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Remote Sensing
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Close-Range Remote Sensing by Ground Penetrating Radar
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Close-Range Remote Sensing by Ground Penetrating Radar

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 June 2014) | Viewed by 55895

Special Issue Editors

Dr. Henrique Lorenzo

E-Mail Website
Guest Editor
Close-Range Remote Sensing & Photogrammetry Group, University of Vigo, EUET Forestal, Campus A Xunqueira s/n, 36005 Pontevedra, Spain
Interests: ground-penetrating radar; close-range photogrammetry; terrestrial laser scanner; cultural heritage applications
Special Issues, Collections and Topics in MDPI journals
Dr. Mercedes Solla

E-Mail Website
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

Special Issue Information

Dear Colleagues,

Ground penetrating radar (GPR) is a geophysical and close-range remote sensing technique based on the use of radar pulses to detect underground features and/or changes in material properties within materials. The principles of GPR operation are based on the ability of low frequency radar waves to penetrate into a non-conductive medium; such a medium usually is subsoil, but can also consist of walls, concrete, snow, etc. The signal emitted travels through the material, and is scattered and/or reflected by changes in impedance; such changes give rise to events that appear similar to the emitted signal. Therefore, GPR is a suitable method for studying changes in propagation medium’ physical properties, and also for characterizing different mediums and reflective targets, by providing information about their physical properties. The last decades have seen major advances as GPR technology matures:GPR has been applied not only from ground-based and airborne platforms, but also from spaceborne platforms.

This special issue is mainly dedicated to publishing state-of-the-art studies on the use of GPR as a close-range remote sensing tool. We invite you to submit articles on the following topics:

- GPR systems and antennas

- Data processing

- Geological, geotechnical, and environmental applications

- Civil engineering and pavements

- Archaeology and cultural heritage

- Mining detection

- GPR and other NDT technologies

Air and spaceborne GPR applications are also welcome.

Dr. Henrique Lorenzo
Dr. Mercedes Solla
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

