Editorial for the Special Issue “Radar Techniques for Structures Characterization and Monitoring”

This Special Issue focuses on the potential of radar-based remote techniques for characterizing and monitoring natural and building structures. This collection concerns ground-penetrating radar (GPR) since it is one of the most versatile geophysical remote-sensing techniques that can be applied virtually in any built technique or material. But it also expands to include other techniques such as laser-based scanning and insight into new developments in the field of radar processing. Ten research papers were published in this Special Issue, comprising nine articles [1,2,3,4,5,6,7,8,9] and one technical note [10].

The first contribution examines the problem of rebar assessment in reinforced concrete structures with GPR. A common problem in some cases is the processing and interpretation of radargrams due to the complexity of the radar images, as the signal is reflected based on the dielectric constant of subsurface media/layers. To tackle this problem, Yue et al. [1] and Wang et al. [2] improved the detectability of rebars using various artificial neural network models to facilitate and automate signal detection, classification, and processing. The second contribution from Wang et al. [3] tackles the difficulty in assessing the thickness of concrete elements (in this case, a tunnel lining) when only one side is available, and the rebar prevents the detection of the opposite side due to the high dielectric constant of the metal media which is considered infinity. The study aims to identify the rebar signals to improve the assessment of the entire depth of the structural element.

GPR is also used in monitoring cracks in road pavements, as elucidated by Guo et al. [4]. Their study includes the use of numerical modeling to improve the characteristics of field data and enhance the data interpretation for a better understanding of radar images.

Two research papers from Zhang et al. [5] and Wang et al. [6] focus on the detection of water content and wet surfaces for use in agricultural settings. The authors of [5] use innovative data processing techniques to improve the assessment of water content in the soil. On the other hand, the authors of [6] show laboratory experiments and numerical simulations to show wet underground objects and surfaces produce a distinct signal within GPR data that allows for a better interpretation of the presence of water.

The paper from Gilmutdinov et al. [7] deals with the detection of wall-layered geometry with GPR. The authors use an innovative method paired with artificial neural network models to improve the accuracy of GPR measurements.

The studies from Zhang et al. [8] and Wang et al. [9] all deal with new developments and improvements in radar signals to reduce clutter and improve the interpretation of field data.

Finally, the paper from Wang et al. [10] illustrates a remote sensing technique using a 3D laser scanner to acquire building geometrical information and compare it with the original design drawings, update the design drawings, and obtain as-built measurements. The study considers the case of the installation of a curtain wall. As-built geometrical data were acquired and compared to design data and used to obtain correct measurements for the effective curtain wall.

In conclusion, the publications in this Special Issue highlight some of the novel developments and advances in the GPR field related to the automatization of data analyses, processing, and decluttering and other fields that can use remote-sensing techniques to provide important insights into the built (and natural) environments.