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In the context of the MOVING (MOuntain Valorisation through INterconnectedness and Green growth) project, we released an open-source software - the MOVING Story Map Building and Visualization Tool (SMBVT) - that allows users to create and visualise story maps within a collaborative environment and using a user-friendly Web interface. The tool uses Semantic Web technologies and the Narrative Ontology to represent the stories of the MOVING mountain Value Chains. The MOVING community access SMBVT through The MOVING story map Virtual Research Environment and creates the events of the story. For each event, the user can add: a title, a textual description, start and end dates, the geographic coordinates, a media object (i.e. a video or image), notes, and digital objects. The tool takes Wikidata as reference KB and assigns Wikidata Internationalized Resource Identifiers (IRIs) to the story components (i.e. the entities that take part in an event). All the knowledge collected by SMBVT is stored in a JSON Postgres DB. When a story is completed, the tool automatically creates the corresponding visualisation using StoryMapJS library and makes available a corresponding URL that can be freely shared. Finally, SMBVT saves the collected knowledge as a Web Ontology Language (OWL) graph and publishes it as a Linked Open Data.

Datasets accompanying the study "A Taxonomy of Tools and Approaches for FAIRification" on the tools and approaches emerging from stakeholders' experiences adopting the FAIR principles in practice.

Complex service robotics scenarios entail unpredictable task appearance both in space and time. This requires robots to continuously relocate and imposes a trade-off between motion costs and efficiency in task execution. In such scenarios, multi-robot systems and even swarms of robots can be exploited to service different areas in parallel. An efficient deployment needs to continuously determine the best allocation according to the actual service needs, while also taking relocation costs into account when such allocation must be modified. For large scale problems, centrally predicting optimal allocations and movement paths for each robot quickly becomes infeasible. Instead, decentralized solutions are needed that allow the robotic system to self-organize and adaptively respond to the task demands. In this paper, we propose a distributed and asynchronous approach to simultaneous task assignment and path planning for robot swarms, which combines a bio-inspired collective decision-making process for the allocation of robots to areas to be serviced, and a search-based path planning approach for the actual routing of robots towards tasks to be executed. Task allocation exploits a hierarchical representation of the workspace, supporting the robot deployment to the areas that mostly require service. We investigate four realistic environments of increasing complexity, where each task requires a robot to reach a location and work for a specific amount of time. The proposed approach improves over two different baseline algorithms in specific settings with statistical significance, while showing consistently good results overall. Moreover, the proposed solution is robust to limited communication and robot failures.

This repository includes two datasets used in Ranghetti et al. (2018) and Ranghetti & Boschetti (2022) to analyse the magnitude of a decreasing trend in the extent of submerged rice paddies during the rice-sowing period in the Italian rice district: methods used to generate these data from MODIS remote sensing imagery are described in these papers.

sen2r is an R library which helps to download and preprocess Sentinel-2 optical images. The purpose of the functions contained in the library is to provide the instruments required to easily perform (and eventually automate) all the steps necessary to build a complete Sentinel-2 processing chain, without the need of any manual intervention nor the needing to manually integrate any external tool. For further details, see the documentation at https://sen2r.ranghetti.info/.

sen2rts is an R library which helps to extract and manage time series from Sentinel-2 archives created with the package sen2r. For further details, see the documentation at https://sen2rts.ranghetti.info/

Sessione speciale IGARS 2021 "Hyperspectral Imaging for Sustainable Agriculture and Food Security"

Iniziativa social di Istituto #ISPConAIR effettuato il 25 febbraio 2021 sulla piattaforma Zoom. Attualmente riproducibile sul canale YouTube ISPC. From the Digitalisation to the Virtual Reconstruction and Sound Simulation of Ancient Musical Instruments: Methods, Results, Perspectives. How might using computational methods for processing the 3D models allow for a more accurate analysis of surfaces, volumes, internal structures, and density of materials of ancient instruments? How might these methods enable a non-invasive study of the instruments' measurements and morphology, overcoming the limitations posed by their fragility? These are the topics of the webinar "From the Digitalisation to the Virtual Reconstruction and Sound Simulation of Ancient Musical Instruments: Methods, Results, Perspectives" which will take place on Thursday, 25th February 2021 on Zoom. This webinar aims to discuss how digital technologies based on 3D modelling and sound simulation can expand our knowledge of ancient musical instruments. As it has emerged from the STESICHOROS project - which has been funded by the European Commission's Marie Sk?odowska-Curie Actions programme -, studies on 3D virtual reconstructions and sound simulations can help us in defining novel approaches and methodologies not only for the "active preservation" of musical instruments, but also in enriching our understanding of ancient music and musical cultural heritage. Although reconstructions cannot tell us unequivocally how ancient users and audiences perceived the sounds of these instruments, they offer the chance to break through the time barrier by reviving sound emissions. By combining optical metrology with computational analysis, some of the subjective observations on ancient instruments can be substituted by measurable parameters, opening up new perspectives for the study of sounds and the artisan production process of ancient instruments. Moreover, the webinar aims to explore the ancient sonic interactions and the spatial configuration of sanctuaries and theatres in their respective landscapes and environment in order to investigate the use of auralisation technology in the archaeological field, as well as experimental interpretative 3D reconstruction integrating acoustic models. These topics will be addressed through the contributions of scholars working in various fields, including: archaeology, archaeomusicology, information engineering, interactive museums, musical heritage, physics, and virtual heritage. The programme of the webinar here: https://drive.google.com/file/d/1Nmg9CUDX3cBnYwRjlmlGzBX3rp0COQsc/view?usp=sharing The event: https://www.eventbrite.it/e/ancient-musical-instruments-methods-results-perspectives-tickets-139650042035#

