BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//pretalx.earthmonitor.org//soil-health-now-2026//SLGM9S BEGIN:VTIMEZONE TZID:Europe/Athens BEGIN:STANDARD DTSTART:20001029T040000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:EET TZOFFSETFROM:+0300 TZOFFSETTO:+0200 END:STANDARD BEGIN:DAYLIGHT DTSTART:20000326T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:EEST TZOFFSETFROM:+0200 TZOFFSETTO:+0300 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-soil-health-now-2026-X3K8B3@pretalx.earthmonitor.org DTSTART;TZID=Europe/Athens:20261207T170000 DTEND;TZID=Europe/Athens:20261207T180000 DESCRIPTION:The SoilWise Project\, a Horizon Europe Mission Soil project (2 023–2027)\, builds an open-access catalogue that harvests soil metadata from across Europe and makes it discoverable through a search interface (t he SoilWise Finder) and an AI chatbot (the Soil Companion)\, which will la ter be part of the European Soil Observatory (EUSO). Yet what surfaces in SoilWise\, and how well\, depends on the publishing choices data and knowl edge providers make. We illustrate how metadata records go through the Soi lWise pipeline\, so that data and knowledge providers understand how they can make their work FAIR (Findable\, Accessible\, Interoperable\, and Reus able). \nStarting from publication on Zenodo with a DOI and a grant-agreem ent number\, the record is picked up automatically by the SoilWise Harvest er via OpenAIRE. It is then harmonised from its source format into a commo n SoilWise data model and deduplicated against records from other aggregat ors such as the INSPIRE Geoportal and data.europa.eu. A validation step sc ores the record for completeness and INSPIRE compliance\, while an augment ation step enriches it with standardised SoilVoc concept identifiers\, nor malised resource types\, and geographic information extracted from text wh ere explicit spatial metadata is missing. The processed metadata record is stored across three parallel structures\, each supporting a different mod e of access: a relational database\, a semantic Knowledge Graph\, and a fu ll-text search index. Finally\, the record becomes discoverable both throu gh the SoilWise Finder's faceted search interface and through the Soil Com panion\, an AI assistant that uses retrieval-augmented generation to synth esise natural-language answers from across the catalogue.\nAt every stage\ , the concrete publishing decision that determines whether a metadata reco rd succeeds is highlighted: a DOI and grant reference for harvesting\, a r ecognised metadata standard for harmonisation\, complete core fields for v alidation\, and controlled-vocabulary keywords and geographic extent for a ugmentation and search. This work is aimed at Mission Soil data managers\, data stewards\, researchers\, and Living Lab participants\, with the prac tical message that understanding the pipeline is what enables soil data an d knowledge providers to make their work findable today and preserved in E USO at the JRC. DTSTAMP:20260825T180223Z LOCATION:Basement (Foyer) SUMMARY:SoilWise project: the journey of a FAIR metadata record from public ation to reusability - Radu Giurgiu\, Wannes De Man URL:https://pretalx.earthmonitor.org/soil-health-now-2026/talk/X3K8B3/ END:VEVENT BEGIN:VEVENT UID:pretalx-soil-health-now-2026-HSXWWG@pretalx.earthmonitor.org DTSTART;TZID=Europe/Athens:20261208T160000 DTEND;TZID=Europe/Athens:20261208T164500 DESCRIPTION:If you produce soil data or knowledge in a Mission Soil project \, will anyone find it after your website goes offline? The SoilWise Proje ct\, a Horizon Europe Mission Soil project (2023–2027)\, builds an open- access catalogue that harvests soil metadata from across Europe and makes it discoverable through a search interface (the SoilWise Finder) and an AI chatbot (the Soil Companion)\, which will later be part of the European S oil Observatory (EUSO). But what surfaces in SoilWise\, and how well\, is decided by the publishing choices data providers make. This hands-on sessi on shows providers exactly what\, how\, and why to publish so their output s are found and reused.\nWe use the journey of a single metadata record as our teaching device. Following a real soil dataset as our worked example\ , we walk through what happens at each stage of the SoilWise pipeline (har vesting\, harmonisation\, validation\, augmentation\, storage\, and discov ery) and\, at every stage\, show the concrete publishing decision that mak es it succeed: a DOI and grant-agreement number so the harvester picks the record up via OpenAIRE\; a community standard so it harmonises cleanly\; complete core fields so it passes validation\; and recognised-vocabulary k eywords and geographic extent so augmentation and search work in the provi der’s favour.\nParticipants then get hands-on with the SoilWise publishi ng tools: the Tabular Soil Data Annotation tool\, the SoilWise GeoPackage \, and the DOI Resolution Widget.\nThe session is aimed at data providers: Mission Soil project data managers and coordinators\, data stewards\, res earchers\, and Living Lab participants. Attendees leave with a clear publi shing checklist and a working understanding of how following the SoilWise guidelines makes their soil data findable in the catalogue and\, ultimatel y\, in the European Soil Observatory at the JRC\, the platform’s foresee n long-term home. Bring a laptop. DTSTAMP:20260825T180223Z LOCATION:Amphitheater I SUMMARY:Make your soil data or knowledge record findable: a hands-on SoilWi se publishing workshop - Radu Giurgiu\, Wannes De Man URL:https://pretalx.earthmonitor.org/soil-health-now-2026/talk/HSXWWG/ END:VEVENT BEGIN:VEVENT UID:pretalx-soil-health-now-2026-FLPJK7@pretalx.earthmonitor.org DTSTART;TZID=Europe/Athens:20261209T161500 DTEND;TZID=Europe/Athens:20261209T163000 DESCRIPTION:SoilWise is a Horizon Europe Mission Soil project (2023–2027) building an open-access catalogue that brings together soil-related datas ets\, publications\, software\, and knowledge currently scattered across h undreds of European repositories\, project websites\, and aggregators. Rat her than hosting data itself\, SoilWise indexes metadata about resources h eld elsewhere and links back to the original sources\, providing a single discovery layer that respects the autonomy of existing data providers.