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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 65577

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Special Issue Editors

Dr. Mercedes Solla

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Guest Editor

GeoTECH Research Group, CINTECX, Universidade de Vigo, 36310 Vigo, Spain
Interests: ground penetrating radar; signal processing; numerical modeling; civil and environmental engineering; cultural heritage; archaeology; geographic information systems (GIS)
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Vega Perez-Gracia

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Guest Editor

GIES Research Group, Universitat Politecnica de Catalunya, Barcelona, Spain
Interests: ground-penmetrating radar; applied geophysics; geophysical prospection; civil engineering assessment; archaeology; cultural heritage; buildings; signal processing; surveys in agriculture
Special Issues, Collections and Topics in MDPI journals

Dr. Simona Fontul

E-Mail Website
Guest Editor

National Laboratory for Civil Engineering, Transportation Department, 1700-066 Lisbon, Portugal
Interests: ground-penetrating radar; signal processing; road and airfield pavements; railways; condition assessment; structural characterization; transport infrastructure rehabilitation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is mainly dedicated to publishing high-quality original research articles, reviews, and applications on the use of GPR and other NDT methods for the assessment of transport infrastructure.

Advances in different nondestructive techniques have shown their great utility in the study of infrastructures, both to make decisions about their maintenance and to control their state during the service life of each structure. Particularly, the application of ground-penetrating radar (GPR) for the evaluation and monitoring of transport infrastructure is an effective method of obtaining information about structures in a non-invasive and nondestructive way. The application of GPR, and complementary nondestructive (NDT) techniques such as ERT, seismic, pulse–echo, magnetics, thermography, etc., provides useful and accurate information about the inner state of structures and infrastructure, which offers valuable information to engineers focused on their diagnosis and maintenance. Applications are highly useful in the case of road and airfield pavements, including layer thickness assessment, compaction analysis, identification of cracking, and moisture content estimation. There is also relevant interest in railway maintenance, including the assessment of ballast thickness, as well as the estimation of fouling and moisture content. Regarding structures, the main objectives reside in the inspection of bridges and tunnels. With respect to bridges, both concrete and masonry, the most interesting aspects to investigate are rebar and tendon ducts mapping, as well as corrosion in reinforced concrete. When dealing with the inspection of masonry bridges, the interest resides in mapping different filling, estimation of moisture content, identification of voids or lack of ashlar, and measuring ring stone thicknesses. In the case of tunnels, the main applications are the estimation of lining thickness and backfill grouting, identification of cavities or cracking in lining, rebar localization, and corrosion and moisture content evaluation.

During the last few decades, there have been major advances in the development of new techniques, data analysis, and decision-making procedures. Recent trends also show an increasing interest in the combination of NDT methods for high-resolution diagnosis. However, the development of these techniques and inspection procedures needs a comprehensive and up-to-date overview of the state-of-the-art of research activities aiming to define capabilities and limitations.

We would like to invite you to submit articles on but not limited to the following topics:

Novel developments on GPR systems and antennas;
Novel applications and developments of NDT methods in transport infrastructure assessment;
Advances on data acquisition methodologies;
New data processing algorithms and GPR imaging;
GPR procedures for transport infrastructure assessment (road and airfield pavements, railways, bridges, tunnels, etc.);
Combined use of GPR and complementary NDT (pulse–echo, seismic, thermography, etc.) for transport infrastructure assessment;
Geophysical assessment as support for maintenance decision and transport infrastructure management;
Practical applications and examples illustrating the potential of NDT techniques in the study of structures and infrastructure;
NDT applications from aerial platforms (airplanes, helicopters, drones, etc.);
NDT computational modelling and inversion models.

