Forests are vital components of the ecosystem of the Earth, regulating climate, conserving soil and water, and fostering biodiversity. Sustainable forest management offers crucial long-term benefits, but challenges such as disease threaten tree health. Disease-infected trees in both forests and urban areas pose risks to safety, property, and culture, leading to economic losses. Traditional inspection methods, such as resistance drilling, are invasive and laborious, while nondestructive techniques such as ground penetrating radar (GPR), offer promising alternatives. Although GPR shows potential, complexities such as tree structure and electromagnetic properties hinder accurate disease detection. In order to address these challenges, a new approach integrates structure-from-motion (SfM) photogrammetry with GPR measurement, and a novel holographic radar tomography processing approach has been proposed in this article. These methodologies accurately reconstruct tree trunks in 3-D, enabling precise GPR positioning and the obtaining of trunk permittivity. An arc-shaped Kirchhoff migration algorithm, moreover, helps mitigate irregular trunk shapes, enhancing data accuracy. The proposed framework demonstrates efficacy in real-tree measurement, offering high-precision disease monitoring. This innovation not only aids in preserving biodiversity but also enhances ecosystem services by promoting sustainable forest management. Effective disease monitoring ensures timely intervention, safeguarding valuable old trees and ecosystems while minimizing economic and cultural losses.

China’s Tianwen-1 successfully landed in the southern Utopian Planitia of the Martian surface on 15 May 2021. The Zhurong Rover, equipped with a high frequency full polarimetric Rover Penetrating Radar (RoPeR), travelled 1,921 m to investigate the shallow geological structure and material composition of the Martian weathered layer. In this study, we propose a new processing strategy to estimate surface relative permittivity using the HH and VV reflections of the high frequency RoPeR data. This new strategy is based on the induced field rotation effect, which occurs when orthogonally-polarised electromagnetic waves propagate into an uneven surface with incident angles. 3D time-domain finite-difference simulations were performed using random surfaces with various relative permittivities under the same geometry as the Zhurong Rover. Polarimetric alpha angle versus relative permittivity was then calculated based on the simulation results. At the same time, direct coupling removal, band-pass filtering and channel calibration were performed on the real RoPeR data and clear surface reflections were extracted. The surface reflection amplitudes of the HH and VV were then obtained and the polarimetric alpha angle calculated. Finally, relative permittivity was estimated through the relationship obtained from the simulation results. The average value of the relative permittivity estimated by the proposed approach is 3.292, with a standard deviation of 0.235. This result is consistent with that obtained by orbiting Radar Systems and the low frequency RoPeR system. This study will contribute to the further signal processing and accurate interpretation of real radar data captured by way of RoPeR on Mars.

This study presents a novel bridge monitoring approach for transport assets, based on the synergistic use of high-resolution (X-band) SAR imagery. A multi-temporal SAR Interferometry analysis is performed to detect potential issues related to the Rochester Bridge, located in Rochester, UK. A displacement map for the structure was produced using space-based SAR measurements acquired by the Italian constellation COSMO-SkyMed over the period 2017–2019, provided by the Italian Space Agency (ASI) in the framework of the Open-call for Science Project “Motib - ID742”. The outcomes of this study demonstrate that multi-temporal InSAR remote sensing techniques can be applied to complement information from non-destructive ground-based methods (e.g., ground-penetrating radars, laser scanners, accelerometers etc.), paving the way for future integrated approaches in the smart monitoring of infrastructure assets.

Internal decays in trees can rapidly escalate into a full decomposition of the inner structural layer, i.e., the “heartwood” layer, due to the action of aggressive diseases and fungal infections. This process leads to the formation of big cavities and hollows, which remain surrounded by the sapwood layer only. Estimating the thickness of the sapwood layer with a high degree of accuracy is therefore crucial for correct assessment of the structural integrity of hollow trees, as well as an extremely challenging task. In this context, ground-penetrating radar (GPR) has proven effective in providing details of the internal structure of trees. Nevertheless, the existing GPR processing methods still offer limited information on their internal configuration. This study investigates the effectiveness of GPR enhanced by a microwave tomography inversion approach in the assessment of hollow trees. To this aim, a living hollow tree was investigated by performing a set of pseudocircular scans along the bark perimeter with a hand-held common-offset GPR system. The tree was then felled, and sections were cut for testing purposes. A dedicated data processing framework was developed and tested through numerical simulations of hollow tree sections. The internal structure of the real trunk was therefore reconstructed via a tomographic imaging approach and the outcomes were quantitatively analyzed by way of comparison with the real sections’ main geometric features. The tomographic approach has proven very accurate in locating the sapwood–cavity interface and in the evaluation of the sapwood layer thickness, with a centimeter prediction accuracy.

In recent years, trees in European countries have been increasingly endangered by emerging infectious diseases (EIDs). In the United Kingdom, this has been observed to affect whole woodlands and forests, threatening the existence of some types of trees. Although quarantine measures have been taken to limit the spreading of such diseases, this has not yet been effectively controlled leading to millions of trees affected by EIDs. Ground-penetrating radar (GPR) has proven effective in identifying critical features on diseased trees for detection of EIDs spread. However, the irregular shape of tree trunks and their complex internal structure represent real challenges for conventional GPR measurements and data processing methodologies. In this research, a dual-polarised GPR system is used to detect internal decay in tree trunks using novel signal processing methodologies. A polarimetric correlation filter based on Bragg Scattering on a 3D Pauli feature vector and an arc-shaped Kirchhoff migration are discussed in detail. The proposed polarimetric correlation filter is utilised to enhance the signal-to-noise ratio (SNR) of B-scans due to bark and tree trunk high-loss properties of tree trunks. Meanwhile, an arc-shaped Kirchhoff migration algorithm is performed to counteract the influence of the bark irregularity. The proposed data processing framework is successfully validated with measurements on a real tree trunk, where cross-sections were subsequently cut for comparison purposes. Outcomes from the proposed methodology demonstrate a high consistency with the features observed on the tree trunk cross-sections, indicating the reliability of the proposed detection scheme for assessing tree-decay associated with EIDs.

