed a primary analysis of a set of equivalent models in a sandbox. The laboratory‐scale GPR investigation highlights differences in GPR patterns depending on the spatial arrangement of small features and supports the further interpretation of real‐life data. The GPR survey in the field covered 2200 m2, revealing areas with a high density of artefacts in the cultural layer and locating individual structural elements of the Fofanovo XIII archaeological site. We suggested using microdebitage samples from manual probing to verify the detected anomalous values of GPR attributes. The results point to a significant correlation between microdebitage and the envelope peak amplitude of the echo signal. Ultimately, our study confirmed the cultural layer in the Fofanovo XIII workshop site to be rich in lithic production wastes, indicating it was a place of mass‐scale production of lithic chopping tools.

Numerical Study on Urban Infrastructure Diagnosis in Laterally Heterogenous Soils Using Resistivity and Ground Penetrating Radar Techniques

Urban environment can be considered a complex system consisting of the engineered pavement physical structure over the buried utilities (water, gas, sewer) network embedded in the background soil environment. Assessment of buried pipeline civil infrastructures using proximal geophysical methods in such instances has to consider possible interferences, difficulties, and incorrect inferences. In this study, we have conducted a numerical modelling investigation to understand and evaluate how electrical resistivity profiling (ERP) and ground penetrating radar (GPR) can be utilised to provide subsurface information that otherwise may not be possible if either one of the techniques is used. A model geometry consisting of a typical pavement structure (asphalt, base/subbase, and background soil) with a single 2 m pipe buried at a depth of 1 m was used. Strong lateral variations in soil type were incorporated over the short pipe section in order to understand the complexities that can arise, especially with ERP measurements. The 3D electrical resistivity measurements were simulated in Comsol using the 4-probe method, while the 2D GPR measurements were simulated in gprMax to obtain the subsurface information. The results from both ERP and GPR were used to develop a practical framework that can be utilised by relevant authorities for proximal condition assessment of their buried assets. It was suggested that ERP can be used as a first level screening tool over the whole pipeline length, followed by discretely selected GPR scans in order to further gain information on the pipe health. This is attractive practically since, following delineations of a large pipe section into shorter subsections, advanced condition assessment approaches that are generally intrusive in nature can then be economically deployed within the subsections suspected of experiencing significant corrosion damage.