Dr. Mercedes Solla Carracelas
Dr. Vega Pérez-Gracia
Dr. Simona Fontul
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

GPR
NDT
Civil Engineering
transport infrastructure
roads
airfields
railways
structures
signal processing
antennas and radar systems

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Published Papers (13 papers)

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Research

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16 pages, 8402 KiB

Open AccessArticle

Bridge Foundation River Scour and Infill Characterisation Using Water-Penetrating Radar

by Kris E. J. Campbell, Alastair Ruffell, Jamie Pringle, David Hughes, Su Taylor and Brian Devlin

Remote Sens. 2021, 13(13), 2542; https://doi.org/10.3390/rs13132542 - 29 Jun 2021

Cited by 10 | Viewed by 3096

Abstract

Inspections of engineered structures below water level are essential to ensure the long-term serviceability of bridge infrastructure and to avoid major damage or failure. This research aimed to investigate integrated geophysical technologies for the underwater inspection of bridge foundation-related scour and erodible scour-based infill. Survey methods focused on Water-Penetrating Radar (WPR), supplemented by sonar. Whilst the survey benefits of the sonar imaging water–sediment interface and structures are well known, those of WPR are not. However, it is ideally suited to the survey of the water base and sub-sediment in shallow (>10 m) freshwater, especially where suspended sediment, weed infestation or methane impede sonar results. Our work produced good WPR imagery acquired from small, manoeuvrable boats that allowed bathymetric profiles to be plotted, as well as the likely locations of soft-sediment scour in future high-water flow events. This study provides clear benefits for integrated sonar and WPR surveys in the quantitative assessment of engineered structures within freshwater. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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20 pages, 7700 KiB

Open AccessArticle

Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes

by Vivek Kumar, Isabel M. Morris, Santiago A. Lopez and Branko Glisic

Remote Sens. 2021, 13(9), 1846; https://doi.org/10.3390/rs13091846 - 9 May 2021

Cited by 10 | Viewed by 3106

Abstract

Estimating variations in material properties over space and time is essential for the purposes of structural health monitoring (SHM), mandated inspection, and insurance of civil infrastructure. Properties such as compressive strength evolve over time and are reflective of the overall condition of the aging infrastructure. Concrete structures pose an additional challenge due to the inherent spatial variability of material properties over large length scales. In recent years, nondestructive approaches such as rebound hammer and ultrasonic velocity have been used to determine the in situ material properties of concrete with a focus on the compressive strength. However, these methods require personnel expertise, careful data collection, and high investment. This paper presents a novel approach using ground penetrating radar (GPR) to estimate the variability of in situ material properties over time and space for assessment of concrete bridges. The results show that attributes (or features) of the GPR data such as raw average amplitudes can be used to identify differences in compressive strength across the deck of a concrete bridge. Attributes such as instantaneous amplitudes and intensity of reflected waves are useful in predicting the material properties such as compressive strength, porosity, and density. For compressive strength, one alternative approach of the Maturity Index (MI) was used to estimate the present values and compare with GPR estimated values. The results show that GPR attributes could be successfully used for identifying spatial and temporal variation of concrete properties. Finally, discussions are presented regarding their suitability and limitations for field applications. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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23 pages, 7632 KiB

Open AccessArticle

Quantification of the Mechanized Ballast Cleaning Process Efficiency Using GPR Technology

by Anna Borkovcová, Vladislav Borecký, Salih Serkan Artagan and Filip Ševčík

Remote Sens. 2021, 13(8), 1510; https://doi.org/10.3390/rs13081510 - 14 Apr 2021

Cited by 7 | Viewed by 2889

Abstract

Ground Penetrating Radar (GPR) has been used recently for diagnostics of the railway infrastructure, particularly the ballast layer. To overcome ballast fouling, mechanized ballast cleaning process, which increases track occupancy time and cost, is usually used. Hence it is of crucial significance to identify at which stage of track ballast life cycle, and level of fouling, ballast cleaning should be initiated. In the present study, a series of in situ GPR surveys on selected railway track sections in Czechia was performed to obtain railway granite ballast relative dielectric permittivity (RDP) values in several phases of railway track lifecycle. GPR data were collected in the form of B-scan, and time-domain analysis was used for post-processing. The results indicate (i) change of railway ballast RDP in time (long term); (ii) a dependency of ballast fouling level on RDP; and (iii) the RDP change during the ballast cleaning process, thus its efficiency. This research aimed to provide new perspectives into the decision-making process in initiating the mechanized ballast cleaning intervention based on the GPR-measured data. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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33 pages, 48226 KiB

