Displays

Approximately 70,000 masonry arch bridge spans (brick and stone) are reported to exist in the United Kingdom with in excess of tens of thousands throughout Europe. A good portion of these bridges is still operational and form part of the road and rail network systems in many countries. However, a great majority of these structures require desperate repair and maintenance [1].

Non-destructive testing (NDT) methods such as ground penetrating radar (GPR), 3D laser scanning, accelerometer sensors and thermal cameras amongst many others have been used to assess and monitor such structures in the past few years [2]. However, research has proven that stand-alone or integrated use of ground-based techniques may not represent a definitive solution to some major structural issues, such as scour and differential settlements [3], as these require continuous monitoring and data collection on long-term basis. To that extent, use of satellite data-based synthetic aperture radar (SAR) interferometry (InSAR) has proven to be effective in measuring displacements of infrastructure [4] [5] and natural terrain [6] over longer periods of observation.

Within this context, the paper presents a new integrated monitoring approach including use of the GPR and the InSAR techniques to an historic masonry arch bridge - the Old Aylesford Bridge in Kent, UK – a 13^th century bridge, crossing the river Medway. Main objectives of the research were: (1) to prove the viability of low-frequency and high-frequency GPR systems in providing structural detailing of the bridge deck at different depths and resolutions; (2) to be able to measure structural displacements with a millimetre accuracy caused by the seasonal variation of the water level in the river and the river bed soil expansions. Results have proven the viability of the above process to form the basis for an integrated health monitoring mechanism.

References

[1] Alani, A.M., Tosti, F., Banks, K., Bianchini Ciampoli, L., Benedetto, A. Non-Destructive Assessment of a Historic Masonry Arch Bridge Using Ground Penetrating Radar and 3D Laser Scanner, IMEKO International Conference on Metrology for Archaeology and Cultural Heritage Lecce, Italy, October 23-25, 2017.

[2] Solla, M., Lorenzo, H., Rial, F.I., Novo, A. (2011). GPR evaluation of the Roman masonry arch bridge of Lugo (Spain), NDT&Int., 44, 8-12.

[3] Selvakumaran, S., Plank, S., Geiß, C., Rossi, C., Middleton, C. (2018). Remote monitoring to predict bridge scour failure using Interferometric Synthetic Aperture Radar (InSAR) stacking techniques, Int. J. .Appl. Earth Obs. and Geoinf. 73, 463-470.

[4] Tosti, F., Gagliardi, V., D'Amico, F. and Alani, A.M., Transport infrastructure monitoring by data fusion of GPR and SAR imagery information. TIS 2019 International Conference of Rome, 23-24 September 2019.

[5] Bianchini Ciampoli, L., Gagliardi, V., Clementini, C. et al. (2019). Transport Infrastructure Monitoring by InSAR and GPR Data Fusion. Surv Geophys. https://doi.org/10.1007/s10712-019-09563-7

How to cite: Gagliardi, V., Bianchini Ciampoli, L., Tosti, F., Benedetto, A., and Alani, A. M.: Health Monitoring of Masonry Arch Bridges by Integration of GPR and InSAR Techniques, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13899, https://doi.org/10.5194/egusphere-egu2020-13899, 2020.

The large availability of Synthetic Aperture Radar (SAR) data collected over the last decade by several satellite missions, such as COSMO-SkyMed, TerraSAR-X and Sentinel-1 constellations, has been pushing toward the present Earth Observation (EO) scenario into a “golden age”, which is rapidly moving towards a real Big Data scenario. The widespread use of satellite SAR data have fostered the development of several SAR applications, one of those referred to as Differential SAR Interferometry (DInSAR) technology, which has deeply demonstrated to profitably detect the surface deformations over a wide spatial extent in both natural and anthropic hazard scenarios, through the generation of spatially dense deformation maps with millimetric accuracies. In particular, the advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS) approach allows retrieving the temporal and spatial characteristics of the detected displacements at two spatial resolution scales, referred to as regional (spatial resolution in the 30-90 m range) and local (spatial resolution in the 3-10 m range) scales, suitable for a large variety of application fields, from natural hazards (volcano eruptions, seismic events, landslides) to anthropic contexts (urban areas, archaeological sites, oil-gas extraction, structures and transport infrastructures).

However, the interferometric processing performed at local scale needs to deal with hundreds of SAR acquisitions at full spatial resolution, i.e. to manage several hundreds of million points; consequently, the processing of such a data amount is particularly heavy from a computational point of view and can not be carried out in reasonable time frames through the traditional (sequential) implementation of the full resolution DInSAR processing chains.

Accordingly, to profitably benefit from the current SAR scenario, it is crucial to develop innovative solutions to automatically and efficiently handle large DInSAR data stacks. These solutions are principally based on the exploitation of advanced distributed computing environments, to achieve high efficiency in terms of scalability performances, as well as on the development of much more advanced DInSAR methodologies (and codes) able to effectively maximize the information related to these huge amount of DInSAR data.

This work is aimed at describing an innovative DInSAR solution, based on the exploitation of distributed HPC and Cloud Computing environments, which benefits from parallel programming techniques (multi-node, multi-threads, GPUs) implemented within an automatic full resolution P-SBAS processing pipeline. Starting from large SAR datasets acquired by the COSMO-SkyMed constellation, the developed parallel full resolution P-SBAS processing chain allows retrieving in short time frame (less than 24 hours) displacement time series and deformation maps, at the single buildings/infrastructure level, relevant to extended urban areas. The presented experimental results and the related performance analyses are achieved by applying the developed parallel P-SBAS pipeline to a number of large full resolution COSMO-SkyMed datasets acquired over some important Italian cities (e.g. Rome and Naples urban areas).

How to cite: Manunta, M., Yasir, M., Buonanno, S., Zinno, I., Lanari, R., and Bonano, M.: The parallel implementation of the full resolution SBAS-DInSAR processing chain for surface deformation analyses in extended urban areas , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20198, https://doi.org/10.5194/egusphere-egu2020-20198, 2020.

Use of advanced health monitoring strategies for bridges is essential to provide a comprehensive condition assessment of these structures and ensure their structural integrity. To this purpose, new technologies have been applied in recent years for both static and dynamic assessments offering unprecedented opportunities within the context of risk management and structural analysis. Among these, areal deformation measurement techniques from ground-based synthetic aperture radar (GB-SAR) sensors were successfully applied for continuous monitoring of dynamic and static displacements of bridges [1] [2]. However, a main limitation for the ground-based microwave interferometry is that, as a linear measurement technique, it is difficult to pinpoint the damage location and obtain accurate displacement time-series for bridges [3]. Moreover, it is known that vertical displacements are usually more relevant than horizontal displacements in the dynamic monitoring of bridges, and the GB-SAR interferometry can only provide the line-of-sight (LOS) displacement of the monitored bridge [4].

In this research, we focus on remote monitoring of the dynamic displacement responses of bridges with a polarimetric GB-SAR system. To this purpose, various strategies were used to overcome the existing limitations of this technique. Results from the monitoring of a long-span metallic railway bridge and a reinforced concrete Shinkansen bridge are discussed.

The aim of this research is to provide more comprehensive and accurate information for bridge health monitoring using a polarimetric sensor. To this extent, a polarimetric analysis was performed to identify the reflection from the side surface of the bridges. In addition, the information about the polarisation orientation angle and the local incidence angle were processed under the acquisition geometry to calculate the radar look angle. Therefore, the bridge deformation fields in the vertical direction were easily converted using the slant range distances and the corresponding maximum transient vertical deformation was transformed through the LOS deformation while a train passing the bridge.

References

[1] Monserrat, O. et al., 2014. A review of ground-based SAR Interferometry for deformation measurement. ISPRS Journal of Photogrammetry and Remote Sensing, pp. 40–48.

