Special Issue "Latest Results on GPR Algorithms, Applications and Systems"

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

Deadline for manuscript submissions: 31 July 2022 | Viewed by 2419

Special Issue Editors

Dr. Sebastiano D’Amico
E-Mail Website
Guest Editor
Department of Geosciences, University of Malta, MSD2080 Msida, Malta
Interests: earthquake ground motion and seismic hazard; earthquake moment tensor solutions and physics of earthquake source; ambient noise measurements on soil and buildings; seismicity and tectonics of the central Mediterranean; scientific methods applied to cultural heritage
Special Issues, Collections and Topics in MDPI journals
Prof. Raffaele Persico
E-Mail Website
Guest Editor
Department of Environmental Engineering, University of Calabria, 87036 Arcavacata, Italy
Interests: ground penetrating radar; electromagnetic wave propagation; magnetic permeability; permittivity; frequency-domain analysis; geophysical techniques; radar imaging; remote sensing by radar; time-domain
Special Issues, Collections and Topics in MDPI journals
Dr. Mercedes Solla
E-Mail Website
Guest Editor
CINTECX, Universidade de Vigo, GeoTECH Research Group, 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
Dr. Craig Warren
E-Mail Website
Guest Editor
Mechanical and Construction Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
Interests: computational modelling; optimisation of electromagnetic (EM) sensing systems, such as Ground Penetrating Radar (GPR)

Special Issue Information

Dear Colleague,

After a pause due to the pandemic, the scientific community working on GPR issues is going to restart exchanging ideas and looking toward innovative solutions. A constant dialogue between academia and companies traditionally accompanies this progress, which has over the years transformed the systems, led to new applications beyond the most traditional ones, and introduced deeper and deeper studies into data processing. The next IWAGPR conference, to be held in Valletta, Malta, on 17–20 October, 2021, will be a meaningful occasion for re-launching this ever-stimulating debate. Associated to the conference, the present Special Issue in Remote Sensing is proposed, in which the authors of contributions to IWAGPR will have the possibility to expand their work and publish them in an open access format.

The Special Issue is aimed at works that introduce any innovation in the state-of-the-art of either GPR systems (antennas, electronics, positioning systems, etc.), or some novelty regarding data gathering and processing (filtering procedures, migration, nonlinear algorithms, particular measurement configurations) or some innovation possibly introduced in the applications, which can be either “classical” such as archaeology, pavement monitoring, tunneling, etc. or more recent and particular, such as monitoring of irrigation, applications with drones, and so on.

In particular, in this Special Issue, we do not look for mere case histories, but we are aware that from case histories, some interesting tips can often arrive because of unexpected problems arising in the field explored. Contributions from participants of the IWAGPR2021 as well as external scientists are equally welcome.

Dr. Sebastiano D’Amico
Prof. Raffaele Persico
Dr. Mercedes Solla
Dr. Craig Warren
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 2500 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

  • Ground-penetrating radar Geophysics Antennas

Published Papers (4 papers)