In recent years, successful applications of the Synthetic Aperture Radar Interferometry (InSAR) for the monitoring of subsidence and deformations in transport infrastructures have been reported in the literature. The main advantage of this technique compared to other non -destructive surveying methodologies is in the possibility to perform fast network-level surveys as well as the provision of time-series of the displacements by multi-temporal data acquisitions. Given the medium ground resolution, C-band imagery are usually not employed for transport infrastructure monitoring as it is considered unlikely to obtain sufficiently accurate information. However, the use of medium resolution SAR data has not been thoroughly investigated until now and is still an open challenge. This study presents a novel approach for transport assets monitoring, based on the synergistic use of medium resolution (C-Band) and high resolution (X-Band) SAR imagery. To this effect, a multi-temporal SAR Interferometry analysis of high and medium-resolution datasets is performed on a runway of the Leonardo Da Vinci Airport in Rome, Italy. The data were acquired by the Scntinel-l A and the COSMO-SkyMed missions, respectively. A comparison between the results from medium and high-resolution datasets demonstrates the viability of using multi-frequency SAR imagery, and pave the way to the development of new methodologies for the monitoring of transport infrastructures.

Ash dieback, acute oak decline (AOD), and Xylella Fastidiosa are emerging infectious diseases (EIDs) that have spread rapidly in European forests during the last decade. Quarantine measurements have mostly failed to repress the outbreaks and millions of trees have already been infected. Identifying infected trees in a nondestructive manner is of high importance for monitoring, managing, and preventing EIDs. The aim of this article is to examine the capabilities of ground penetrating radar (GPR) on evaluating the internal structure of tree trunks and detecting tree decay associated with EIDs. Traditionally used processing schemes tuned for GPR line acquisitions are modified accordingly to be compatible with the new measurement configurations. In particular, a detection framework is presented based on a modified Kirchhoff and a reverse-time migration. Both of the aforementioned methodologies are compatible with measurements taken along closed irregular curves assuming a homogeneous permittivity distribution. To that extent, prior to migration, a novel focal criterion is used that estimates the bulk permittivity of the host medium from the measured B-scans. The suggested detection scheme is successfully tested on both numerical and laboratory measurements, indicating that GPR has the potential to become a coherent and practical tool for detecting tree decay associated with EIDs.

Ground penetrating radar (GPR) is traditionally applied to smooth surfaces in which the assumption of half-space is an adequate approximation that does not deviate much from reality. Nonetheless, using GPR for internal structure characterization of tree trunks requires measurements on an irregularly shaped closed curve. A typical hyperbola fitting has no physical meaning in this new context since the reflection patterns are strongly associated with the shape of the tree trunk. Instead of a clinical hyperbola, the reflections give rise to complex-shaped patterns that are difficult to be analyzed even in the absence of clutter. In this paper, a novel processing scheme is described which can interpret complex reflection patterns assuming a circular target subject to any arbitrary shaped surface. The proposed methodology can be applied using commercial hand-held antennas in real time, avoiding computationally costly tomographic approaches that require the usage of custom-made bespoke antenna arrays. The validity of the current approach is illustrated both with numerical and real experiments.

The effective monitoring of ballasted railway track beds is fundamental for maintaining safe operational conditions of railways and lowering maintenance costs. Railway ballast can be damaged over time by the breakdown of aggregates or by the upward migration of fine clay particles from the foundation, along with capillary water. This may cause critical track settlements. To that effect, early stage detection of fouling is of paramount importance. Within this context, ground penetrating radar (GPR) is a rapid nondestructive testing technique, which is being increasingly used for the assessment and health monitoring of railway track substructures. In this paper, we propose a novel and efficient signal processing approach based on entropy analysis, which was applied to GPR data for the assessment of the railway ballast conditions and the detection of fouling. In order to recreate a real-life scenario within the context of railway structures, four different ballast/pollutant mixes were introduced, ranging from clean to highly fouled ballast. GPR systems equipped with two different antennas, ground-coupled (600 and 1600 MHz) and air-coupled (1000 and 2000 MHz), were used for testing purposes. The proposed methodology aims at rapidly identifying distinctive areas of interest related to fouling, thereby lowering significantly the amount of data to be processed and the time required for specialist data processing. Prominent information on the use of suitable frequencies of investigation from the investigated set, as well as the relevant probability values of detection and false alarm, is provided.

This paper discusses the development of a highly interactive multimedia package which includes a series of standard soil mechanics laboratory experiments for teaching and learning purposes at undergraduate level of a typical civil engineering or Earth science course. The developed software is in the form of a CD-ROM and consists of three distinct key elements including: (a) photo-panoramic guided tour of a typical soil mechanics laboratory (navigable movies); (b) technical information, which includes a procedural statement for each experiment, a description of the equipment and apparatus, an example, typical results, references to other literature and additional information to underpin lecture notes; (c) questions and log file of results and navigation. The paper also provides an example test (Shear Box Test) explaining the step by step procedure of using the package. Finally detailed technical and programming information about how this package was designed and developed are provided in this paper.