[2] Pieraccini, M. et al., 2006. Dynamic monitoring of bridges using a high-speed coherent radar. IEEE Transaction Geoscience and Remote Sensing, pp. 3284–3288.

[3] Sato M., Zou L., Nico G., 2017. Monitoring of Infrastructure by GB-SAR. IEICE technical report, pp. 11-16.

[4] Sato M., Zou L., Nico G., Kikuta K., 2019. Displacement and Vibration Monitoring by GB-SAR. IEICE Transactions on Communications, pp.844-852.

How to cite: Zou, L., Sato, M., Tosti, F., and Alani, A. M.: Advanced Bridge Monitoring Strategies by Polarimetric GB-SAR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11982, https://doi.org/10.5194/egusphere-egu2020-11982, 2020.

In the last decades, monitoring the regional-scale deformation of international airports has become a priority, in order to ensure the highest operational security and safety standards. Within this context, among the most innovative and suitable techniques for transport infrastructures monitoring purpose, Persistent Scatterer SAR Interferometry (PSI) technology has proven to be an effective technique to investigate ground deformations [1-3].

However, the application of PSI to effectively and continuously monitor settlement in airports is an open challenge. In this study, a long time-series analysis of a high-resolution COSMO-Skymed satellite image-stack, acquired from September 2011 to October 2019, was collected and processed by PSI technique to retrieve the mean deformation velocity and time series of surface deformation of the runways of Leonardo Da Vinci-International Airport.

The mean PS velocity information is compared to the ground-based levelling-data, collected on the runway using a total station, in order to validate and increase the feasibility of the monitoring processing.

Finally, various Deformation maps using the Natural Neighbor Geostatistical interpolation algorithm [4], were created and demonstrated a maximum subsidence rate is up to 15.3 mm/yr during the investigated period. The results confirmed the well-known major down-lifting phenomenon over an area, which has undergone routine maintenance.

Results have demonstrated the viability of integrating InSAR and topographical in-situ survey methods, paving the way to future implementations in prioritizing maintenance activities and helping for decision-making to have a comprehensive and inclusive information data system for the investigation of survey sites.

The research is supported by the Italian Ministry of Education, University and Research under the National Project “Extended resilience analysis of transport networks (EXTRA TN): Towards a simultaneously space, aerial and ground sensed infrastructure for risks prevention”, PRIN 2017, Prot. 20179BP4SM

[1] Bianchini Ciampoli, L., Gagliardi, V., Clementini, C. et al. Transport Infrastructure Monitoring by InSAR and GPR Data Fusion. Surv Geophys (2019). https://doi.org/10.1007/s10712-019-09563-7

[2] Ferretti, A., Prati, C., Rocca, F., 2000. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Trans. Geosci. 38 (5), 2202–2212. https://doi.org/10.1109/36.868878.

[3] Ferretti, A., Prati, C., Rocca, F.,2001. Permanent scatterers in SAR interferometry. IEEE Trans. Geosci. Remote Sens. 2001, 39, 8–20.

[4] Sibson, R. (1981). "A brief description of natural neighbor interpolation (Chapter 2)". In V. Barnett (ed.). Interpolating Multivariate Data. Chichester: John Wiley. pp. 21–36.

How to cite: Bianchini Ciampoli, L., Gagliardi, V., Tosti, F., Calvi, A., and Benedetto, A.: Persistent Scatterer SAR Interferometry (PSI) for Airport Runways monitoring, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8699, https://doi.org/10.5194/egusphere-egu2020-8699, 2020.

Bayesian posterior sampling is a flexible and general purpose method that can be used to quantify uncertainty in geophysical inversion results. It produces large ensembles of plausible subsurface models consistent with the data and some spatial prior. Unfortunately, it is computationally expensive and becomes impractical for high-dimensional models. This problem is exacerbated by the challenges of joint inversion using data from different geophysical methods, which may be sensitive to different petrophysical properties at different resolutions. To speed up and simplify both implementation and application, we introduce Bayesian spatial ensemble fusion.

The method is demonstrated here using airborne electromagnetic (both VTEM and Tempest) and magnetotelluric data from Cloncurry in the Mount Isa province of Queensland, Australia. 1D transdimensional inversion is applied to individual sites to quantify uncertainty locally, which produces ensembles of 1D layered resistivity models with variable numbers of layers. These local ensembles are then fused together to produce ensembles of more complex 2D models as an approximation to what laterally constrained probabilistic joint ensemble inversion would have produced.

There are several benefits to this approach: Different and existing software can be used by different specialists to create the input ensembles, which reduces the need for complex coordination and simplifies coding. Forward calculations are performed once and then stored to be recycled in many subsequent fusions. Many inversions of the same data, or different combinations thereof, can then be performed using different priors, constraints and geological interpretations, at very little additional cost. Thorough exploratory uncertainty analysis is thus made more practical as specialists can elicit and test different interpretations more quickly.

How to cite: Visser, G., Seillé, H., and Markov, J.: Approximating Probabilistic Joint Inversion using Bayesian Spatial Ensemble Fusion, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4388, https://doi.org/10.5194/egusphere-egu2020-4388, 2020.

In the field of non-destructive testing (NDT) in civil engineering, a large number of measurement data are collected. Although they serve as a basis for scientific analyses, there is still no uniform representation of the data. An analysis of various distributed data sets across different test objects is therefore only possible with high manual effort.

We present a system architecture for an integrated data management of distributed data sets based on Semantic Web technologies. The approach is essentially based on a mathematical model - the so-called ontology - which represents the knowledge of our domain NDT. The ontology developed by us is linked to data sources and thus describes the semantic meaning of the data. Furthermore, the ontology acts as a central concept for database access. Non-domain data sources can be easily integrated by linking them to the NDT construction ontology and are directly available for generic use in the sense of digitization. Based on an extensive literature research, we outline the possibilities that this offers for NDT in civil engineering, such as computer-aided sorting, analysis, recognition and explanation of relationships (explainable AI) for several million measurement data.

The expected benefits of this approach of knowledge representation and data access for the NDT community are an expansion of knowledge through data exchange in research (interoperability), the scientific exploitation of large existing data sources with data-based methods (such as image recognition, measurement uncertainty calculations, factor analysis, material characterization) and finally a simplified exchange of NDT data with engineering models and thus with the construction industry.

Ontologies are already the core of numerous intelligent systems such as building information modeling or research databases. This contribution gives an overview of the range of tools we are currently creating to communicate with them.

How to cite: Völker, C., Moreno-Torres, B., and Kruschwitz, S.: Understanding distributed data – a semantic web approach for data based analysis of NDT data in civil engineering , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19332, https://doi.org/10.5194/egusphere-egu2020-19332, 2020.

In order to plan infrastructure maintenance strategies, Non-Destructive Techniques (NDT) have been largely employed in recent years, achieving outstanding results in the identification of infrastructural deficiencies. Nevertheless, the extensive combination of different NDT that can cover various factors affecting infrastructure durability has not yet been thoroughly investigated.

This paper proposes a methodology for evaluating the resilience of infrastructures towards endogenous factors by combining different NDT outcomes. Machine Learning (ML) Regression algorithms have been used to predict the pavement surface roughness connected to a set of potential endogenous conditioning factors. The development, application, and comparison of two different regression algorithms, specifically Regression Tree (RT) and Random Forest (RF) have been carried out.

The study area involves 4 testing sites, both in the rural and urban context, for a total length of 11400 m. In addition to the International Roughness Index (IRI) calculated by profilometric measurements, a set of endogenous features of the infrastructure were collected by using NDT such as Falling Weight Deflectometer (FWD), and Ground Penetrating Radar (GPR). Moreover, a set of topographical data of roadside areas, information on properties of materials composing the subgrade and the pavement structure, traffic flow, rainfall, temperature, and age of infrastructure were gathered.

