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This Training Itinerary to Improve ICT Competences was developed as part of DigitArt Project, co-financed by Erasmus+ KA2 - Cooperation for Innovation and the Exchange of Good Practices - Partnerships for Creativity, coordinated by Contextos (Faro, Portugal), in partnership with Lascò Srl (Caserta, Italy), and FRONTEiRAS - Asociación Cultural (Huelva, Spain). This document is the third of a total of four publications (Intellectual Outputs) that result from this project: IO1 – State of the Art - Creativity and Creative Learning Environments IO2 – Participatory Video - Methodological Guide for the Implementation of Innovative Strategies that Promote the Participation of Youth IO3 – Training Itinerary to Improve ICT Competences IO4 – Methodological Guide for the Development of Collaborative Projects for Youth The fifth and final output of the project, IO5 – Collaborative Documentary, tells the story of the DigitArt project in a video format. This third volume, IO3 – Training Itinerary to Improve ICT Competences, aims to provide a set of activities that youth workers can implement with young people to achieve the following objectives: improve digital and communicative skills among young people, critical reading skills, multimedia creation, contents productions, and meaningful use of Information and Communication Technologies; promote responsible participation and active citizenship through communication and collaboration., This publication has received funding from the European Commission under the Grant Agreement number 2020-1-PT02-KA227-YOU-007642, Erasmus+ KA2 - Cooperation for Innovation and the Exchange of Good Practices - Partnerships for Creativity project "DigitArt".

Over the last 50 years, many approaches for extracting plant key parameters from remotely sensed data have been developed, especially in the last decade with the spread of unmanned aerial vehicles (UAVs) in agriculture. Multispectral sensors are very useful for the elaboration of common vegetation indices (VIs), however, the spectral accuracy and range may not be enough. In this scenario, hyperspectral (HS) technologies are gaining particular attention thanks to the highest spectral resolution, which allows deep characterization of vegetative/soil response. Literature presents few papers encompassing UAV-based HS applications in vineyard, a challenging conditions respect to other crops due to high presence of bare soil, grass cover, shadows and high heterogeneity canopy structure with different leaf inclination. The purpose of this paper is to present the first contribution combining traditional and multivariate HS data elaboration techniques, supported by strong ground truthing of vine ecophysiological, vegetative and productive variables. Firstly the research describes the UAV image acquisition and processing workflow to generate a 50 bands HS orthomosaic of a study vineyard. Subsequently, the spectral data extracted from 60 sample vines were elaborated both investigating the relationship between traditional narrowband VIs and grapevine traits. Then, multivariate calibration models were built using a double approach based on Partial Least Square (PLS) regression and interval-PLS (iPLS), to evaluate the correlation performance between the biophysical parameters and HS imagery using the whole spectral range and a selection of more relevant bands applying a variable selection algorithm, respectively. All techniques (VIs, PLS and iPLS) provided satisfactory correlation performances for the ecophysiological (R2= 0.65), productive (R2= 0.48), and qualitative (R2= 0.63) grape parameters. The novelty of this work is represented by the first assessment of a UAV HS dataset with the expression of the entire vine ecosystem, from the physiological and vegetative state to grapes production and quality, using narrowband VIs and multivariate PLS regressions. A correct non-destructive estimation of key parameters in vineyard, above all physiological parameters which must be measured in a short time as they are extremely influenced by the variability of environmental conditions during the day, represents a powerful tool to support the winegrower in vineyard management.