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This paper describes the new opportunities made possible by the X-band radar systems for monitoring and management of infrastructures in coastal areas as well as for offshore platforms. In particular, the paper presents the effectiveness and the reliability of the Remocean system, a X-band radar developed at IREA-CNR, as observational tool for the support of the Costa Concordia ship wreck removal and as a scientific opportunity to observe wave phenomena rarely observable in deep sea.

We report a geophysical study across an active normal fault in the Southern Apennines. The surveyed area is the “Il Lago” Plain (Pettoranello del Molise), at the foot of Mt. Patalecchia (Molise Apennines, Southern Italy), a small tectonic basin filled by Holocene deposits located at the NW termination of the major Quaternary Bojano basin structure. This basin, on the NE flank of the Matese Massif, was the epicentral area of the very strong 26 July, 1805, Sant’Anna earthquake (I0 = X MCS, Mw = 6.7). The “Il Lago” Plain is bordered by a portion of the right-stepping normal fault system bounding the whole Bojano Quaternary basin (28 km long). The seismic source responsible for the 1805 earthquake is regarded as one of the most hazardous structures of the Apennines; however, the position of its NW boundary of this seismic source is debated. Geological, geomorphological and macroseismic data show that some coseismic surface faulting also occurred in correspondence with the border fault of the “Il Lago” Plain. The study of the “Il Lago” Plain subsurface might help to constrain the NW segment boundary of the 1805 seismogenic source, suggesting that it is possibly a capable fault, source for moderate (Mw < 5.5) to strong earthquakes (Mw ≥ 5.5). Therefore, we constrained the geometry of the fault beneath the plain using low-frequency Ground Penetrating Radar (GPR) data supported by seismic tomography. Seismic tomography yielded preliminary information on the subsurface structures and the dielectric permittivity of the subsoil. A set of GPR parallel profiles allowed a quick and high-resolution characterization of the lateral extension of the fault, and of its geometry at depth. The result of our study demonstrates the optimal potential of combined seismic and deep GPR surveys for investigating the geometry of buried active normal faults. Moreover, our study could be used for identifying suitable sites for paleoseismic analyses, where record of earthquake surface faulting might be preserved in Holocene lacustrine sedimentary deposits. The present case demonstrates the possibility to detect with high accuracy the complexity of a fault-zone within a basin, inferred by GPR data, not only in its shallower part, but also down to about 100 m depth.

This paper deals with a geophysical survey carried out in some critical urban areas of the historical city of Matera (Southern Italy). Matera has a very complex shallower stratigraphy characterized by both anthropic and natural “targets” and is affected by geological instability. Therefore, Matera represents an ideal and very challenging outdoor laboratory for testing novel approaches for near-surface explorations in urban areas. Here, we present the results of a near-surface survey carried out by jointly applying Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) methods. The survey was implemented in three different critical zones within the urban area of Matera (Piazza Duomo, Piazza San Giovanni, Villa dell’Unità d’Italia). These test sites are of great interest for archaeological and architectonical studies and are affected by ground instability phenomena due to the presence of voids, cavities and other anthropic structures. The effectiveness of the survey was enhanced by the exploitation of advanced 3D tomographic approaches, which allowed to achieve 3D representation of the investigated underground and obtain information in terms of both the location and the geometry of buried objects and structures and the characterization of shallow geological layers. The results of the surveys are now under study (or have attracted the interest) of the Municipality in order to support smart cities programs and activities for a better management of the underground space.

This paper deals with a feasibility study assessing the reconstruction capabilities of a small Multicopter-Unmanned Aerial Vehicle (M-UAV) based radar system, whose flight positions are determined by using the Carrier-Phase Differential GPS (CDGPS) technique. The paper describes the overall radar imaging system in terms of both hardware devices and data processing strategy for the case of a single flight track. The data processing is cast as the solution of an inverse scattering problem and is able to provide focused images of on surface targets. In particular, the reconstruction is approached through the adjoint of the functional operator linking the unknown contrast function to the scattered field data, which is computed by taking into account the actual flight positions provided by the CDGPS technique. For this inverse problem, we provide an analysis of the reconstruction capabilities by showing the effect of the radar parameters, the flight altitude and the spatial offset between target and flight path on the resolution limits. A measurement campaign is carried out to demonstrate the imaging capabilities in controlled conditions. Experimental results referred to two surveys performed on the same scene but at two different UAV altitudes verify the consistency of these results with the theoretical resolution analysis.