The database was randomly split into a Training (70%) and Test sets (30%). With the Training set, through a 10-Fold Cross-Validation (CV), the models have been trained and validated. A set of three performance metrics, namely Correlation Coefficient (R²), Root Mean Square Error (RMSE), and Mean Absolute Error (MSE), has been used for the Goodness-of-Fit (GoF) assessment. Also, with the Test set, the Predictive Performance (PP) of the models has been evaluated.

Results indicate that the suggested methodology is satisfactory for supporting processes on planning road maintenance by National Road Authorities (NRA) and allows decision-makers to pursue better solutions.

How to cite: Fiorentini, N., Leandri, P., and Losa, M.: Evaluating Resilience of Infrastructures Towards Endogenous Events by Non-Destructive High-Performance Techniques and Machine Learning Regression Algorithms, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21183, https://doi.org/10.5194/egusphere-egu2020-21183, 2020.

Street trees are widely recognised to be an essential asset for the urban environment, as they bring several environmental, social and economic benefits [1]. However, the conflicting coexistence of tree root systems with the built environment, and especially with road infrastructures, is often cause of extensive damage, such as the uplifting and cracking of sidewalks and curbs, which could seriously compromise the safety of pedestrians, cyclists and drivers.

In this context, Ground Penetrating Radar (GPR) has long been proven to be an effective non-destructive testing (NDT) method for the evaluation and monitoring of road pavements. The effectiveness of this tool lies not only in its ease of use and cost-effectiveness, but also in the proven reliability of the results provided. Besides, recent studies have explored the capability of GPR in detecting and mapping tree roots [2]. Algorithms for the reconstruction of the tree root systems have been developed, and the spatial variations of root mass density have been also investigated [3].

The aim of this study is, therefore, to investigate the GPR potential in mapping the architecture of root systems in street trees. In particular, this research aims to improve upon the existing methods for detection of roots, focusing on the identification of the road pavement layers. In this way, different advanced signal processing techniques can be applied at specific sections, in order to remove reflections from the pavement layers without affecting root detection. This allows, therefore, to reduce false alarms when investigating trees with root systems developing underneath road pavements.

In this regard, data from trees of different species have been acquired and processed, using different antenna systems and survey methodologies, in an effort to investigate the impact of these parameters on the GPR overall performance.

Acknowledgements

The authors would like to express their sincere thanks and gratitude to the following trusts, charities, organisations and individuals for their generosity in supporting this project: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook Trust, Sir Henry Keswick, Ian Bond, P. F. Charitable Trust, Prospect Investment Management Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation, and The Wyfold Charitable Trust. This paper is dedicated to the memory of our colleague and friend Jonathan West, one of the original supporters of this research project.

References

[1] J. Mullaney, T. Lucke, S. J. Trueman, 2015. “A review of benefits and challenges in growing street trees in paved urban environments,” Landscape and Urban Planning, 134, 157-166.

[2] A. M. Alani, L. Lantini, 2019. “Recent advances in tree root mapping and assessment using non-destructive testing methods: a focus on ground penetrating radar,” Surveys in Geophysics, 1-42.

[3] L. Lantini, F. Tosti, Giannakis, I., Egyir, D., A. Benedetto, A. M. Alani, 2019. “A Novel Processing Framework for Tree Root Mapping and Density Estimation using Ground Penetrating Radar,” In 10th International Workshop on Advanced Ground Penetrating Radar, EAGE.

How to cite: Lantini, L., Tosti, F., Giannakis, I., Munisami, K. J., Mortimer, D., and Alani, A. M.: Advanced GPR Signal Processing Techniques for Root Detection in Urban Environments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11954, https://doi.org/10.5194/egusphere-egu2020-11954, 2020.

Ground penetrating radar (GPR) and Seismic Surface Wave methods (SWMs) are two nondestructive testing (NDT) methods commonly used in near-surface site investigations. These two methods investigate the media properties of subsurface based on different physical phenomena. GPR has a good resolvability to characterize the layered structure since the propagation of electromagnetic wave is sensitive to the change of electrical properties, while, the geometric dispersion of surface waves can be used to retrieve the variation of S-wave velocity (Vs) with depth. In most situations, these two data sets are processed separately, and the results are later used for comprehensive interpretation. Constrained inversion, as a way to implement data fusion, can alleviate the non-uniqueness of the solution and produce more consistent information for the comprehensive site and material investigations.

We present an algorithm for the inversion of surface-wave dispersion curves with GPR interface constraints in 2D media. The reflection interfaces interpreted from the GPR profile are integrated into a cell- and boundary-based Vs model. This implementation allows both vertical and lateral changes within each region while also allows sharp changes across the boundaries. In addition, our algorithm simultaneously inverts several dispersion curves extracted along the survey line using multi-size spatial windows, which mitigates the adverse effects of 1D assumption in traditional surface-wave dispersion inversion and improves the matching of GPR and SWMs in lateral variations. We use synthetic and field data sets to test the effectivity of the proposed method. Both results show the improved resolution of the Vs model retrieved by the constrained inversion compared to the standard inversion.

How to cite: Hu, S., Zhao, Y., Bi, W., Shen, R., Li, B., and Ge, S.: Constrained Surface-wave Dispersion Inversion Using GPR Reflection Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12233, https://doi.org/10.5194/egusphere-egu2020-12233, 2020.

Transport infrastructures play a significant role in the economy of countries. However, in European countries, transport infrastructures aging (>40 years) and traffic increase require to develop in-situ efficient inspection and maintenance solutions. Monitoring of steel and composite structures are important issues for sustainability of existing and new infrastructure. Classical approach relies on large human activities eventually performed in unsafe conditions. To overcome the problem on site contactless global automated measurement methods are to be favoured.

For apparent corrosion, visible imaging coupled with image processing allows to detect and characterize the extension of the defective area. Anyway, characterization of corrosion thickness and nature require complementary measurements. Among imaging techniques, knowing that corrosion acts as a insulating layer, active infrared thermography is a possible approach [1-2]. But here we will focus on the complementary approach based on THz-TDS imaging as investigated and tested for corrosion detection under painting with preliminary corrosion type classification [2].

In the present study, we first performed a measurement campaign on several steel samples at different corrosion stages. Typically, three stages were investigated: from non-corroded with paint coating, to pitting corrosion up to fully corroded sample surface.

Data were gathered by means of the Z-Omega Fiber-Coupled Terahertz Time Domain (FICO) system working in a high-speed reflection mode and were processed by using a properly designed data processing chain recently proposed in [3] and involving a noise filtering procedure based on the Singular Value Decomposition (SVD) of the data matrix. Complementary post-processing approach for quick detection and characterization were added to these filtered data.

The obtained results, which will be presented in detail at the conference, allowed us to state the imaging capabilities offered by the adopted instrumentation and obtain valuable information on the surveyed specimens, such as the corrosion thickness connection with apparent pseudo-intensity images. Finally, perspectives on coupling techniques will be introduced.

Acknowledgments:

Authors wish to thank Research Fund for Coal and Steel for funding part of this work under grant agreement No 800687 in the framework of DESDEMONA project.

References

[1] A. Crinière, J. Dumoulin, C. Ibarra-Castanedo and X. Maldague ,” Inverse model for defect characterization of externally glued CFRP on reinforced concrete structures: Comparative study of square pulsed and pulsed thermography “, Quantitative InfraRed Thermography Journal, Taylor & Francis Editor, vol 11, pp 84-114, 2014. DOI: 10.1080/17686733.2014.897512.

[2] T. Sakagami, D. Shiozawa, Y. Tamaki, H. Ito A. Moriguchi, T. Iwama, K. Sekine and T. Shiomi, “Nondestructive detection of corrosion damage under corrosion protection coating using infrared thermography and terahertz imaging, in. Proc AITA 2015 conference, pp. 229-233, 2015.