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Research

3256 KiB  
Article
GPR Signal Characterization for Automated Landmine and UXO Detection Based on Machine Learning Techniques
by Xavier Núñez-Nieto, Mercedes Solla, Paula Gómez-Pérez and Henrique Lorenzo
Remote Sens. 2014, 6(10), 9729-9748; https://doi.org/10.3390/rs6109729 - 13 Oct 2014
Cited by 85 | Viewed by 11283
Abstract
Landmine clearance is an ongoing problem that currently affects millions of people around the world. This study evaluates the effectiveness of ground penetrating radar (GPR) in demining and unexploded ordnance detection using 2.3-GHz and 1-GHz high-frequency antennas. An automated detection tool based on [...] Read more.
Landmine clearance is an ongoing problem that currently affects millions of people around the world. This study evaluates the effectiveness of ground penetrating radar (GPR) in demining and unexploded ordnance detection using 2.3-GHz and 1-GHz high-frequency antennas. An automated detection tool based on machine learning techniques is also presented with the aim of automatically detecting underground explosive artifacts. A GPR survey was conducted on a designed scenario that included the most commonly buried items in historic battle fields, such as mines, projectiles and mortar grenades. The buried targets were identified using both frequencies, although the higher vertical resolution provided by the 2.3-GHz antenna allowed for better recognition of the reflection patterns. The targets were also detected automatically using machine learning techniques. Neural networks and logistic regression algorithms were shown to be able to discriminate between potential targets and clutter. The neural network had the most success, with accuracies ranging from 89% to 92% for the 1-GHz and 2.3-GHz antennas, respectively. Full article
(This article belongs to the Special Issue Close-Range Remote Sensing by Ground Penetrating Radar)
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5674 KiB  
Article
GPR Laboratory Tests For Railways Materials Dielectric Properties Assessment
by Francesca De Chiara, Simona Fontul and Eduardo Fortunato
Remote Sens. 2014, 6(10), 9712-9728; https://doi.org/10.3390/rs6109712 - 13 Oct 2014
Cited by 44 | Viewed by 7835
Abstract
In railways Ground Penetrating Radar (GPR) studies, the evaluation of materials dielectric properties is critical as they are sensitive to water content, to petrographic type of aggregates and to fouling condition of the ballast. Under the load traffic, maintenance actions and climatic effects, [...] Read more.
In railways Ground Penetrating Radar (GPR) studies, the evaluation of materials dielectric properties is critical as they are sensitive to water content, to petrographic type of aggregates and to fouling condition of the ballast. Under the load traffic, maintenance actions and climatic effects, ballast condition change due to aggregate breakdown and to subgrade soils pumping, mainly on existing lines with no sub ballast layer. The main purpose of this study was to validate, under controlled conditions, the dielectric values of materials used in Portuguese railways, in order to improve the GPR interpretation using commercial software and consequently the management maintenance planning. Different materials were tested and a broad range of in situ conditions were simulated in laboratory, in physical models. GPR tests were performed with five antennas with frequencies between 400 and 1800 MHz. The variation of the dielectric properties was measured, and the range of values that can be obtained for different material condition was defined. Additionally, in situ GPR measurements and test pits were performed for validation of the dielectric constant of clean ballast. The results obtained are analyzed and the main conclusions are presented herein. Full article
(This article belongs to the Special Issue Close-Range Remote Sensing by Ground Penetrating Radar)
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5802 KiB  
Article
Assessment of Complex Masonry Structures with GPR Compared to Other Non-Destructive Testing Studies
by Sonia Santos-Assunçao, Vega Perez-Gracia, Oriol Caselles, Jaume Clapes and Victor Salinas
Remote Sens. 2014, 6(9), 8220-8237; https://doi.org/10.3390/rs6098220 - 29 Aug 2014
Cited by 66 | Viewed by 8618
Abstract
Columns are one of the most usual supporting structures in a large number of cultural heritage buildings. However, it is difficult to obtain accurate information about their inner structure. Non-destructive testing (NDT) methodologies are usually applied, but results depend on the complexity of [...] Read more.
Columns are one of the most usual supporting structures in a large number of cultural heritage buildings. However, it is difficult to obtain accurate information about their inner structure. Non-destructive testing (NDT) methodologies are usually applied, but results depend on the complexity of the column. Non-flat external surfaces and unknown and irregular internal materials complicate the interpretation of data. This work presents the study of one column by using ground-penetrating radar (GPR) combined with seismic tomography, under laboratory conditions, in order to obtain the maximum information about the structure. This column belongs to a “Modernista” building from Barcelona (Spain). These columns are built with irregular and fragmented clay bricks and mortar. The internal irregular and complex structure causes complicated 2D images, evidencing the existence of many different targets. However, 3D images provide valuable information about the presence and the state of an internal tube and show, in addition, that the column is made of uneven and broken bricks. GPR images present high correlation with seismic data and endoscopy observation carried out in situ. In conclusion, the final result of the study provides information and 3D images of damaged areas and inner structures. Comparing the different methods to the real structure of the column, the potential and limitations of GPR were evaluated. Full article
(This article belongs to the Special Issue Close-Range Remote Sensing by Ground Penetrating Radar)
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Graphical abstract