Open AccessArticle

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

by Xavier Dérobert, Vincent Baltazart, Jean-Michel Simonin, Shreedhar Savant Todkar, Christophe Norgeot and Ho-Yan Hui

Remote Sens. 2021, 13(8), 1474; https://doi.org/10.3390/rs13081474 - 11 Apr 2021

Cited by 16 | Viewed by 3583

Abstract

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

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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19 pages, 10862 KiB

Open AccessArticle

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

by Zhen Liu, Wenxiu Wu, Xingyu Gu, Shuwei Li, Lutai Wang and Tianjie Zhang

Remote Sens. 2021, 13(6), 1081; https://doi.org/10.3390/rs13061081 - 12 Mar 2021

Cited by 103 | Viewed by 6937

Abstract

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

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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15 pages, 6774 KiB

Open AccessCommunication

Diagnostics of Reinforcement Conditions in Concrete Structures by GPR, Impact-Echo Method and Metal Magnetic Memory Method

by Karel Pospisil, Monika Manychova, Josef Stryk, Marta Korenska, Radek Matula and Vaclav Svoboda

Remote Sens. 2021, 13(5), 952; https://doi.org/10.3390/rs13050952 - 3 Mar 2021

Cited by 13 | Viewed by 2863

Abstract

It is important to use adequately reliable non-destructive methods that would be capable of determining the reinforcement conditions in concrete structures. Three different methods: ground penetrating radar, impact-echo method, and metal magnetic memory method were used for testing laboratory-prepared reinforced concrete beams (with a reinforcing bar of the same diameter along its whole length, reinforcing bar locally impaired, and reinforcing bar interrupted). The ground-penetrating radar proved the correlation of signal parameters with the reinforcing bar condition. An impairment/interruption reinforcing bar appeared in the record from measurements in the transversal and longitudinal direction by changes of the observed depth of the reinforcing bar from the concrete surface and direct wave attenuation. The impact-echo method proved that the shifts of the dominant frequencies from the response signal correspond with the impairment/interruption of the reinforcing bar. Results of diagnostics by the metal magnetic memory method were presented by a magnetogram of the magnetic field strength and field gradient on the measured distance. The changes in the magnetic field strength proved different stress concentration zones due to the reinforcing bar condition. The used non-destructive methods showed that they are capable of indicating the different reinforcement conditions in reinforced concrete beams. This paper indicates in which cases and for what reason it is appropriate to use these three methods and in what way they differ from each other. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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22 pages, 16722 KiB

Open AccessFeature PaperArticle

Spatial Representation of GPR Data—Accuracy of Asphalt Layers Thickness Mapping

by Šime Bezina, Ivica Stančerić, Josipa Domitrović and Tatjana Rukavina

Remote Sens. 2021, 13(5), 864; https://doi.org/10.3390/rs13050864 - 25 Feb 2021

Cited by 5 | Viewed by 3109

Abstract

Information on pavement layer thickness is very important for determining bearing capacity, estimating remaining life and strengthening planning. Ground-penetrating radar (GPR) is a nondestructive testing (NDT) method used for determining the continuous pavement layer thickness in the travel direction. The data obtained with GPR in one survey line is suitable for the needs of repair and rehabilitation planning of roads and highways, but not for wider traffic areas such as airfield pavements. Spatial representation of pavement thickness is more useful for airfield pavements but requires a 3D model. In the absence of 3D GPR, a 3D model of pavement thickness can be created by additional processing of GPR data obtained from multiple survey lines. Five 3D models of asphalt pavements were created to determine how different numbers of survey lines affect their accuracy. The distance between survey lines ranges from 1 to 5 m. The accuracy of the 3D models is determined by comparing the asphalt layer thickness on the model with the values measured on 22 cores. The results, as expected, show that the highest accuracy is achieved for the 3D model created with a distance of 1 m between survey lines, with an average relative error of up to 1.5%. The lowest accuracy was obtained for the 3D model created with a distance of 4 m between the survey lines, with an average relative error of 7.4%. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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18 pages, 11378 KiB