[3] I. Catapano, F. Soldovieri, “A Data Processing Chain for Terahertz Imaging and Its Use in Artwork Diagnostics".J Infrared Milli Terahz Waves, pp.13, Nov. 2016.

How to cite: Dumoulin, J., Catapano, I., Moliard, J.-M., Ludeno, G., Toullier, T., and Soldovieri, F.: Comparative study of steel corrosion characterization by visible and THz imaging techniques, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11677, https://doi.org/10.5194/egusphere-egu2020-11677, 2020.

The danger related to the structural stability of hollowed trees is a matter of wide discussion among the scientific community. Hollow cores in trees can extend to more than 50% of the total diameter [1] and, while the presence of a hollow tree might appear dramatic in terms of public safety, it is not always a cause of concern. It is known that hollow trees can form in many years or even decades [2] and, although the heartwood is effectively dead, the tree can continue to form sapwood on the exterior of the trunk to create a cylinder. However, robustness and structural support provided by this cylinder to the trunk and canopy above depend on the ratio of healthy to diseased tissue.

In this context, Ground Penetrating Radar (GPR) has proven to be an effective non-invasive tool, capable of generating information about the inner structure of tree trunks in terms of existence, location, and geometry of defects [3], [4]. Nevertheless, it had been observed that the currently available and known GPR-related processing and data interpretation methods and tools are able to provide only limited information on the tree inner structure.

In this study, we present a microwave tomographic approach for improved GPR data processing with the aim of detecting and characterising the geometry of hollowed trees. Tests were performed at Gunnesbury Park, London, UK. In particular, a number of 15 circular measurements were collected around the tree using the Aladdin 2 GHz hand-held antenna system manufactured by IDS GeoRadar (Part of Hexagon), covering a height of 140 cm. The tree was eventually felled and three sections were cut for validation purposes.

Results presented in this abstract are part of a major research project that the authors have undertaken for the last three years.

Acknowledgements

The authors would like to express their sincere thanks and gratitude to the following trusts, charities, organisations and individuals for their generosity in supporting this project: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook Trust, Sir Henry Keswick, Ian Bond, P.F. Charitable Trust, Prospect Investment Management Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation, and The Wyfold Charitable Trust. This paper is dedicated to the memory of our colleague and friend Jonathan West, one of the original supporters of this research project.

References

[1] Braithwaite, R.W. (1985). The Kakadu fauna survey: an ecological survey of Kakudu National Park. Canberra, Australia: Australian Parks and Wildlife Service.

[2] Ruxton, G.D. (2014). Why are so many trees hollow? Biology Letters, 10 (11).

[3] Giannakis, I., Tosti, F., Lantini, L., Alani, A.M. (2019). Diagnosing Emerging Infectious Diseases of Trees Using Ground Penetrating Radar, IEEE Transactions on Geoscience and Remote Sensing. doi: 10.1109/TGRS.2019.2944070

[4] Alani, A.M., Soldovieri, F., Catapano, I., Giannakis, I., Gennarelli, G., Lantini, L., Ludeno, G., Tosti, F. (2019). The Use of Ground Penetrating Radar and Microwave Tomography for the Detection of Decay and Cavities in Tree Trunks. Remote Sens., 11, 2073.

How to cite: Tosti, F., Soldovieri, F., Catapano, I., Giannakis, I., Gennarelli, G., Lantini, L., Ludeno, G., and Alani, A. M.: GPR and Microwave Tomography for the Assessment of Hollowed Tree Trunks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20841, https://doi.org/10.5194/egusphere-egu2020-20841, 2020.

The deployment of non-invasive sensing methodologies capable of providing information useful to characterize, monitor and manage archaeological sites represents a fundamental step for the conservation/preservation of cultural heritage assets. In the framework of the national project VESTA (funded by the Campania Region), several non invasive activities have been carried out for testing a novel approach of analysis including in situ methodologies, drone and satellite technologies.

This communication deals with a case study carried out at the monumental archaeological site of Paestum, sited in the southern Italy, where Greek settlers founded the ancient city of Poseidonia (6th century B.C.) [1]. At this site, geophysical surveys based on the combined use of magnetometric analyses [2], geoelectrical surveys [3] and ground-penetrating radar measurements [4] have been performed. Specifically, the areas immediately close to the temples of Ceres and Neptune have been investigated to identify unknown and buried archaeological features and characterise the paleo-morphological context. The different resolution and depth of investigations related to the application of each one of the considered methodologies as well as the use of tomographic methodologies for the data processing allowed the collection of images showing different subsurface features of the investigated area at different spatial scale. These images made possible the identification of anomalies of the subsoil, which were useful both to respond to the questions of the archaeologists and give new perspectives for managing the site. At the conference, the results of the integrated geophysical surveys, as well as their archaeological interpretation, will be presented with a focus on the cultural and social value of the “water resource” for the ancient city of Poseidonia.

[1] https://www.museopaestum.beniculturali.it/?lang=en

[2] A. Aspinall, C. Gaffney, A. Schmidt, A Magnetometry for archaeologists. Geophysical methods for archaeology, Altamira Press, Lanham (2008).

[3] A. Binley, A. Kemna, DC resistivity and induced polarization methods. InHydrogeophysics Water and Science Technology Library; R. Yuram, S.S- Hubbard, S.S., Eds.; Springer: New York, NY, USA (2005).

[4] D. J. Daniels, Ground penetrating radar, IET (2004).

How to cite: Capozzoli, L., Soldovieri, F., Rizzo, E., Catapano, I., Ludeno, G., Gennarelli, G., De Martino, G., Scelza, F. U., and Zuchtriegel, G.: Cooperative use of non invasive sensing methodologies for the geophysical monitoring of the archaeological park of Paestum, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7077, https://doi.org/10.5194/egusphere-egu2020-7077, 2020.

Railway infrastructure maintenance is a critical activity for ensuring safe train operations, due to the constant mechanical stress and wear and tear that crucial parts of the infrastructure such as rail and catenary undergo under use. Several methodologies and systems have been devised for diagnosing and prevent anomalies and minimize safety risks, that measure geometrical parameters and assess the way the infrastructure interacts with the train. While those techniques help at identifying anomalies when they occur, sometimes they are not able to provide enough evidence on the reasons behind the failure. A visual inspection can surely help in assessing the causes of failure, especially when they happen during train operations, without introducing any disruption to the service to schedule a specific check with a visit to the site. This work investigates the design of a stereo vision system that can be mounted on diagnostic trains so that a virtual visit to the site can be done when needed, by providing a 3d reconstruction of the surrounding of a train path. To achieve this, in the proposed system two color cameras can be mounted on the head or tail locomotive in a stereo configuration. They are triggered by an axle encoder mounted on the train at a fixed distance of 2 mt. This way the acquired point clouds can be registered together to achieve a full 3d reconstruction of the train path so that an offline, remote inspection of parts of the rails and catenaries can support in detecting, and possibly prevent, future anomalies. Moreover, since the reconstruction extends beyond train paths for a few meters, the 3d reconstruction of the railway can be exploited in different ways too, for example by preventing that foreign objects invade and jeopardize the train loading gauge.

How to cite: Nitti, M., Mosca, N., Reno, V., Cosimo, P., diSumma, M., Colella, R., and Stella, E.: 3d stereo reconstruction of train paths for supporting maintenance operations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20265, https://doi.org/10.5194/egusphere-egu2020-20265, 2020.

The magnetotelluric method (MT) is a geophysical technique that provides high resolution information of the electrical resistivity of the subsurface geological structures by measuring the natural variations of the electromagnetic field recorded on the surface. Among the numerous applications, it can be used to map the presence of fluid reservoirs and localize significant structural contrasts that could be related to the presence of a geothermal or volcanic system. However, the interference of the anthropogenic noise during the MT measurements could affect significantly the correct interpretation of the collected data.

