Marco Corsi

HOW SATELLITES AND GEOSPATIAL TECHNOLOGIES CAN HELP AGENCIES INVOLVED IN LAND MONITORING _____________________________________________________________________ We have published a study in the international journal *Scientific Reports*, which represents another step forward in understanding new methodologies for assessing the impacts of climate change on habitats. In this study, conducted in a little-known and under-researched area of inland Basilicata, we used satellite data and geospatial technologies (remote sensing, GIS and PCA geostatistical analysis) to determine whether ongoing climate change is altering the behavior of certain natural habitats of ecological and conservation interest. What emerges (in a very concise and simplified manner), as also confirmed by studies in other areas, is that: - Some grasslands exhibit earlier phenological cycles and a shortened life cycle due to higher temperatures and reduced autumn precipitation. Even at high elevations, the grasslands dry out sooner; - Shrublands have shown a similar trend but have proven to be more stable than grasslands; - Beech forests (and, to some extent, the Laurenzana fir forest), on the other hand, show a lengthening of their growing season; in short, to put it simply, the leaves sprout earlier and fall later; - Among the exceptions are riparian forests and those - Exceptions include riparian forests and those dominated by thermophilic oak, where negative anomalies were associated with localized water stress, canopy desiccation, and human-induced disturbances. The study explores the reasons behind these findings through a critical analysis of the data, which is available in open access format at the link below for those interested. But can all this talk from researchers actually be useful to regional offices and park authorities? The answer is: ABSOLUTELY YES!!! All these methods of studying the territory, combined with field studies, can provide data and information to support decision-making and land-use planning. In some cases, regional governments and park authorities commission these studies from universities and research institutions, but, alas, in most cases it’s just a way to spend money (that would otherwise be lost). Furthermore, in many contexts, technical offices lack up-to-date knowledge and training and are therefore unaware of the potential of these technologies. https://lnkd.in/dT63Du8Q

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📢 #CallForPapers The Special Issue “Path Planning, Trajectory Tracking and Guidance for UAVs” (3rd Edition) collects the latest research results on path planning, trajectory tracking, and guidance for UAVs—topics that are fundamentally important for autonomous #UAV operations. 🗓️Manuscript submission deadline: 16 June 2026 🔗Learn more and explore already published papers here: https://lnkd.in/dE453_wE

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We’re proud to share a major milestone in our journey. We’re expanding into key international markets and RE-MONITOR Inc. in the United States marks a decisive step forward. New horizons, same mission: #protecting people and #infrastructure through advanced #technologies for #monitoring and #analysis. Together with RE-MONITOR, we’re amplifying the impact of our solutions in structural safety, early warning and asset resilience connecting research, innovation and field operations, from system design to data-driven decisions. NHAZCA and RE-MONITOR: two teams, one mission. 👀 https://lnkd.in/dq7iix6b Tony Simmonds https://lnkd.in/dVYBN2de