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Research

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Article
Wavefield Reconstruction Inversion Based on the Multi-Scale Cumulative Frequency Strategy for Ground-Penetrating Radar Data: Application to Urban Underground Pipeline
Remote Sens. 2022, 14(9), 2162; https://doi.org/10.3390/rs14092162 - 30 Apr 2022
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Abstract
High-precision detection of the underground pipelines is an indispensable part of the development and construction of cities. At present, the inversion technology for ground-penetrating radar (GPR) data is an effective means of realizing shallow-underground-space visualization in the field of geophysical exploration. However, the [...] Read more.
High-precision detection of the underground pipelines is an indispensable part of the development and construction of cities. At present, the inversion technology for ground-penetrating radar (GPR) data is an effective means of realizing shallow-underground-space visualization in the field of geophysical exploration. However, the traditional full-waveform inversion (FWI) method usually faces the problems of strong nonlinearity of the objective function, high dependence on the initial model, and huge calculation cost. For improving the accuracy and efficiency of GPR data inversion, a wavefield reconstruction inversion (WRI) strategy is used for GPR data imaging to reduce the nonlinearity of the inversion problem and the dependence on the initial model. Then, the frequency weighting strategy and the multi-scale method are adopted to avoid the high-frequency component data dominating the optimization process and enhance the stability of inversion. In this paper, two numerical experiments of pipeline models with different materials and spacing or buried depths verified that the proposed method can effectively reconstruct the subsurface pipelines, and further performance of our algorithm on the field data verified the reliability of high-precision imaging of urban underground pipelines, which shows great potential of application in the field of high-precision detection of the urban underground pipelines. Full article
(This article belongs to the Special Issue Latest Results on GPR Algorithms, Applications and Systems)
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Article
A New Methodology for the Detection and Extraction of Hyperbolas in GPR Images
Remote Sens. 2021, 13(23), 4892; https://doi.org/10.3390/rs13234892 - 02 Dec 2021
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Abstract
Reliable detection of underground infrastructure is essential for infrastructure modernization works, the implementation of BIM technology, and 3D cadasters. This requires shortening the time of data interpretation and the automation of the stage of selecting the objects. The main factor that influences the [...] Read more.
Reliable detection of underground infrastructure is essential for infrastructure modernization works, the implementation of BIM technology, and 3D cadasters. This requires shortening the time of data interpretation and the automation of the stage of selecting the objects. The main factor that influences the quality of radargrams is noise. The paper presents the method of data filtration with use of wavelet analyses and Gabor filtration. The authors were inspired to conduct the research by the fact that the interpretation and analysis of radargrams is time-consuming and by the wish to improve the accuracy of selection of the true objects by inexperienced operators. The authors proposed automated methods for the detection and classification of hyperboles in GPR images, which include the data filtration, detection, and classification of objects. The proposed object classification methodology based on the analytic hierarchy process method introduces a classification coefficient that takes into account the weights of the proposed conditions and weights of the coefficients. The effectiveness and quality of detection and classification of objects in radargrams were assessed. The proposed methods make it possible to shorten the time of the detection of objects. The developed hyperbola classification coefficients show promising results of the detection and classification of objects. Full article
(This article belongs to the Special Issue Latest Results on GPR Algorithms, Applications and Systems)
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Technical Note
A Numerical Investigation of the Dispersion Law of Materials by Means of Multi-Length TDR Data
Remote Sens. 2022, 14(9), 2003; https://doi.org/10.3390/rs14092003 - 21 Apr 2022
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Abstract
In this paper, we propose a method for retrieving the dispersion law of a material under test from multi-length TDR measurements in reflection mode, repeated at several frequencies. By replacing the multi-frequency measurements with measurements using multi-length TDR probe, it is possible to [...] Read more.
In this paper, we propose a method for retrieving the dispersion law of a material under test from multi-length TDR measurements in reflection mode, repeated at several frequencies. By replacing the multi-frequency measurements with measurements using multi-length TDR probe, it is possible to retrieve the complex equivalent permittivity of the material in a frequency band of interest. The proposed procedure does not require a priori knowledge of the type of dispersion law of the material, which instead can possibly be inferred from the measured data. The algorithm is validated using numerically simulated data obtained with the commercial code CST Microstudio®. Full article
(This article belongs to the Special Issue Latest Results on GPR Algorithms, Applications and Systems)
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Technical Note
Local Freeman Decomposition for Robust Imaging and Identification of Subsurface Anomalies Using Misaligned Full-Polarimetric GPR Data
Remote Sens. 2022, 14(3), 804; https://doi.org/10.3390/rs14030804 - 08 Feb 2022
Cited by 1 | Viewed by 458
Abstract
A full-polarimetric ground penetrating radar (FP-GPR) uses an antenna array to detect subsurface anomalies. Compared to the traditional GPR, FP-GPR can obtain more abundant information about the subsurface. However, in field FP-GPR measurements, the arrival time of the received electromagnetic (EM) waves from [...] Read more.
A full-polarimetric ground penetrating radar (FP-GPR) uses an antenna array to detect subsurface anomalies. Compared to the traditional GPR, FP-GPR can obtain more abundant information about the subsurface. However, in field FP-GPR measurements, the arrival time of the received electromagnetic (EM) waves from different channels cannot be strictly aligned due to the limitations of human operation errors and the craftsmanship of the equipment. Small misalignments between the radargrams acquired from different channels of an FP-GPR can lead to erroneous identification results of the classic Freeman decomposition (FD) method. Here, we propose a local Freeman decomposition (LFD) method to enhance the robustness of the classic FD method when managing with misaligned FP-GPR data. The tests on three typical targets demonstrate that misalignments will severely interfere with the imaging and the identification results of the classic FD method for the plane and dihedral scatterers. In contrast, the proposed LFD method can produce smooth images and accurate identification results. Besides, the identification of the volume scatterer is not affected by misalignments. A test of ice-fracture detection further verifies the capability of the LFD method in field measurements. Due to the different relative magnitudes of the permittivity of the media on two sides of the interfaces, the ice surface and ice fracture show the features of surface-like and double-bounce scattering, respectively. However, the definition of double-bounce scattering is different from the definition in polarimetric synthetic aperture radar (SAR). Finally, a quantitative analysis shows that the sensitivities of the FD and LFD methods to misalignments are related to both the type of target and the polarized mode of the misaligned data. The tolerable range of the LFD method for misalignments is approximately ±0.2 times the wavelength of the EM wave, which is much wider than that of the FD method. In most cases, the LFD method can guarantee an accurate result of identification. Full article
(This article belongs to the Special Issue Latest Results on GPR Algorithms, Applications and Systems)
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