2858 KiB  
Article
On Recovering Missing Ground Penetrating Radar Traces by Statistical Interpolation Methods
by Gonzalo Safont, Addisson Salazar, Alberto Rodriguez and Luis Vergara
Remote Sens. 2014, 6(8), 7546-7565; https://doi.org/10.3390/rs6087546 - 14 Aug 2014
Cited by 34 | Viewed by 6758
Abstract
Missing traces in ground penetrating radar (GPR) B-scans (radargrams) may appear because of limited scanning resolution, failures during the acquisition process or the lack of accessibility to some areas under test. Four statistical interpolation methods for recovering these missing traces are compared in [...] Read more.
Missing traces in ground penetrating radar (GPR) B-scans (radargrams) may appear because of limited scanning resolution, failures during the acquisition process or the lack of accessibility to some areas under test. Four statistical interpolation methods for recovering these missing traces are compared in this paper: Kriging, Wiener structures, Splines and the expectation assuming an independent component analyzers mixture model (E-ICAMM). Kriging is an adaptation to the spatial context of the linear least mean squared error estimator. Wiener structures improve the linear estimator by including a nonlinear scalar function. Splines are a commonly used method to interpolate GPR traces. This consists of piecewise-defined polynomial curves that are smooth at the connections (or knots) between pieces. E-ICAMM is a new method proposed in this paper. E-ICAMM consists of computing the optimum nonlinear estimator (the conditional mean) assuming a non-Gaussian mixture model for the joint probability density in the observation space. The proposed methods were tested on a set of simulated data and a set of real data, and four performance indicators were computed. Real data were obtained by GPR inspection of two replicas of historical walls. Results show the superiority of E-ICAMM in comparison with the other three methods in the application of reconstructing incomplete B-scans. Full article
(This article belongs to the Special Issue Close-Range Remote Sensing by Ground Penetrating Radar)
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Graphical abstract

1457 KiB  
Article
3D Ground Penetrating Radar to Detect Tree Roots and Estimate Root Biomass in the Field
by Shiping Zhu, Chunlin Huang, Yi Su and Motoyuki Sato
Remote Sens. 2014, 6(6), 5754-5773; https://doi.org/10.3390/rs6065754 - 18 Jun 2014
Cited by 68 | Viewed by 12915
Abstract
The objectives of this study were to detect coarse tree root and to estimate root biomass in the field by using an advanced 3D Ground Penetrating Radar (3D GPR) system. This study obtained full-resolution 3D imaging results of tree root system using 500 [...] Read more.
The objectives of this study were to detect coarse tree root and to estimate root biomass in the field by using an advanced 3D Ground Penetrating Radar (3D GPR) system. This study obtained full-resolution 3D imaging results of tree root system using 500 MHz and 800 MHz bow-tie antennas, respectively. The measurement site included two larch trees, and one of them was excavated after GPR measurements. In this paper, a searching algorithm, based on the continuity of pixel intensity along the root in 3D space, is proposed, and two coarse roots whose diameters are more than 5 cm were detected and delineated correctly. Based on the detection results and the measured root biomass, a linear regression model is proposed to estimate the total root biomass in different depth ranges, and the total error was less than 10%. Additionally, based on the detected root samples, a new index named “magnitude width” is proposed to estimate the root diameter that has good correlation with root diameter compared with other common GPR indexes. This index also provides direct measurement of the root diameter with 13%–16% error, providing reasonable and practical root diameter estimation especially in the field. Full article
(This article belongs to the Special Issue Close-Range Remote Sensing by Ground Penetrating Radar)
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1416 KiB  
Article
GPR Raw-Data Order Statistic Filtering and Split-Spectrum Processing to Detect Moisture
by Gokhan Kilic
Remote Sens. 2014, 6(6), 4687-4704; https://doi.org/10.3390/rs6064687 - 26 May 2014
Cited by 4 | Viewed by 7030
Abstract
Considerable research into the area of bridge health monitoring has been undertaken; however, information is still lacking on the effects of certain defects, such as moisture ingress, on the results of ground penetrating radar (GPR) surveying. In this paper, this issue will be [...] Read more.
Considerable research into the area of bridge health monitoring has been undertaken; however, information is still lacking on the effects of certain defects, such as moisture ingress, on the results of ground penetrating radar (GPR) surveying. In this paper, this issue will be addressed by examining the results of a GPR bridge survey, specifically the effect of moisture in the predicted position of the rebars. It was found that moisture ingress alters the radargram to indicate distortion or skewing of the steel reinforcements, when in fact destructive testing was able to confirm that no such distortion or skewing had occurred. Additionally, split-spectrum processing with order statistic filters was utilized to detect moisture ingress from the GPR raw data. Full article
(This article belongs to the Special Issue Close-Range Remote Sensing by Ground Penetrating Radar)
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