Open AccessArticle

Frequency–Wavenumber Analysis of Deep Learning-based Super Resolution 3D GPR Images

by Man-Sung Kang and Yun-Kyu An

Remote Sens. 2020, 12(18), 3056; https://doi.org/10.3390/rs12183056 - 18 Sep 2020

Cited by 19 | Viewed by 4378

Abstract

This paper proposes a frequency–wavenumber (f–k) analysis technique through deep learning-based super resolution (SR) ground penetrating radar (GPR) image enhancement. GPR is one of the most popular underground investigation tools owing to its nondestructive and high-speed survey capabilities. However, arbitrary underground medium inhomogeneity and undesired measurement noises often disturb GPR data interpretation. Although the f–k analysis can be a promising technique for GPR data interpretation, the lack of GPR image resolution caused by the fast or coarse spatial scanning mechanism in reality often leads to analysis distortion. To address the technical issue, we propose the f–k analysis technique by a deep learning network in this study. The proposed f–k analysis technique incorporated with the SR GPR images generated by a deep learning network makes it possible to significantly reduce the arbitrary underground medium inhomogeneity and undesired measurement noises. Moreover, the GPR-induced electromagnetic wavefields can be decomposed for directivity analysis of wave propagation that is reflected from a certain underground object. The effectiveness of the proposed technique is numerically validated through 3D GPR simulation and experimentally demonstrated using in-situ 3D GPR data collected from urban roads in Seoul, Korea. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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21 pages, 5045 KiB

Open AccessArticle

GPR Spectra for Monitoring Asphalt Pavements

by Josep Pedret Rodés, Adriana Martínez Reguero and Vega Pérez-Gracia

Remote Sens. 2020, 12(11), 1749; https://doi.org/10.3390/rs12111749 - 29 May 2020

Cited by 24 | Viewed by 4583

Abstract

Ground Penetrating Radar (GPR) is a prospecting method frequently used in monitoring asphalt pavements, especially as an optimal complement to the defection test that is commonly used for determining the structural condition of the pavements. Its application is supported by studies that demonstrate the existence of a relationship between the parameters determined in GPR data (usually travel time and wave amplitude) and the preservation conditions of the structure. However, the analysis of frequencies is rarely applied in pavement assessment. Nevertheless, spectral analysis is widespread in other fields such as medicine or dynamic analysis, being one the most common analytical methods in wave processing through use of the Fourier transform. Nevertheless, spectral analysis has not been thoroughly applied and evaluated in GPR surveys, specifically in the field of pavement structures. This work is focused on analyzing the behavior of the GPR data spectra as a consequence of different problems affecting the pavement. The study focuses on the determination of areas with failures in bituminous pavement structures. Results epitomize the sensitivity of frequencies to the materials and, in some cases, to the damage. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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Review

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54 pages, 7153 KiB

Open AccessReview

A Review of GPR Application on Transport Infrastructures: Troubleshooting and Best Practices

by Mercedes Solla, Vega Pérez-Gracia and Simona Fontul

Remote Sens. 2021, 13(4), 672; https://doi.org/10.3390/rs13040672 - 13 Feb 2021

Cited by 125 | Viewed by 17037

Abstract

The non-destructive testing and diagnosis of transport infrastructures is essential because of the need to protect these facilities for mobility, and for economic and social development. The effective and timely assessment of structural health conditions becomes crucial in order to assure the safety of the transportation system and time saver protocols, as well as to reduce excessive repair and maintenance costs. Ground penetrating radar (GPR) is one of the most recommended non-destructive methods for routine subsurface inspections. This paper focuses on the on-site use of GPR applied to transport infrastructures, namely pavements, railways, retaining walls, bridges and tunnels. The methodologies, advantages and disadvantages, along with up-to-date research results on GPR in infrastructure inspection are presented herein. Hence, through the review of the published literature, the potential of using GPR is demonstrated, while the main limitations of the method are discussed and some practical recommendations are made. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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Other