Spraying in agriculture represents a societal challenge due to its negative impact in human and animal health and in environment. Increasing spraying efficiency towards the objective of "right time, right amount, right place", involves reduction of losses and, consequently, amount of phytopharmaceuticals used, water usage, and human and animal exposure to pesticides, and the increase of the spraying system availability while reducing labour costs. Furthermore, adoption of new ecological spraying treatments to increase both yield and treatment efficiency is desirable. Agriculture in rough terrain is also challenging, due to the steepness of some terrain, lack of space to manoeuvre, difficulties of communications due to natural obstacles and harsh atmospheric conditions associated. To cope with these challenges a consortium with complementary precision farming actors was formed for SCORPION project, bringing together steep slope vineyards associations (CERVIM, INNOVI), robotics and agricultural machinery RTD institutions (INESC, EUT, and CNR-IMAMOTER, WUR), SMEs and large company (TEYME, KommTek Intelligente Lösungen, Deimos), and an institution devoted to innovation in the sector (IPN). SCORPION's solution will be a safe and autonomous precision spraying tool integrated into a modular unmanned tractor (robotics platform). It will focus on steep slope vineyards but with impact in other high-value permanent crops (olive groves and fruiticulture). SCORPION' will consider Global Navigation Satellite System (GNSS) receiver (considering Galileo triple frequency (E1, E5 and E6) including the full E5 AltBOC signal, Open Service - Navigation Message Authentication (OS-NMA) and High Accuracy Service (HAS)) fused with other sensors, to increase the solution reliability, accuracy and safeness, and to enable autonomous ultraviolet light treatments (to eliminate partial need of phytopharmaceuticals) and to allow high precision spraying in permanent crops. SCORPION will bring the TRL of the technologies involved from 5 to 7. This increment is driven by five main RTD topics: localization and navigation systems (considering GNSS); advanced sprayer tool with Variable Rate Technology (VRT); safety systems; compliance and interoperability; and modularity. SCORPION will contribute to build up its market segment aligned to the European Strategic Robotics Agenda and create new business opportunities, and reduce the fertiliser usage in agriculture and increase air quality. SCORPION brings to the market a cost effective modular robot for high precision spraying in permanent crops, integrating three main modules: an autonomous tractor (<50hp), high precision sprayer with novel UV light treatments, and advanced outdoor sensing system. These modules can be commercialized independently or in the form of SCORPION robot.

Ground-Truth and Sentinel2 imagery classification of Trees Outside Forest in an agroforestry landscape in Umbria, Italy. Location: Alfina plains, Castelgiorgio area, Umbria, Italy. Reference system: EPSG:32632 (WGS84, UTM zone 32 North) Extent: West 740609 -- East 750828, South 4726490 -- North 4737250 Dataset format: geopackage, a single file data.gpkg containing 9 vector layers (in alphabetical order): Areas -- Areas of interest, 2 polygons Classification -- Automated classification from Sentinel2 imagery, 11781 polygons Hedgerows1 -- Ground truth, hedgerows of Area1, 148 lines Hedgerows2 -- Ground truth, hedgerows of Area2, 135 lines Sentinel2 -- Sentinel2 scenes footprint, one polygon Trees1 -- Ground truth, isolated trees of Area1, 55 points Trees2 -- Ground truth, isolated trees of Area2, 64 points Woods1 -- Ground truth, small forest patches of Area1, 33 polygons Woods2 -- Ground truth, small forest patches of Area2, 37 polygons Accompanying map: map.qgz, Qgis 3.6 format. The geopackage dataset is supposed to be stored in the same directory of the map (relative path = ./) Dataset description and metadata: meta.pdf