In this contribution, we present some results achieved in the archaeological site of Le Cesine, close to Lecce, in southern Italy. The investigations have been performed in a site close to the Adriatic Sea, only slightly explored up to now, and where the presence of an ancient Roman harbour is alleged on the basis of remains visible above all under the current sea level. This measurement campaign has been performed in the framework of a short-term scientific mission (STSM) performed in the framework of the European Cost Action 17131 (acronym SAGA), and has been aimed to identify possible points where future localized excavation might and hopefully will be performed in the next few years. Both a traditional elaboration and an innovative data processing based on a linear inverse scattering model have been performed on the data., peer-reviewed

Aggressive fungal and insect attacks have reached an alarming level, threatening a variety of tree species, such as ash and oak trees, in the United Kingdom and beyond. 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. 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 regarding the existence of defects and anomalies within 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 decay and cavities in trees. The microwave tomographic approach is able to pinpoint explicitly the position of the measurement points on the tree surface and thus to consider the actual geometry of the sections beyond the classical (circular) ones. The robustness of the microwave tomographic approach with respect to noise and data uncertainty is tackled by exploiting a regularised scheme in the inversion process based on the Truncated Singular Value Decomposition (TSVD). A demonstration of the potential of the microwave tomography approach is provided for both simulated data and measurements collected in controlled conditions. First, the performance analysis was carried out by processing simulated data achieved by means of a Finite-Difference Time-Domain (FDTD) in three scenarios characterised by different geometric trunk shapes, internal trunk configurations and target dimensions. Finally, the method was validated on a real trunk by proving the viability of the proposed approach in identifying the position of cavities and decay in tree trunks.

The efficient use of water in agriculture is one of the most significant agricultural challenges that modern technologies are helping to cope with through Irrigation Advisory Services (IAS) and Decision Support Systems (DSS). These last are considered powerful management instruments able to help farmers achieve the best efficiency in irrigation water use and to increase their incomes through obtaining the highest possible crop yield. In this context, within the project "An advanced low cost system for farm irrigation support - LCIS" (a joint Italian-Israeli R&D project), a fully transferable DSS for irrigation support, based on three different methodologies representative of the state of the art in irrigation management tools (W-Tens, in situ soil sensor; IRRISAT®, remote sensing; W-Mod, simulation modelling of water balance in the soil-plant and atmosphere system), has been developed. These three LCIS-DSS tools have been evaluated, in terms of their ability to support the farmer in irrigation management, in a real applicative case study on maize grown on Andosols in a private farm in southern Italy in the 2018 season. The evaluation considered the predictive performance of the tools and also the pros and cons of their application, due their different spatial scale applicability, costs and complexity of use. The results have shown that all three approaches are able to realise the maximum obtainable maize production. However, the method based on in situ soil sensor (W-Tens) supplied 40% more water compared to the other two methods, whereas the IRRISAT® and W-Mod approaches represent the best solution in terms of irrigation water use efficiency (IWUE). Moreover, IRRISAT® has the advantage of being able to work without soil spatial information, although unlike W-Tens both the latter methods need a high level of user expertise and consequently support of external service providers. Integration between different tools represents an opportunity for improved water use efficiency in agriculture (e.g., field sensors and remote sensing).

The paper deals with subsurface imaging via radar systems mounted onboard aerial platforms. Specifically, the attention is focused on a radar prototype installed on a small unmanned aerial vehicle (S-UAV), previously proposed by few of the authors. In particular, the challenges in terms of electromagnetic modeling and flight dynamics knowledge and control are here tackled. In this frame, an ad-hoc designed data processing strategy is presented; this strategy involves a pre-processing step and a reconstruction step. The pre-processing is performed in time domain and, beyond filtering procedures commonly exploited in radar imaging, involves a procedure devoted to compensate flight altitude variations and to account for the S-UAV trajectory, which is estimated by processing measurements collected by an onboard GPS receiver. In addition, the reconstruction of the investigated scenario is performed by means of a microwave tomographic approach based on a linear model of the electromagnetic scattering and the concept of equivalent dielectric permittivity for the propagation path. This latter allows us to properly face the imaging of buried objects, while avoiding the mathematical complexity introduced by the presence of the air-medium interface. Accordingly, the imaging is faced as a linear inverse scattering problem formulated in the spatial domain similarly to the case of a homogeneous scenario and, thanks to the concept of equivalent permittivity, depth and horizontal position of buried objects are retrieved properly. This is corroborated by means of a numerical analysis accounting for synthetic data.