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At 𝐌𝐄𝐓𝐀𝐋𝐄𝐕𝐄𝐋𝐒, we believe 𝒔𝒆𝒎𝒂𝒏𝒕𝒊𝒄 𝒊𝒏𝒕𝒆𝒓𝒐𝒑𝒆𝒓𝒂𝒃𝒊𝒍𝒊𝒕𝒚 𝒊𝒔 𝒂𝒏 𝒆𝒎𝒆𝒓𝒈𝒊𝒏𝒈 𝒑𝒓𝒐𝒑𝒆𝒓𝒕𝒚 of a system—not a feature to be designed. 🌱 We believe this property can be 𝐦𝐞𝐚𝐬𝐮𝐫𝐞𝐝 and 𝐡𝐞𝐥𝐩𝐞𝐝 𝐢𝐧𝐭𝐨 𝐞𝐱𝐢𝐬𝐭𝐞𝐧𝐜𝐞 through consistent and coherent design choices across every data modelling task. We have the knowledge. We built the tools. And we proved it on Italy's schema.gov.it—the national repository of semantic assets. Using their MCP interface, we didn't just take a census. We measured the gravitational pull of every asset using two principles: 🧠 𝐃𝐞𝐬𝐢𝐠𝐧 𝐂𝐨𝐧𝐯𝐞𝐫𝐠𝐞𝐧𝐜𝐞: Is the community rallying around the same models? 📊 𝐀𝐝𝐨𝐩𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐯𝐞𝐫𝐠𝐞𝐧𝐜𝐞: Is that rallying backed by real published data? What we found is a living ecosystem with seven clear gravitational centers 🪐—ontologies that have accrued so much institutional mass (through consistent and coherent design choices) that they now naturally shape the orbit of new services. 𝐓𝐡𝐢𝐬 𝐜𝐡𝐚𝐧𝐠𝐞𝐬 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠. 🔄 The cool part? We embedded this insight into a novel tool: an AI knowledge engineer 🤖 that, when given a new digital service design project, can now say: "Based on how the ecosystem has converged, you should anchor your design in these semantic assets." 𝐓𝐡𝐚𝐭 𝐢𝐬 𝐭𝐡𝐞 𝐚𝐧𝐬𝐰𝐞𝐫 𝐭𝐨 𝐬𝐞𝐦𝐚𝐧𝐭𝐢𝐜 𝐢𝐧𝐭𝐞𝐫𝐨𝐩𝐞𝐫𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐜𝐨𝐧𝐯𝐞𝐫𝐠𝐞𝐧𝐜𝐞. 👇 See the full story in the PDF below. Discover how embedding semantic interoperability convergence can shape the future of your organization. Imagine a world where AI agents don't just model data—they negotiate semantics in real time, spot divergence the moment it appears, and automatically adjust course. Want to find the gravitational centers in your national or sectoral semantic asset repositories? G̲e̲t̲ i̲n̲ t̲o̲u̲c̲h̲—̲l̲e̲t̲'̲s̲ m̲a̲p̲ y̲o̲u̲r̲ s̲e̲m̲a̲n̲t̲i̲c̲ g̲r̲a̲v̲i̲t̲y̲.̲ ̲🚀̲✨̲ Claudia Cristina Pollina | Matteo Fortini | Giorgia Lodi | Rocco Affinito | Kirsi Mikkonen | Riitta Alkula | Rannar Park | Jorge Cabrita de Sousa | Kathleen Jennrich | Michal Bukowski | Marta Kotlarska | Geir Myrind | Georges Lobo | Henrikas Krukauskas | Stefan Hoppe | Clara Pezuela | Adele Johanson | Filip Hansen | Kjersti Steien | Mark Dietrich | Carlos Mateus | Peter Hopfgartner #InteroperableEurope #DigitalEurope #DigitalPublicSector #CrossBorderInteroperability #SemanticInteroperability #Convergence #GovTech #PublicSector #DigitalTransformation #EGovernment #DataStandardization #PublicData #GovernmentInteroperability #DigitalItaly #SmartGovernment #LinkedOpenData #OpenDataCatalog #RDF #SPARQL #Ontology #SemanticWeb #LLM #AgenticAI #genAI #AI #MCP

