Andrea Berton

Forestry applications of UAVs in Europe: a review

ABSTRACT Unmanned aerial vehicles (UAVs) or remotely piloted aircraft systems are new platforms that have been increasingly used over the last decade in Europe to collect data for forest research, thanks to the miniaturization and cost reduction of GPS receivers, inertial navigation system, computers, and, most of all, sensors for remote sensing. In this review, after describing the regulatory framework for the operation of UAVs in the European Union (EU), an overview of applications in forest research is presented, followed by a discussion of the results obtained from the analysis of different case studies. Rotary-wing and fixed-wing UAVs are equally distributed among the case studies, while ready-to-fly solutions are preferred over self-designed and developed UAVs. Most adopted technologies are visible-red, green, and blue, multispectral in visible and near-infrared, middle-infrared, thermal infrared imagery, and lidar. The majority of current UAV-based applications for forest research aim to inventory resources, map diseases, classify species, monitor fire and its effects, quantify spatial gaps, and estimate post-harvest soil displacement. Successful implementation of UAVs in forestry depends on UAV features, such as flexibility of use in flight planning, low cost, reliability and autonomy, and capability of timely provision of high-resolution data. Unfortunately, the fragmented regulations among EU countries, a result of the lack of common rules for operating UAVs in Europe, limit the chance to operate within Europe’s boundaries and prevent research mobility and exchange opportunities. Nevertheless, the applications of UAVs are expanding in different domains, and the use of UAVs in forestry will increase, possibly leading to a regular utilization for small-scale monitoring purposes in Europe when recent technologies (i.e. hyperspectral imagery and lidar) and methodological approaches will be consolidated.

Assessment of a canopy height model CHM in a vineyard using UAV-based multispectral imaging

ABSTRACT Biomass is one of the most important parameters in order for the farmer to choose the best canopy management within the field and it can be estimated using plant canopy height. In combination with a non-vegetation ground model, plant height can be obtained by quantifying the height of a canopy using crop surface models (CSMs). A modified Mikrokopter Okto unmanned aerial vehicle (UAV) acquired high-resolution multispectral images (4 cm) and a processing chain was developed to construct a 3D digital surface model (DSM) for the creation of precise digital terrain models (DTMs) based on Structure from Motion (SfM) computer vision algorithms. The DTM was then subtracted from the DSM to obtain a canopy height model (CHM) of a vineyard. The results show a good separation of ground pixels from vine rows, but their elevations were not quite in accordance with the actual height of the vines due to a smoothing effect of the reconstructed CHM. A further comparison between CHM and a vigour map obtained from normalized difference vegetation index (NDVI) values showed a good correlation. A preliminary assessment of biomass volume was made using the average canopy height and vine row width for three different homogeneous classes. This is a preliminary study on how a 3D model developed by UAV images can be useful for a simple and prompt biomass evaluation.

Hardware and software modifications on the Advion NanoTek microfluidic platform to extend flexibility for radiochemical synthesis.

Microfluidic systems are currently receiving a lot of attention in the PET radiochemistry field, due to their demonstrated ability to obtain higher incorporation yields with reduced total processing time and using a decreased amount of precursors. The Advion NanoTek LF was the first commercial microfluidic system available for radiochemistry that allows basic parameter optimization to be performed. In this paper we report hardware and software modifications that would allow better performing procedures, higher product throughput and flexibility to utilize the system. In particular, HPLC purification and SPE formulation have been fully integrated.

Development of an automated modular system for the synthesis of [11C]acetate.

BackgroundCarboxylation reactions offer a straightforward method for the synthesis of carbon-11 labelled carboxylic acids. Among these, the preparation of carbon-11 (11C)-acetate is receiving increasing attention because of diagnostic applications in oncology in addition to its well-established use as a probe for myocardial oxidative metabolism. Although a number of dedicated modules are commercially available, the development of the synthesis on flexible platforms would be beneficial to widen the number of tracers, in particular for preclinical assessment and testing. MethodsIn this study, the carboxylation reaction was implemented for the synthesis of sodium 1-[11C]acetate after the classic route of carboxylation of methylmagnesium chloride by [11C]carbon dioxide, followed by the acidic hydrolysis, purification and sterile filtration. This was performed using a commercially available kit of preassembled hardware units and fully compatible components of radiochemistry automation (VarioSystem). ResultsThe system proved be to highly versatile and inexpensive and allowed a quick translation of the radiochemistry project into a working system even by less experienced personnel, because of predefined interfaces between electronic parts and operating software (preloaded on a laptop and included in the kit). The automatic module proved to be a simple and reliable system for the production of 1-[11C]acetate that was prepared in 24 min (total synthesis time) with stable radiochemical yields (20% nondecay corrected) and high radiochemical purity (>97%). The module is used routinely to produce 1-[11C]acetate for preclinical studies and is being implemented for the production of the labelled fatty acids.

UAV-based high-throughput phenotyping to discriminate barley vigour with visible and near-infrared vegetation indices

ABSTRACT In the context of plant breeding, high-throughput phenotyping is an assessment of plant phenotypes on a scale and with a level of speed and precision not achievable with traditional methods, through the application of emerging technologies such as automation and robotics, new sensors, and imaging technologies (hardware and software). In the present work, high-resolution digital images have been acquired with an unmanned aerial vehicle (UAV) prototype platform on an experimental phenotyping barley field. Six vegetation indices generated from the red–green–blue and near-infrared-based images were calculated for 912 experimental barley plots and provided high correlation with the indices determined from hyperspectral data taken at the ground (gt); the indices performance in discriminating the vigour of genotypes was finally assessed.

Evaluation of spectral-based and canopy-based vegetation indices from UAV and Sentinel 2 images to assess spatial variability and ground vine parameters

New remote sensing technologies have provided unprecedented results in vineyard monitoring. The aim of this work was to evaluate different sources of images and processing methodologies to describe spatial variability of spectral-based and canopy-based vegetation indices within a vineyard, and their relationship with productive and qualitative vine parameters. Comparison between image-derived indices from Sentinel 2 NDVI, unfiltered and filtered UAV NDVI and with agronomic features have been performed. UAV images allow calculating new non-spectral indices based on canopy architecture that provide additional and useful information to the growers with regards to within-vineyard management zone delineation.

Performances of a TRACERlab FX C synthesis module using a Ni-nanopowder/molecular sieves mixed catalyst

The progress of positron emission tomography goes together with an increasing demand for new radiopharmaceuticals: among these, the development of radiopharmaceuticals labelled with carbon-11 is particularly interesting because these compounds are biologically indistinguishable from their stable analogues. These radiotracers are prepared starting from [11C]carbon dioxide, the most common and versatile primary labelling precursor, or from secondary labelling precursors such [11C]methyl iodide produced by “wet” or “gas-phase” method. The gas-phase is the most used method and consists in the radical reaction of iodine vapours with [11C]methane, produced in target or from [11C]carbon dioxide by reduction with hydrogen on nickel catalyst at high temperature. This second approach is frequently adopted in commercial automatic methylation modules, such as the TRACERlab FX C. When not performed in target, [11C]CH4 production represents a key step for the [11C]CH3I synthesis from which the outcome of the whole radiolabelling process depends. In order to improve the performance of the module, a new reduction catalyst made of a mixture of metallic Ni (nanopowder) and molecular sieves mixed in different ratios has been tested. Preliminary results demonstrated that not only the mixture of nanopowder-Ni and molecular sieves represents a valid reduction catalyst but also permits to trap [11C]CO2 and subsequently use it as labelling reagent, making TRACERlab FX C a module for both methylation and carboxylation.