On the Combined Use of Ground Penetrating Radar and Crack Meter Sensors for Structural Monitoring: Application to the Historical Consoli Palace in Gubbio, Italy

The paper deals with joint use of non-invasive monitoring technologies and civil engineering analysis methods aimed at providing multi-sensing information about the structural health of historical and cultural assets. Specifically, linear variable displacement transducers (LVDT) and ground penetrating radar (GPR) are considered for monitoring a significant crack affecting the Consoli Palace in Gubbio, Italy, precisely one of the walls of the cross-hall leading to the Loggia. In this frame, LVDT is adopted to control horizontal amplitude variations of the crack, while GPR is applied to investigate the wall interior and to detect the occurrence of inner issues related to the visible appearance of the crack on the wall surface. The effectiveness of GPR surveys is improved by means of a microwave tomography-based data processing strategy. The main result is that there is a consistency between the monitoring outputs of LVDT, which allowed us to display the crack widening/contraction due to the seasonal temperature variations, and the fact that no significant changes of the geometry of the inner areas of the walls were observed by the GPR

Gpr investigation at the archaeological site of le cesine, lecce, italy

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

Combining numerical simulations and normalized scalar product strategy: A new tool for predicting beach inundation

The skills of the Normalized Scalar Product (NSP) strategy, commonly used to estimate the wave field, as well as bathymetry and sea-surface current, from X-band radar images, are investigated with the aim to better understand coastal inundation during extreme events. Numerical simulations performed using a Nonlinear Shallow-Water Equations (NSWE) solver are run over a real-world barred beach (baseline tests). Both bathymetry and wave fields, induced by reproducing specific storm conditions, are estimated in the offshore portion of the domain exploiting the capabilities of the NSP approach. Such estimates are then used as input conditions for additional NSWE simulations aimed at propagating waves up to the coast (flood simulations). Two different wave spectra, which mimic the actual storm conditions occurring along the coast of Senigallia (Adriatic Sea, central Italy), have been simulated. The beach inundations obtained from baseline and flood tests related to both storm conditions are compared. The results confirm that good predictions can be obtained using the combined NSP-NSWE approach. Such findings demonstrate that for practical purposes, the combined use of an X-band radar and NSWE simulations provides suitable beach-inundation predictions and may represent a useful tool for public authorities dealing with the coastal environment, e.g., for hazard mapping or warning purposes

Nearshore Observations and Modeling: Synergy for Coastal Flooding Prediction

Coastal inundation has recently started to require significant attention worldwide. The increasing frequency and intensity of extreme events (sea storms, tsunami waves) are highly stressing coastal environments by endangering a large number of residential areas, ecosystems, and tourist facilities, and also leading to potential environmental risks. Predicting such events and the generated coastal flooding is thus of paramount importance and can be accomplished by exploiting the potential of different tools. An example is the combination of remote sensors, like marine radars, with numerical models. Specifically, while instruments like X-band radars are able to precisely reconstruct both wave field and bathymetry up to some kilometers off the coast, wave-resolving Boussinesq-type models can reproduce the wave propagation in the nearshore area and the consequent coastal flooding. Hence, starting from baseline simulations of wave propagation and the conversion of water elevation results into radar images, the present work illustrates the reconstruction of coastal data (wave field and seabed depth) using a specifically suited data processing method, named the “Local Method”, and the use of such coastal data to run numerical simulations of coastal inundation in different scenarios. Such scenarios were built using two different European beaches, i.e., Senigallia (Italy) and Oostende (Belgium), and three different directional spreading values to evaluate the performances in cases of either long- or short-crested waves. Both baseline and inundation simulations were run using the FUNWAVE-TVD solver. The overall validation of the methodology, in terms of maximum inundation, shows its good performance, especially in cases of short-crested wind waves. Furthermore, the application on Oostende Beach demonstrates that the present methodology might work using only open-access tools, providing an easy investigation of coastal inundation and potential low-cost integration into early warning system

The Discovery of a buried temple in Paestum: The advantages of the geophysical multi-sensor application

Southern Italy is characterized by important archaeological sites developed during the pre-roman period. Among these, Paestum and Velia Archaeological Park, located in the Campania region, represents one of the most important and well-preserved sites of the Magna Graecia. During the last year, several unexpected archaeological findings have permitted the supposition of the presence of another undiscovered temple at Paestum, in a not yet investigated area of the site, close to the fortification walls (Western City Walls) of the ancient city and a few meters away from the gate of Porta Marina. To support this amazing hypothesis, the Paestum and Velia Archaeological Park and the National Research Council planned an accurate campaign of geophysical surveys, based on the combined use of Geomagnetic and Ground Penetrating Radar methodologies. The results of the geophysical surveys have effectively supported the detection of the temple, providing detailed information about its location and highlighting the geometry of the basement of the structure with high accuracy. The discovery sheds new light on the archaeological and architectonic history of the site and may represent one of the most relevant archaeological discoveries of the XXI century performed in Italy

UAV radar imaging for target detection

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

Small multicopter-UAV-based radar imaging: Performance assessment for a single flight track

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

A smart multiple spatial and temporal resolution system to support precision agriculture from satellite images: Proof of concept on Aglianico vineyard

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

A micro-UAV-borne system for radar imaging: A feasibility study

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