\nTh is talk presents the platform by following the journey of a single soil me tadata record from publication to use. Tracing one record through the syst em\, we show how it is harvested from major European aggregators such as O penAIRE and CORDIS\; harmonised from its original format into a single com mon model\; validated for completeness and INSPIRE compliance\; augmented with standardised vocabulary concepts\, multilingual labels\, and link che cks\; and stored across a relational database\, a knowledge graph\, and a search index. The journey ends at the two user-facing tools: the SoilWise Finder\, a search-and-browse catalogue\, and the Soil Companion\, a soil-d omain chatbot that grounds its natural-language answers in catalogue recor ds and links back to its sources.\nThis single narrative gives the audienc e a clear mental model of how heterogeneous\, fragmented soil metadata is made coherently searchable across Europe — and where the FAIR principles work well in practice and where systemic gaps remain. The talk also looks ahead: the SoilWise Catalogue is designed to feed directly into the Europ ean Soil Observatory (EUSO) at the Joint Research Centre\, which is forese en to host and operate the platform beyond the project's lifetime\, keepin g the discovery layer growing as part of the European soil-observation eco system.\nThe talk is aimed at a broad audience\, researchers\, policy make rs\, Mission Soil participants\, and JRC/EUSO stakeholders\, interested in how European soil knowledge can be brought together and kept findable. DTSTAMP:20260825T180223Z LOCATION:Amphitheater I SUMMARY:SoilWise - Advancing a fair data and knowledge infrastructure for h ealthier soils in Europe - Radu Giurgiu\, Wannes De Man URL:https://pretalx.earthmonitor.org/soil-health-now-2026/talk/FLPJK7/ END:VEVENT BEGIN:VEVENT UID:pretalx-soil-health-now-2026-YECZSZ@pretalx.earthmonitor.org DTSTART;TZID=Europe/Athens:20261207T170000 DTEND;TZID=Europe/Athens:20261207T180000 DESCRIPTION:This work presents a UAV-based hyperspectral imaging pipeline f or high-resolution Soil Organic Carbon (SOC) mapping at the field scale. T he system combines hyperspectral remote sensing\, ground-truth soil sampli ng\, and machine learning to generate detailed SOC distribution maps that can support precision agriculture and soil monitoring applications.\nThe p ipeline begins with data acquisition using a hyperspectral camera mounted on an unmanned aerial vehicle (UAV). In this study\, a real-time hyperspec tral imager based on a large Fabry-Pérot Interferometer (FPI) filter was used. Unlike conventional fixed-band hyperspectral systems\, the tunable F PI design developed by VTT allows the user to programmatically select the spectral bands and wavelength combinations most suitable for a specific ap plication\, enabling more flexible and efficient data acquisition. The sen sor operates in the 650–1200 nm wavelength range using an InGaAs detecto r with 1280 × 1024 pixel resolution and captures full 2D spatial informat ion for every spectral channel while minimizing acquisition delays. \nThe UAV captures hyperspectral imagery at sub-meter spatial resolution\, allow ing detailed observation of soil variability across agricultural fields. C ompared to conventional multispectral imagery\, hyperspectral data provide s significantly richer spectral information\, enabling the detection of su btle soil characteristics and absorption features related to organic carbo n content.\nTo create reference data for model development\, soil samples were collected from multiple locations within each field and analyzed in t he laboratory to determine SOC content. The laboratory measurements were t hen spatially linked with the hyperspectral imagery to form a training and testing dataset consisting of spectral signatures and corresponding SOC v alues. Image preprocessing included radiometric correction\, geometric ali gnment\, and bare-soil identification to reduce the influence of vegetatio n and non-soil materials on the spectral signal.\nThree machine learning a lgorithms were evaluated for SOC prediction\, including Convolutional Neur al Networks (CNN)\, Random Forest\, and Gradient Boosting (XGBoost) models . Model performance was assessed using 5-fold cross-validation with metric s such as Root Mean Squared Error (RMSE) and coefficient of determination (R²). Among the evaluated approaches\, XGBoost achieved the best predicti ve performance and was selected for final SOC map generation.\nThe trained model was subsequently applied to the full hyperspectral dataset to produ ce continuous high-resolution SOC maps for multiple agricultural fields. T he resulting maps reveal fine-scale spatial variability in soil carbon con tent that would be difficult to capture using traditional sampling approac hes alone. DTSTAMP:20260825T180223Z LOCATION:Basement (Foyer) SUMMARY:UAV-Based Hyperspectral SOC Mapping Using a Tunable Fabry-Pérot Im ager and Machine Learning - Wannes De Man\, Haris Ampas\, Tuna Coppens\, N ick Berkvens URL:https://pretalx.earthmonitor.org/soil-health-now-2026/talk/YECZSZ/ END:VEVENT END:VCALENDAR