For this reason, in order to evaluate the effect of data contamination by anthropogenic sources, we analyzed the data registered by a continuous recording magnetotelluric station located inside the caldera of Las Cañadas (Tenerife, Spain). The instrumentation consisted of an ADU-08e, equipped with EPF-06 electrodes and MFS-06 magnetic coils. Two electric (Ex, Ey) and three magnetic (Hx, Hy, Hz) components have been recorded. This geophysical station was installed by the Instituto Volcanológico de Canarias (INVOLCAN), with purposes of volcano monitoring, on June 2019 and since then it has been recording data daily in the frequency range of 0.001 – 1000s.

On September 29 (2019) a significant electric blackout took place in the entire island of Tenerife in which, during approximately 6 hours the electricity supply was completely shut down. This situation represented a clear opportunity to obtain raw data almost free of anthropogenic contamination and it could help to quantify the effect of the anthropogenic noise in the MT measurements performed in a densely urbanized area as Tenerife. The first results show the clear change at 13:11:39 local time (GMT) in which both the electrical and magnetic components evidenced a pronounced change in their temporal pattern. Moreover, the comparison of the impedance tensor components between the previous hours and during the blackout reveals a noticeable difference for periods higher than 1 s.

How to cite: Martínez van Dorth, D., D'Auria, L., Ledo Fernández, J., Piña-Varas, P., Di Paolo, F., Cabrera-Pérez, I., Cervigón, G., Przeor, M., Hernández, W., Queralt, P., Marcuello, A., and Pérez, N.: The blackout of September 2019 on the island of Tenerife: an opportunity to estimate the level of contamination of electromagnetic noise using the magnetotelluric method, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-256, https://doi.org/10.5194/egusphere-egu2020-256, 2020.

The proposed study aims at analyzing effective surveying techniques and methodologies to acquire more detailed metric data and to support traditional surveying techniques on linear infrastructures.

In particular, from measurements acquired with LiDAR technique, it is possible to obtain an accurate 3D model of the infrastructure surface, which can be used to have complete information on its distress conditions.

The particular plano-altimetric development of the road belt makes the classic methods used for DEM extraction unsuitable, on which most modelling software is based, which reconstruct the trend of a given variable according to a regular grid of nodes starting from discrete measured and irregularly distributed values. This is done by means of interpolation techniques with which we arrive at a statistical or deterministic surface, usually in matrix format with a resolution chosen by the user; each element of the matrix corresponds to an elevation value. However, it is evident that a grid structure oriented according to the North-South cartographic grid is not effective to represent the curvilinear development of a road infrastructure.

Therefore, we want to introduce a first methodology to generate a particular curvilinear abscissa DEM, called DEMc, suitable for road pavements, which optimizes not only the computational effort but also the organization and extraction of profiles (longitudinal and transversal) and the plano-altimetric analysis. The construction of this model, represented by a ‘raster’ matrix, is semi-automatic. The elevation value of each single node of the two-dimensional grid is estimated through specially modified spatial and local interpolation processes. The process has been implemented in a Matlab environment.

A more advanced example of the digital paving model was based on the study of the deviation of the paved surface from a reference plane. The process involves the creation of a two-pitched flat surface constructed so as to lay on the real surface (theoretically, a road cross-section is represented by a double pitch to allow water flow). The building of the planes is carried out on road sections as wide as the entire carriageway and between 3 and 5 m long. To ensure that the pitch lays on the surface, an iterative algorithm has been implemented; at each iteration the algorithm excludes the points below the plane obtained by previous interpolation. In this way, in the next cycle, the new plane will be built by interpolation on the basis only of the data that were above the plane at the previous iteration; this method makes the plane orient itself according to the number of points remaining at each iterative cycle. The adjacent pitches, in the direction of travel, are built in such a way as to be mutually joined. This process has been implemented in the Matlab environment as well.

How to cite: Fiani, M. and Di Benedetto, A.: Digital Elevation Models (DEM) for the Analysis of the paved surface of Linear Infrastructures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22059, https://doi.org/10.5194/egusphere-egu2020-22059, 2020.

Most of the damage in road-flexible pavements occur where stiffness of the asphalt and load-bearing layers is low. To this extent, an effective assessment of the strength and deformation properties of these layers can help to identify the most critical sections [1].

This work proposes an experimental-based model [2] for the assessment of the bearing capacity of road-flexible pavements using ground-penetrating radar (GPR – 2 GHz horn antenna) and the Curviameter [3] non-destructive testing (NDT) methods. It is known that the identification of early decay and loss of bearing capacity is a major challenge for effective maintenance of roads and the implementation of pavement management systems (PMSs). To this effect, a time-efficient methodology based on a quantitative modelling of road bearing capacity is developed in this study. The viability of using a GPR system in combination with the Curviameter NDT equipment is also proven.

The research is supported by the Italian Ministry of Education, University and Research under the National Project “Extended resilience analysis of transport networks (EXTRA TN): Towards a simultaneously space, aerial and ground sensed infrastructure for risks prevention”, PRIN 2017, Prot. 20179BP4SM

[1] Frangopol, D.M.; Liu, M. Maintenance and management of civil infrastructure based on condition, safety, optimization, and life-cycle cost. Infrastruct. Eng. 2007, 1, 29–41.

[2] Tosti, C. L. Bianchini, F. D'Amico, A. M. Alani and A. Benedetto, “An experimental-based model for the assessment of the mechanical properties of road pavements using ground-penetrating radar,” Construction and Building Materials, vol. 165, pp. 966-974, 2018.

[3] M. Simonin, J.L. Geffard, P. Hornych, Performance of deflection measurement equipment and data interpretation in France, International Symposium Non-Destructive Testing in Civil Engineering (NDT-CE) September 15–17, 2015, Berlin, Germany.

How to cite: Ferrante, C., Bianchini Ciampoli, L., Tosti, F., Alani, A. M., and Benedetto, A.: Predicting the Bearing Capacity of Road Flexible Pavements using GPR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7021, https://doi.org/10.5194/egusphere-egu2020-7021, 2020.

Performing structural assessment at any time of asphalt pavements service life is an inherent process within pavement condition assessment. Layers thicknesses are among the major contributors to the overall pavement response and performance. Knowledge of layer thicknesses is imperative for both new and in-service pavements, because thickness data is usually combined with other response indicators (i.e. pavement deflections) in order to perform pavement evaluation during pavements service life. As such, inaccuracies in thickness assessment might result in erroneous response analysis and life expectancy estimation with a detrimental financial impact during maintenance planning.

Traditionally, layer thicknesses were retrieved through coring or digging test pits. Because of the limitations of these methods (including location-specific information, destructive nature, need for traffic disruptions), the pavement engineering community has consistently drawn its attention to a broadened utilization of advanced Non-Destructive Testing (NDT) systems in order to non-invasively determine the pavement cross-section. The most indicative NDT tool for that purpose is the Ground Penetrating Radar (GPR), which is systematically used for layers thickness evaluation. Within the framework of pavement evaluation processes, GPR is quite often combined with the Falling Weight Deflectometer (FWD), which provides with pavement response indications in terms of surface deflections.

It is worthwhile mentioning that GPR requires high expertise in order to reliably analyze the collected data and until now, there is none uniquely recognizable and universally accepted signal processing scheme. Supplementary to experienced users and analysts, investments in time and human resources are also needed to make reliable interpretations. Such reasons may potentially discourage related stakeholders from systematic GPR use, especially in cases where there are budgets constraints for the procurement and transportation logistics of multiple expensive equipment.

In light of the above, related research is pursed in respect to the investigation of the ability of FWD surface deflections indexes to provide with reliable information on the Asphalt Concrete (AC) layer thicknesses. For this purpose, Long-Term Pavement Performance (LTPP) data is analyzed including FWD and GPR data as well as sample coring. A nonlinear regression based relationship is under development that preliminarily exhibits a satisfactory performance both during model fit and model accuracy evaluation. Based on the above framework, it is suggested that the NDT analysis with deflection indexes seems promising in terms of roughly producing AC thickness, thereby balancing constraints at network level.