In this century, one of the main objectives of agriculture is sustainability addressed to achieve food security, based on the improvement of use efficiency of farm resources, the increasing of crop yield and quality, under climate change conditions. The optimization of farm resources, as well as the control of soil degradation processes (e.g., soil erosion), can be realized through crop monitoring in the field, aiming to manage the local spatial variability (time and space) with a high resolution. In the case of high profitability crops, as the case of vineyards for high-quality wines, the capability to manage and follow spatial behavior of plants during the season represents an opportunity to improve farmer incomes and preserve the environmental health. However, any field monitoring represents an additional cost for the farmer, which slows down the objective of a diffuse sustainable agriculture. Satellite multispectral images have been widely used for production management in large areas. However, their observation is limited by the pre-defined and fixed scale with relatively coarse spatial resolution, resulting in limitations in their application. In this paper, encouraged by recent achievements in convolutional neural network (CNN), a multiscale full-connected CNN is constructed for the pan-sharpening of Sentinel-2A images by UAV images. The reconstructed data are validated by independent multispectral UAV images and in-situ spectral measurements. The reconstructed Sentinel-2A images provide a temporal evaluation of plant responses using selected vegetation indices. The proposed methodology has been tested on plant measurements taken either in-vivo and through the retrospective reconstruction of the eco-physiological vine behavior, by the evaluation of water conductivity and water use efficiency indexes from anatomical and isotopic traits recorded in vine trunk wood. In this study, the use of such a methodology able to combine the pro and cons of space-borne and UAVs data to evaluate plant responses, with high spatial and temporal resolution, has been applied in a vineyard of southern Italy by analyzing the period from 2015 to 2018. The obtained results have shown a good correspondence between the vegetation indexes obtained from reconstructed Sentinel-2A data and plant hydraulic traits obtained from tree-ring based retrospective reconstruction of vine eco-physiological behavior.

Radar mounted onboard micro-UAV is an early stage technology and its potentiality is far from being focused, even if radar sensors having costs compatible with micro-UAV are currently developed. As a contribution to this topic, this paper describes a radar-equipped hexacopter assembled thanks to complementary skills available at IREA and DII. In order to test the operation mode of the system as well as to investigate its target detection and localization capabilities, a feasibility experiment has been carried out in December 2016. The results of this flight campaign are presented, in terms of both raw data and images obtained by means of an ad-hoc data processing approach. These results provide an encouraging preliminary proof of the achievable outcomes.

This paper deals with exploitation of the wave radar system for sea surface current estimation in a coastal zone. In particular, we present the results of the processing of the radar data collected by an X-band marine radar installed in Capo Granitola site, which is located in the south-west part of Sicily, on 15 May 2015. The effectiveness of the data processing is analyzed by comparing the wave radar estimated sea surface current with that provided by the Lagrangian drifters along its movement trajectory. During the measurement campaign, three drifter releases are carried out and for each one the comparison is provided in terms of the mean error and standard deviation. In addition, we report the characteristic sea state parameters, in terms of peak wavelength (lp), peak direction propagation (qp), peak period (Tp) and significant wave height (Hs) of the dominant waves estimated by the wave radar system.

Summary A variety of tree species, such as ash and oak trees, are nowadays under serious threat in the United Kingdom and European territories as a result of the action of aggressive fungal diseases. To this effect, Ground Penetrating Radar (GPR) is an effective geophysical tool capable of collecting information on the internal structure of trees. Nevertheless, traditional processing methods can provide only limited indications for health monitoring purposes. In this study, a demonstration of the GPR potential and the use of a tomographic inversion approach in detecting decay and cavities is provided. In that context, a set of finite-difference time-domain (FDTD) simulations of different complexity (i.e. internal trunk configurations and dimensions of the targets) were used to assess the performance of the proposed strategy. The results prove the viability of the proposed approach in identifying the position of cavities and decay in tree trunks.