Enrico Chiarelli

Innovative applications of high-resolution airborne imaging are explored for detecting grapevine diseases. Driven by the motivation to enhance early disease detection, the method’s effectiveness lies in its capacity to identify isolated cases of grapevine yellows (Flavescence dorée and Bois Noir) and trunk disease (Esca complex), crucial for preventing the disease from spreading to unaffected areas. Conducted over a 17 ha vineyard in the Forlì municipality in Emilia-Romagna (Italy), the aerial survey utilized a photogrammetric camera capturing centimeter-level resolution images of the whole area in 17 minutes. These images were then processed through an automated analysis leveraging RGB-based spectral indices (Green–Red Vegetation Index—GRVI, Green–Blue Vegetation Index—GBVI, and Blue–Red Vegetation Index—BRVI). The analysis scanned the 1.24 · 10⁹ pixels of the orthomosaic, detecting 0.4% of the vineyard area showing evidence of disease. The instances, density, and incidence maps provide insights into symptoms’ spatial distribution and facilitate precise interventions. High specificity (0.96) and good sensitivity (0.56) emerged from the ground field observation campaign. Statistical analysis revealed a significant edge effect in symptom distribution, with higher disease occurrence near vineyard borders. This pattern, confirmed by spatial autocorrelation and non-parametric tests, likely reflects increased vector activity and environmental stress at the vineyard margins. The presented pilot study not only provides a reliable detection tool for grapevine diseases but also lays the groundwork for an early warning system that, if extended to larger areas, could offer a valuable system to guide on-the-ground monitoring and facilitate strategic decision-making by the authorities.

In the Caleri lagoon, a coastal lagoon in the Po River Delta, Northern Adriatic, the transplant of the dwarf eelgrass Zostera noltei was used as a nature-based solution to attempt the ecological restoration of a previously depleted lagoon area. A total of 135 15-cm-diameter sods were transplanted, with the donor site at the Venice lagoon. Using unmanned aerial vehicles (UAVs), eelgrass transplants were mapped and monitored with great precision. After two years, the area covered by eelgrass increased from the initial 2.5 m² to 60 m². Changes in the community structure and on the frequency of biological traits of macrobenthos occurred at the transplant site, with a higher frequency of epifaunal predators and herbivores, and of organisms with longer life spans and larger body sizes. Sensitive and indifferent taxa were always higher in the transplant site than in the bare bottom control site, where opportunistic taxa continued to dominate. Ecological quality status measured through M-AMBI and HBFI indices showed a clear improvement in the transplant site. The rapid changes in benthos demonstrate that even relatively small-scale transplantation of dwarf eelgrass can restore faunal communities very rapidly.

In the Caleri lagoon, a coastal lagoon in the Po River Delta, Northern Adriatic, the transplant of the dwarf eelgrass Zostera noltei was used as a nature-based solution to attempt the ecological restoration of a previously depleted lagoon area. A total of 135 15 cm diameter sods were transplanted, with the donor site at the Venice lagoon. Using unmanned aerial vehicles (UAVs), eelgrass transplants have been mapped and monitored with great precision. After 2 years, the area covered by eelgrass increased from the initial 2.5 m2 to 60 m2. Changes in the community structure and on the frequency of biological traits of macrobenthos occurred at the transplant site, with a higher frequency of epifaunal predators and herbivores, of organisms with longer life spans and larger body sizes. Sensitive and indifferent taxa were always higher in the transplant site than in the bare bottom control site, where opportunistic taxa continued to dominate. Ecological quality status measured through M-AMBI and HBFI indices showed a clear improvement in the transplant site. The rapid changes in benthos demonstrate that even relatively small-scale transplantation of dwarf eelgrass can restore faunal communities very rapidly.

Using a novel joint inversion approach, this study tackles the challenge of accurately characterizing subsurface electrical resistivity in vineyards, a critical and strategic aspect of precision viticulture. For the first time, we integrate 3D Galvanic Contact Resistivity with multi-2D Capacitively Coupled Resistivity data. Conducted in a prestigious Sangiovese vineyard in Montalcino (Tuscany, Italy), the data are analyzed utilizing a single algorithm capable of inverting Capacitively Coupled Resistivity, Galvanic Contact Resistivity, and joint datasets. This approach combines data sensitive to different depths and spatial resolutions, resulting in a comprehensive analysis of soil resistivity variations and moisture distribution, thus providing a detailed and coherent subsurface model. The joint inversion produced a high spatial resolution 3D resistivity model with a density of 20.21 data/m³. This model significantly enhances subsurface characterization, delineating root systems and correlating water distribution with resistivity patterns, showing relative variations sometimes greater than 50%. This method reduced data misfit more effectively than individual inversions and identified a low-resistivity volume (<20 Ω·m), extending from northeast to south, indicating the presence of subsurface water. The systematic alternation of high and low resistivity across vineyard rows highlights the impact of soil management activities on resistivity and supports targeted interventions for vineyard health.

Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in the Mezzano Lowland (Italy), a 189 km² agricultural plain investigated through a dedicated airborne gamma-ray spectroscopy survey. The K and Th abundances were used to retrieve the clay and sand content by means of a multi-approach method. Linear (simple and multiple) and non-linear (machine learning algorithms with deep neural networks) predictive models were trained and tested adopting a 1:50,000 scale soil texture map. The comparison of these approaches highlighted that the non-linear model introduces significant improvements in the prediction of soil texture fractions. The predicted maps of the clay and of the sand content were compared with the regional soil maps. Although the macro-structures were equally present, the airborne gamma-ray data permits us shedding light on finer features. Map areas with higher clay content were coincident with paleo-channels crossing the Mezzano Lowland in Etruscan and Roman periods, confirmed by the hydrographic setting of historical maps and by the geo-morphological features of the study area.

Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in the Mezzano Lowland (Italy), a 189 km² agricultural plain investigated through a dedicated airborne gamma-ray spectroscopy survey. The K and Th abundances were used to retrieve the clay and sand content by means of a multi-approach method. Linear (simple and multiple) and non-linear (machine learning algorithms with deep neural networks) predictive models were trained and tested adopting a 1:50,000 scale soil texture map. The comparison of these approaches highlighted that the non-linear model introduces significant improvements in the prediction of soil texture fractions. The predicted maps of the clay and of the sand content were compared with the regional soil maps. Although the macro-structures were equally present, the airborne gamma-ray data permits us shedding light on finer features. Map areas with higher clay content were coincident with paleo-channels crossing the Mezzano Lowland in Etruscan and Roman periods, confirmed by the hydrographic setting of historical maps and by the geo-morphological features of the study area.

This study presents the map of the external effective annual dose rate (1:200,000 scale) due to terrestrial and cosmic radiation. The terrestrial dose is assessed via gamma ray spectroscopy combining radiometric data from airborne surveys and laboratory measurements. The geostatistical method Collocated CoKriging is used for the spatial interpolation of the sparse gamma ray data, adopting a high-resolution geological map as ancillary information. The obtained numerical map is integrated with the cosmic radiation effective dose rate calculated using the CARI-7 software tool that considers the effects of altitude, latitude, and the solar magnetic activity cycle. The absorbed dose rate due to radioactivity of the main lithological groups is studied and, for the most populated municipalities, the population-weighted average effective dose is also calculated. For future generations, this map will be a reference tool for evaluating radiological effects in case of accidental events like radioactive fallout or environmental contaminations.

The scarcity of water due to climate change is endangering worldwide the production, quality, and economic viability of growing wine grapes. One of the main mitigation measures to be adopted in the viticulture sector will be an adequate irrigation strategy. Irrigation involves an increasing demand for water, a natural limited resource with increasing availability problems for the foreseeable future. Therefore, the development of a precision irrigation system, which is able to manage the efficient use of water and to monitor the crop water stress, is an important research topic for viticulture. This paper, through the analysis of a case study, aims to describe the prototype of a software platform that integrates data coming from different innovative remote and proximal sensors to monitor the hydric stress status of the vineyard. In addition, by using a cost analysis of grape cultivation and implementing economic indices, this study examines the conditions by which irrigation strategies may be economically justified, helping the decision-making process. By combining different sensors, the platform makes it possible to assess the spatial and temporal variability of water in vineyards. In addition, the output data of the platforming, matched with the economic indices, support the decision-making process for winemakers to optimize and schedule water use under water-scarce conditions.

The accurate knowledge of seabed properties is in increasing demand for telecommunication companies, national governments, military forces, academic institutions and oil and gas corporations. Recently the quality of bathymetry and seafloor mapping extraordinarily improved thanks to the employment of Autonomous Underwater Vehicles, which mount on board multiparametric instruments such as high resolution multibeam echo sounders, synthetic aperture sonars, sub bottom profilers, magnetometers, camera laser profilers and environmental sensors.The fruition of this huge amount of high-resolution information is often limited to advanced experts on GIS software which requires a long and steep learning curve in addition to a properly equipped workstation. With the increasing interest in bathymetry and oceanography from the larger community, the challenge is definitively to improve the visualization and the online handling for users with little familiarity on sophisticated applications.For this purpose, we developed a Plotly Dash (an open-source Python library) web-based GIS application for real time rendering of 3D high-resolution bathymetric data. An easy-to-interpret and easy-to-manage visualization is obtained through the creation of an interactive 2D map with Mapbox (a provider of custom online maps) for positioning in the world and for selecting bathymetric data. The user can also easily set different visualization parameters such as depth color scales and the stage lighting and shadowing to enhance the seabed details.For an optimized usability on mobile devices, the web application loads the 3D model obtained from a raster flexible interpolation. The rendering speed is further boosted by automatically varying the 3D mesh resolution in accordance with the extension of the selected region.Starting from an ASCII file containing depth and coordinates data together with their map projection system, our innovative tool automatically organizes the data into a raster file with the WGS84 spatial reference system. Data collected from different surveys can therefore be effortlessly processed, managed, and visualized.

Vertical take-off and landing Unmanned Aerial Vehicles (UAVs) for Gamma-Ray Surveys (GRS) provide a cost-effective and timely approach tool for environmental radioactivity mapping. The UAV technique combines the advantages of ground and airborne measurements:  there is no need for an airport for take-off and landing, and high spatial resolution surveys can also be performed in dangerous areas without endangering the operators.The main limitation of existing UAVs for GRS is the lack of software and hardware integration between avionics systems and radiation detectors. RadHawk fills this gap with an advanced mechanical, electronic, and software connection between a specifically developed quadcopter and a digital Multi-Channel Analyzer GammaStream (GS). The GS is coupled with a 2” CeBr3 scintillator having spectral energy resolution ~60% better than that of a NaI for 137C detection. Communication between the GS onboard microcomputer and the drone’s autopilot Pixhawk is achieved through a custom protocol which allows sharing telemetry updates and executing commands.The best spatial resolution of radiometric data is achieved through a list mode real-time processing that generates, with optimized acquisition time, energy calibrated georeferenced gamma spectra. A radio frequency transceiver module sends data to a control station, where the user can easily control the flight path and check the artificial radionuclides warning for real-time identifying of hotspots.A post-processing algorithm based on a Full Spectrum Analysis – Maximum Likelihood Estimation was developed to enhance the identification capability of anthropogenic radionuclides and to produce maps of the K, Th and U abundances of the investigated areas.