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13 pages, 2088 KiB

Open AccessTechnical Note

A GPR-Based Pavement Density Profiler: Operating Principles and Applications

by Nectaria Diamanti, A. Peter Annan, Steven R. Jackson and Dylan Klazinga

Remote Sens. 2021, 13(13), 2613; https://doi.org/10.3390/rs13132613 - 3 Jul 2021

Cited by 8 | Viewed by 2653

Abstract

Density is one of the most important parameters in the construction of asphalt mixtures and pavement engineering. When a mixture is properly designed and compacted, it will contain enough air voids to prevent plastic deformation but will have low enough air void content to prevent water ingress and moisture damage. By mapping asphalt pavement density, areas with air void content outside of the acceptable range can be identified to predict its future life and performance. We describe a new instrument, the pavement density profiler (PDP) that has evolved from many years of making measurements of asphalt pavement properties. This instrument measures the electromagnetic (EM) wave impedance to infer the asphalt pavement density (or air void content) locally and over profiles. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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15 pages, 1859 KiB

Open AccessTechnical Note

Optimising the Complex Refractive Index Model for Estimating the Permittivity of Heterogeneous Concrete Models

by Hossain Zadhoush, Antonios Giannopoulos and Iraklis Giannakis

Remote Sens. 2021, 13(4), 723; https://doi.org/10.3390/rs13040723 - 16 Feb 2021

Cited by 16 | Viewed by 4131

Abstract

Estimating the permittivity of heterogeneous mixtures based on the permittivity of their components is of high importance with many applications in ground penetrating radar (GPR) and in electrodynamics-based sensing in general. Complex Refractive Index Model (CRIM) is the most mainstream approach for estimating the bulk permittivity of heterogeneous materials and has been widely applied for GPR applications. The popularity of CRIM is primarily based on its simplicity while its accuracy has never been rigorously tested. In the current study, an optimised shape factor is derived that is fine-tuned for modelling the dielectric properties of concrete. The bulk permittivity of concrete is expressed with respect to its components i.e., aggregate particles, cement particles, air-voids and volumetric water fraction. Different combinations of the above materials are accurately modelled using the Finite-Difference Time-Domain (FDTD) method. The numerically estimated bulk permittivity is then used to fine-tune the shape factor of the CRIM model. Then, using laboratory measurements it is shown that the revised CRIM model over-performs the default shape factor and provides with more accurate estimations of the bulk permittivity of concrete. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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14 pages, 3957 KiB

Open AccessTechnical Note

Displacement Monitoring in Airport Runways by Persistent Scatterers SAR Interferometry

by Luca Bianchini Ciampoli, Valerio Gagliardi, Chiara Ferrante, Alessandro Calvi, Fabrizio D’Amico and Fabio Tosti

Remote Sens. 2020, 12(21), 3564; https://doi.org/10.3390/rs12213564 - 30 Oct 2020

Cited by 49 | Viewed by 4894

Abstract

Deformations monitoring in airport runways and the surrounding areas is crucial, especially in cases of low-bearing capacity subgrades, such as the clayey subgrade soils. An effective monitoring of the infrastructure asset allows to secure the highest necessary standards in terms of the operational and safety requirements. Amongst the emerging remote sensing techniques for transport infrastructures monitoring, the Persistent Scatterers Interferometry (PSI) technique has proven effective for the evaluation of the ground deformations. However, its use for certain demanding applications, such as the assessment of millimetric differential deformations in airport runways, is still considered as an open issue for future developments. In this study, a time-series analysis of COSMO–SkyMed satellite images acquired from January 2015 to April 2019 is carried out by employing the PSI technique. The aim is to retrieve the mean deformation velocity and time series of the surface deformations occurring in airport runways. The technique is applied to Runway 3 at the “Leonardo da Vinci” International Airport in Rome, Italy. The proposed PSI technique is then validated by way of comparison with the deformation outcomes obtained on the runway by traditional topographic levelling over the same time span. The results of this study clearly demonstrate the efficiency and the accuracy of the applied PSI technique for the assessment of deformations in airport runways. Full article

(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)

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