How to cite: Plati, C., Loizos, A., and Gkyrtis, K.: Data correlation of non-destructive testing methods to assess asphalt pavement thickness, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3422, https://doi.org/10.5194/egusphere-egu2020-3422, 2020.

Potholes are one of the public’s main local concerns as they cost a lot to the economy in terms of repair bills, delays while repairs are carried out and vehicle wear-and-tear. According to the Annual Local Authority Road Maintenance (ALARM) survey, eliminating the pothole backlog in England and Wales would cost £9.8bn and take a decade to complete despite increased local roads investment. The aim of this study is to research why potholes occur in the first place using non-destructive testing (NDT) and potential remedies in terms of the development of effective design and innovative materials to prevent their formation in future.

To investigate the causes of potholes formation, in-situ use of NDT methods such as ground-penetrating radar (GPR) has proven effectiveness as roads remain in continuous use. Analysis of GPR data can provide information on layer depths, material condition, moisture, voiding, reinforcement and location of other features [1, 2, 3].

Through our results, we will test two hypothesis; (i) shallow potholes are formed on loss of adhesion of the surface course, (ii) deep potholes are formed due to the loss of bearing capacity or settlement of the subgrade. Poor drainage in combination of heavy loads trigger shallow potholes while extreme wetting-drying cycles as a result of climate change decayed subgrade conditions of the pavement.

Results presented in this abstract are part of a PhD project funded by the University of West London.

References

[1] Saarenketo, T. and T. Scullion (2000). Road evaluation with ground penetrating radar. Journal of Applied Geophysics (43): 119–138.

[2] Benedetto, A., Tosti, F., Bianchini Ciampoli, L., and F. D’Amico (2016). An overview of ground-penetrating radar signal processing techniques for road inspections. Signal Processing (132): 201-209.

[3] Benedetto, A., Benedetto, F., and F. Tosti (2012). GPR applications for geotechnical stability of transportation infrastructures. Nondestructive Testing and Evaluation, 27 (3): 253–262.

How to cite: Naveed, M., Turrakheil, K. S., Tosti, F., and Alani, A. M.: Investigating the Causes of Roads Deterioration in the Form of Potholes using Non-Destructive Testing, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12032, https://doi.org/10.5194/egusphere-egu2020-12032, 2020.

Concrete is a strongly heterogeneous and densely packed composite material. Due to the high density of scattering constituents and inclusions, ultrasonic wave propagation in this material consists of a complex mixture of multiple scattering, mode conversion and diffusive energy transport. For a better understanding of the effect of aggregates, porosity and of crack distribution on elastic wave propagation in concrete and to optimize inverse techniques it is useful to simulate the wave propagation and scattering process explicitly in the time domain. For this purpose, we use the rotated staggered grid (RSG) finite-difference technique for solving the wave equations for elastic, anisotropic and/or viscoelastic media. This study is part of the CoDA project (DFG project 398216472, FOR 2825), which aims to develop a novel method based on ultrasonic coda wave interferometry (CWI) for the assessment of safety and durability of reinforced concrete structures. For this purpose, the coda technique is a suitable method to detect small changes in concrete members. In order to distinguish changes in the coda signal in terms of their origin (i.e. mechanical load, temperature, moisture), wave propagation simulations are performed to support the experimental investigations within the project. The idea is to create realistic digital twins for the experiments on two different scales: The specimen scale and the structural scale. In this study, high-performance simulations of ultrasonic wave propagation within concrete structures on the specimen scale were performed and evaluated using coda wave interferometry (CWI).

How to cite: Saydak, L. A. and Saenger, E. H.: Concrete Damage Assessment by Coda Waves: Wave propagation simulations to support experimental investigations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20493, https://doi.org/10.5194/egusphere-egu2020-20493, 2020.

Road pavements are subject to a range of problems due to traffic and temperature variations 

producing cracks that propagate to the pavement surface. Cracks need to be assessed to avoid 

deterioration and provide confidence in the functioning of the road system. Cracks are usually 

maintained after visual inspection by filling with bitumen as a first rehabilitation technique to 

avoid further deterioration and absorbing water leakages. Although this temporary solution does 

not extend the pavement life cycle it can help to avoid additional problems occurring within the

pavement. This work is proposed to aid the development of understanding and characterization

of cracks filled with bitumen in both rigid and asphalt pavements.

This study reports on the results of several laboratory experiments that were performed to 

explore the capability of Ground Penetrating Radar (GPR) in the assesment of bitumen-filled 

cracks in both rigid and asphalt pavements, respectively. These tests were focused on the 

analysis of cracking filled with bitumen using a GPR system equipped with a ground-coupled 

antenna with a 2.3 GHz central frequency, and varying the antenna orientation with respect to the 

crack axis.

Results showed the variation in characterization and changes in amplitude that could be expected 

when analysing bitumen-filled cracks in concrete and asphalt specimens, dependent upon the 

antenna orientation being used; GPR B-scans were compared to images from computational 

models using a Finite-Difference Time-Domain (FDTD) method-based software package 

(gprMax2D). Additionally, a field survey carried out provided images consistent with the

comparable conditions of the lab tests. The results of this work proved the capability of the GPR

method to detect and characterize cracks filled with bitumen in pavements across a range of 

crack dimensions and pavement types.

Keywords

GPR, NDT, Rigid pavements, Asphalt Pavements, Cracks, Computational models, Target orientation,

Pavement assessmen

How to cite: Rasol, M., Gracia, V. P., Solla, M., Pais, J. C., Fernandes, F. M., Santos, C., and Roberts, S.: Incorporation of GPR data into characterization of the bitumen filled cracks in pavements: Lab and numerical study , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20920, https://doi.org/10.5194/egusphere-egu2020-20920, 2020.

Recent and dramatic events occurred on the Italian transport networks have pointed out the urgent need for assessing the actual state of health along the national transport assets. Analogous considerations can be addressed towards the high exposition and vulnerability of the transport system to major natural events, such as floods or earthquake.

Recently, the administrations and managing companies have increasingly made use of non-destructive techniques for achieving a denser knowledge about the health of the asset.

However, one of the major limitations concerning these methods is that each technology, according to its specific features, is usually suitable for a single specific application and has very limited effectiveness for other tasks. Accordingly, the integration of datasets collected with different NDTs stands as a viable approach to fill technology-specific gaps, thereby ensuring a more comprehensive assessment of the infrastructure [1-3]. Data fusion logic can also potentially allow for further data interpretation from merging different information [4].

The EXTRATN project aims at overcoming the state-of-the-art research in the field of non-destructive monitoring of linear infrastructures and, through a “data fusion” logic, at achieving a comprehensive rate of knowledge about the actual condition of the asset. The addressed concept is a “fully sensed infrastructure”, being sensed by different technologies and with different scopes. Specifically, interferometric synthetic aperture radar (DInSAR), Laser Imaging Detection and Ranging (LiDAR), Ground-penetrating Radar (GPR) and Falling Weight Deflectometer (FWD) are considered to the purpose.

A system of transport infrastructure being located in the Province of Salerno (IT), within an area subjected to hydrogeological risk, has been selected as a study case for the integrated approach. This system includes a motorway, a rural highway and a railway.

As a major advantage with respect to the state-of-the-art, such a methodology allows for analysing the evolution trend of the on-going distresses, meaning a significant upgrade of the monitoring activities that may provide valuable information for a priority-based scheduling of the maintenance.

Moreover, such an approach enables to simultaneously monitor exogenous and endogenous events that may lead to a decrease of the safety, functionality or strength conditions.