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The March 2026, Vol. 3 Issue 1 of ACM JATS is now live! This issue includes Part II of the Special Issue on Applications-Driven UAV Routing and Scheduling Algorithms for Autonomous Transportation Systems (Guest Editors: Francesco Betti Sorbelli, Punyasha Chatterjee, Christian Claudel, Federico Corò). This selection highlights emerging solutions addressing routing optimization, energy-aware planning, system resilience, and novel application domains. The following six articles exemplify the breadth of ongoing work in this fast-evolving field: 1. Raffaele Elia, Massimiliano Rak, and Domenico Pascarella. 2025. Automated Identification and Evaluation of Threat Scenarios for U-Space Solutions. ACM J. Auton. Transport. Syst. 3, 1, Article 2 (March 2026), 24 pages. https://lnkd.in/gb-pds9E 2. Talha Azfar, Kaicong Huang, and Ruimin Ke. 2025. Enhancing Disaster Resilience with UAV-Assisted Edge Computing: A Reinforcement Learning Approach to Managing Heterogeneous Edge Devices. ACM J. Auton. Transport. Syst. 3, 1, Article 3 (March 2026), 21 pages. https://lnkd.in/gkCYgcS9 3. Simon Kohaut, Nikolas Hohmann, Sebastian Brulin, Benedict Flade, Julian Eggert, Markus Olhofer, Jürgen Adamy, Devendra Singh Dhami, and Kristian Kersting. 2025. Hybrid Many-Objective Optimization in Probabilistic Mission Design for Compliant and Effective UAV Routing. ACM J. Auton. Transport. Syst. 3, 1, Article 4 (March 2026), 24 pages. https://lnkd.in/gFCj3wwV 4. Navya Dhawde, NILOTPAL CHAKRABORTY, and Mirza Ghalib Baig. 2025. Intelligent Drone Surveillance with Efficient Charging Mechanism Using Eternal Vertex Cover and p-Dispersion. ACM J. Auton. Transport. Syst. 3, 1, Article 5 (March 2026), 28 pages. https://lnkd.in/gphqUYjg 5. William Gray II, Abduallah Al Redwan Newaz, Milad Khaleghi, Hieu T. Nguyen, Leila Hashemi-Beni, Abolghasem Shahbazi, and Ali Karimoddini. 2025. Multi-UAV Tasking and Coordination for Monitoring and Coverage of Agricultural Farmland. ACM J. Auton. Transport. Syst. 3, 1, Article 6 (March 2026), 22 pages. https://lnkd.in/gH39w_DA 6. Christophe Cariou, Laure Moiroux-Arvis, Fatiha Bendali-Mailfert, Yuankang HU, and Jean Mailfert (Jean MAILFERT). 2025. Unmanned Aerial Vehicle Optimal Route Planning for Data Collection of Underground Communicating Sensor Nodes in Agriculture. ACM J. Auton. Transport. Syst. 3, 1, Article 7 (March 2026), 17 pages. https://lnkd.in/gxYERNFD All the papers can be accessed online: https://lnkd.in/guAAWC3W #ACM #JATS #Journal #Autonomous #Transportation #Systems #UAV #Drones #RoutePlanning #Data #Communication #Optimization #Sensor #EdgeComputing #Routing #Surveillance #Research #Publication

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🗺️ The Uncertainty Assessment by the Monte Carlo Analysis of NDVI Measurements Based on Multispectral UAV Imagery 🧑 Fatemeh Khalesi*, Imran Ahmed, Pasquale Daponte, Francesco Picariello, Luca De Vito and Ioan Tudosa 🏫 University of Sannio 🔎 This paper proposes a workflow to assess the uncertainty of the Normalized Difference Vegetation Index (NDVI), a critical index used in precision agriculture to determine plant health. From a metrological perspective, it is crucial to evaluate the quality of vegetation indices, which are usually obtained by processing multispectral images for measuring vegetation, soil, and environmental parameters. For this reason, it is important to assess how the NVDI measurement is affected by the camera characteristics, light environmental conditions, as well as atmospheric and seasonal/weather conditions. The proposed study investigates the impact of atmospheric conditions on solar irradiation and vegetation reflection captured by a multispectral UAV camera in the red and near-infrared bands and the variation of the nominal wavelengths of the camera in these bands. Specifically, the study examines the influence of atmospheric conditions in three scenarios: dry–clear, humid–hazy, and a combination of both. Furthermore, this investigation takes into account solar irradiance variability and the signal-to-noise ratio (SNR) of the camera. Through Monte Carlo simulations, a sensitivity analysis is carried out against each of the above-mentioned uncertainty sources and their combination. The obtained results demonstrate that the main contributors to the NVDI uncertainty are the atmospheric conditions, the nominal wavelength tolerance of the camera, and the variability of the NDVI values within the considered leaf conditions (dry and fresh). https://lnkd.in/gKSbTiEM

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