The research is supported by the Italian Ministry of Education, University and Research under the National Project “Extended resilience analysis of transport networks (EXTRA TN): Towards a simultaneously space, aerial and ground sensed infrastructure for risks prevention”, PRIN 2017, Prot. 20179BP4SM.

How to cite: D'Amico, F., Ferrante, C., Bianchini Ciampoli, L., Calvi, A., and Benedetto, A.: EXTRA-TN: A novel approach for an extended resilience analysis of transport networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7230, https://doi.org/10.5194/egusphere-egu2020-7230, 2020.

How to cite: Lee, J., Kim, Y., Yeom, J., Park, S., Han, Y., and Kim, T.: Analysis of co-registration performance of KOMPSAT satellite images according to acquisition angles , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6410, https://doi.org/10.5194/egusphere-egu2020-6410, 2020.

Shipping containers provide a standard and ubiquitous way to move goods between different places and countries. In fact, a large proportion of the international trade rely on them every day. It is thus understandable the importance of improving transport security of the containers hosting those goods.

It is therefore important to detect the possibility that a container has been tampered, both for avoiding losses due to theft, both for minimizing security risks due to counterfeiting or smuggling of illegal assets as soon as possible.

Standard tampering and intrusion counter-measures include locks, hard walls or reinforced curtains, tamper evident seals, etc. Most of these solutions, however, either need that the shipping company buys suitable containers (e.g. a container with hardened walls), or invest money in adding usually active devices to them (like for IR detection systems, locks, etc.).

A different way to detect anomalies can be achieved if the focus for finding intrusion evidence shifts from containers to the intermodal terminals that will receive the goods once they are offloaded from vessels, aircrafts or trains. A few solutions already exist or are being investigated, but they are usually expensive or difficult to deploy, thus reducing their spread and adoption.

In this work, the focus is on cost-effective, transportable solutions. In this context, various sensing technologies for evaluating the integrity of a container, are being explored, both on their own merits, and in combination with others. In particular, inspection based on colour and texture, 3d shape of the container, response to hyperspectral and thermal imaging are considered. 

Based on the sensors investigation, a cost-effective prototype of a “transportable” multimodal system is being devised. Such system is complemented by colour and 3d snapshot sensors, able to scan and report anomalies on a panel container or part of it. The system is designed to inspect a container and to fit in it while not in use, for logistics consideration. This work will present a prototype being experimented, along with an investigation of the obtainable results and the necessary trade-off that are necessary to develop such a system.

How to cite: Mosca, N., Negri, S., Nitti, M., Colella, R., Renò, V., Semerano, A., and Stella, E.: A system for detection of tampering on intermodal containers, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20040, https://doi.org/10.5194/egusphere-egu2020-20040, 2020.

The South China Sea is the biggest conjugate marginal sea in the West Pacific Ocean, which is influenced by the Eurasian plate, the Pacific plate, and the Indo-Australian plate. There have developed continental tectonic margins with different characters after experiencing subduction, collision, strike-slip and so on since the Mesozoic and Cenozoic (Yao et al., 2004; Zhang et al., 2014). However, the igneous rock can be regarded as a recorder to reveal some information of evolution and deep geodynamics of the South China Sea, which helps us to improve understanding of the continental rifting, the seafloor spreading, the formation of deep water basins and the process of hydrocarbon accumulation(Zhang et al., 2016).
The igneous rocks are studied by multiple types of data that are magnetic data, seismic profiles, and drilling data in the previous studies. Hence, there are bunch of research results about the igneous rocks that contain the reason and time of formation, the distribution of space, the period of eruption in the north of the South China Sea because of the abundant datasets (Zou et al., 1993,1995; Zhou et al., Yan and Liu, 2005; Xu et al., 2013; Zhang et al., 2013; Zhang et al., 2014; Zhang et al., 2015; Zhang et al., 2016), in addition, the Pearl River Mouth Basin is the most famous one among all of the basins in the South China Sea. However, the researchs related to the south of the South China Sea where are the deep-sea are far less knowledgeable about the distribution of the igneous rocks than the north because of the limitation of datasets that are poor quality and less quantity (Yao et al., 2004; Li et al., 2010; Hui et al., 2016), which lead to the less researches with respect to the big area of the South China Sea.
The followings can be concluded from the previous studies. The northern and continental margin of the South China Sea are distributed by Cenozoic extrusive rocks with high susceptibility and low density and Yanshanian intrusive rocks with low susceptibility and density (Hao et al., 2009; Lu et al., 2011; Hui et al., 2016), the Central Sub-basin is covered by Cenozoic extrusive rocks (Yan and Liu, 2005; Hui et al., 2016), however, there are few distributions of the Yanshanian intrusive rocks in the Southern South China Sea (Zhang et al., 2015; Hui et al., 2016). In this study, a new method, the fusion of gravity and magnetic data, is applied to detect the distribution of the igneous rocks in order to provide more geophysical data in the South China Sea.

How to cite: Yang, M., Wang, W., Ji, X., Ma, T., Ma, J., and Xiong, S.: The extent of igneous rocks of the South China Sea based on the correlational analyses of gravity and magnetic data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6307, https://doi.org/10.5194/egusphere-egu2020-6307, 2020.

Ground Penetrating Radar has widely proven to be an effective tool for archaeological purposes [1-4]. Our contribution concerns a geophysical experimental activity carried out in the Maxentius Complex, an archaeological site located between the second and the third miles of the ancient Appian Way in Rome, Italy. This site is characterized by different phases dated between the end of the 3rd and the beginning of the 4th century AD. The objective of this study is to evaluate the feasibility of GPR, in this case using two different antennas (200 MHz and 600 MHz frequencies), for the structural detailing of buried roman baths structures. As a result, GPR analysis confirmed the literature-based information, i.e. to precisely locate the tanks of the thermal area (2nd century AD). The structure was partially brought to light and reburied during the second half of the last century, providing a partial plan view of the area. In addition, the tomographic results, together with the analysis of B-Scans, highlighted the presence of two further tanks, thereby suggesting the possibility of further rooms which are located close to the known ones. Furthermore, the tomographic analysis revealed a wall pattern that seems to suggest the presence of other rooms in the top-right side of the area. In general terms, GPR demonstrated a great applicability to archaeological purposes, for example to detect buried remains and to interpret the function of buried structures, despite the reliability and productivity of the data interpretation are strongly influenced by the expertise of both the geophysicists and the archaeologists involved.

This work falls within the project “ArchaeoTrack”, supported by Regione Lazio, under the Framework “L.R. 13/08, Research Group Project n. 20 prot. 85-2017-14857”.

How to cite: Santarelli, R., Bianchini Ciampoli, L., and Benedetto, A.: The use of GPR in Archaeology: the structural detailing of buried roman baths, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7042, https://doi.org/10.5194/egusphere-egu2020-7042, 2020.

Assessing internal decay in tree trunks can be of crucial importance for industrial, environmental and public safety reasons [1]. To this effect, non-destructive testing (NDT) methods can provide information on the structural condition of trees with minimum intrusion. In this work, authors have analysed the capabilities of ultrasonic tomography in evaluating the internal structure of living trees, with a special focus on the identification of internal decay areas and tree bark inclusions.

The presented ultrasonic tomography provides an image of the distribution of the ultrasonic velocity of propagation within the investigated section of a mature horse chestnut (Aesculus hippocastanum). This technique has proven its viability to detect fungal decomposition [2]. However, there exist some open issues with regard to: a) the coupling of the transducers to the tree, b) the anisotropy of the wood, c) the signal attenuation and the resolution of the tomographic inversion. To overcome these challenges, research is underway to explore the integration and new data-fusion strategies with other NDT methods, such as ground penetrating radar (GPR), which have proven their effectiveness within this area of endeavour [3].

Within this context, data have been obtained from a “diseased” horse chestnut tree located at the Kensington Gardens – The Royal Parks – in London, UK, using two different ultrasonic equipment, i.e., the PICUS Sonic Tomograph and the Arbotom Sonic Tomograph. After compilation of data, the tree was felled and cut at the two sections where ultrasonic tomography tests were performed. In more detail, 12 sensors were arranged around the perimeter of the tree in compliance with the manufacturer’s recommendations concerning the inspection methodology (sensors installed within the bark of the tree without any intrusion to the core of the tree). The adopted methodology takes to account the shape and size of the trunk [1]. The processed data were mapped against the cut sections of the tree for validity purposes.   

Results presented in this abstract are part of a major ongoing research project that the authors have undertaken for the last three years.

Acknowledgements

The authors would like to express their sincere thanks and gratitude to the following trusts, charities, organisations and individuals for their generosity in supporting this project: Lord Faringdon Charitable Trust,The Schroder Foundation,Cazenove Charitable Trust,Ernest Cook Trust,Sir Henry Keswick,Ian Bond, P.F. Charitable Trust,Prospect Investment Management Limited,The Adrian Swire Charitable Trust,The John Swire 1989 Charitable Trust,The Sackler Trust,The Tanlaw Foundation, and The Wyfold Charitable Trust. We would like to thank also Ian Rodger – Royal Parks Arboricultural Manager– for providing us with the tested tree. This paper is dedicated to the memory of our colleague and friend Jonathan West, one of the original supporters of this research project.

References

[1] Gilbert, G.S. et al. (2016). Use of sonic tomography to detect and quantify wood decay in living trees, Applications in Plant Sciences 4(12): 1600060.

[2] Bucur, V. Acoustics of Wood. CRC Press Inc., Boca Raton,Argentina (1995).

[3] Alani, A.M. et al. (2019). The Use of Ground Penetrating Radar and Microwave Tomography for the Detection of Decay and Cavities in Tree Trunks. Remote Sensing 11: 2073.

How to cite: Alani, A. M., Chambers, J., Melarange, P., Lantini, L., and Tosti, F.: The Use of Ultrasonic Tomography for the Non-destructive Assessment of Tree Trunks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20872, https://doi.org/10.5194/egusphere-egu2020-20872, 2020.

Soil compaction has direct effects on soil physical properties (increase in soil strength, bulk density, decrease in total porosity, soil aeration, water infiltration rate, and saturated hydraulic conductivity) often reducing root penetration and plant growth, thereby causing a reduction of soil productivity. However, the presence of compacted layers in rice paddy fields increases the efficiency of the traditional flooding irrigation method. For this reason, the use of monitoring tools to detect depth,  thickness and lateral continuity of compacted soil layers in paddy fields is of crucial importance for the assessment of their irrigation efficiency. Electrical Resistivity Tomography (ERT) is a non-invasive geophysical method which allows to detect soil horizons with different degrees of compaction. Particularly, arrays constituted of short electrodes spaced a few centimeters can be used to investigate with high vertical resolution the soil profile.

In a sandy loam paddy field located in the Lomellina region (PV; RISTEC project, RDP-EU, Lombardy Region), a surface ERT survey was conducted in February 2019 to verify the effectiveness of this technique in assessing soil compaction. The ERT was carried out with Wenner arrays of 48 electrodes spaced 0.1 m along a 5 m transect, to investigate the soil profile up to about 1 m depth in proximity of a soil profile trench dug for soil description and sampling. The results of the traditional soil survey (accurate description of soil horizons, including the compacted layer) were considered as reference data to evaluate the reliability of ERT results. During the ERT survey, soil samples were collected at different depths and distances along the ERT transect: texture, bulk density and porosity were successively measured in laboratory. Moreover, the volumetric soil water content was measured with a probe (ML2 ThetaProbe, Delta-T Devices). Main results show that the correlation between electrical resistivity (ER) and bulk density, soil porosity and volumetric water content is well in line with those observed in recent studies. Data points in the scatter plots are clustered based on the bulk density values; particularly, the cluster corresponding to high bulk density values (i.e. compacted soil) includes the measurement points at the depth where the ERT image shows a greater ER gradient. This depth also corresponds to the compacted layer observed during the investigation of soil profile with traditional methods. These results confirm that compacted layers can be effectively detected in ERT images by identifying depths characterized by higher ER gradients in soils with a relatively homogeneous soil texture. Consequently, an integrated approach combining surface ERT and soil sampling with a hand auger at a few depths to check the texture homogeneity and eventually collect a few soil samples for further analysis (e.g., bulk density, volumetric water content, soil hydraulic conductivity) could be explored to assess the presence and continuity of compacted layers in paddy soils, instead of intensive and extremely invasive surveys.

How to cite: Ortuani, B., Negri, C., and Facchi, A.: Surface Electrical Resistivity Tomography: a non-invasive tool to assess the compaction in paddy soils , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21132, https://doi.org/10.5194/egusphere-egu2020-21132, 2020.

  Non-destructive testing (NDT) for health monitoring of trees is a suitable candidate for detecting signs of early decay [1]. Recent developments [2,3,4] have highlighted that ground-penetrating radar (GPR) has the potential to provide with a robust and accurate detection tool with minimum computational and operational requirements in the field. In particular, a processing framework is suggested in [2] that can effectively remove ringing noise and unwanted clutter. Subsequently, an arc length parameterisation is employed in order to utilise a wheel-measurement device to accurately position the measured traces. Lastly, two migration schemes; Kirchhoff and reverse-time migration, are successfully applied on numerical and laboratory data in [3].

  In the current paper, the detection scheme described in [2,3] using reverse-time migration is tested in two case studies that involve diseased urban trees within the greater London area, UK (Kensington and Gunnersbury park). Both of the trees were cut down after the completion of the measurements and furthermore cut into several slices to get direct information with regards to their internal structure. The processing scheme described in [3,4] managed to adequately detect the internal decay present in both trees. The aforementioned case studies provide coherent evidences to support the premise that GPR is capable of detecting decay in diseased trunks and therefore has the potential to become an accurate and efficient diagnostic tool against emerging infectious diseases of trees.

Acknowledgements

The authors would like to express their sincere thanks and gratitude to the following trusts, charities, organizations and individuals for their generosity in supporting this project: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook, Sir Henry Keswick, Ian Bond, P. F. Charitable Trust, Prospect Investment Manage- ment Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation and The Wyfold Charitable Trust.

  This paper is dedicated to the memory of Jonathon West, a friend, a colleague, a forester, a conservationist and an environmentalist who died following an accident in the woodland that he loved.

References

[1] P. Niemz, D. Mannesm, ”Non-destructive testing of wood and wood-based materials,” J. Cult. Heritage, vol. 13, pp. S26-S34, 2012.

[2] I. Giannakis, F. Tosti, L. Lantini and A. M. Alani, "Health Monitoring of Tree Trunks Using Ground Penetrating Radar," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 10, pp. 8317-8326, 2019.

[3] I. Giannakis, F. Tosti, L. Lantini and A. M. Alani, "Diagnosing Emerging Infectious Diseases of Trees Using Ground Penetrating Radar," IEEE Transactions on Geoscience and Remote Sensing, Early Access, doi: 10.1109/TGRS.2019.2944070 

[4] A. M. Alani, F. Soldovieri, I. Catapano, I. Giannakos, G. Gennarelli, L. Lantini, G. Ludeno and F. Tosti, “The Use of Ground Penetrating Radar and Microwave Tomography for the Detection of Decay and Cavities in Tree Trunks,” Remote Sensing, vol. 11, no. 18, 2019.

How to cite: Giannakis, I., Tosti, F., Zou, L., Lantini, L., and Alani, A. M.: Tree Monitoring Using Ground Penetrating Radar: Two Case Studies Using Reverse-Time Migration, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19697, https://doi.org/10.5194/egusphere-egu2020-19697, 2020.