BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//2026.europe.foss4g.org// BEGIN:VTIMEZONE TZID:+03:00 BEGIN:STANDARD DTSTART:20000101T000000 RRULE:FREQ=YEARLY;BYMONTH=1 TZNAME:+03:00 TZOFFSETFROM:+0300 TZOFFSETTO:+0300 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:pretalx-fe2026-8eaa10a0-c143-5dcf-a2ed-00ee23eeda3f@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T090000 DTEND;TZID="+03:00":20260629T100000 DESCRIPTION:Welcome to FOSS4G Europe 2026! DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Opening Plenary — Marian Neagul URL:https://talks.osgeo.org/foss4g-europe-2026/talk/LAPHSL/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-bb370e40-1ee7-5376-af33-ab1479268cc3@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T100000 DTEND;TZID="+03:00":20260629T110000 DESCRIPTION:Introduction to the OSGeo Foundation. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:The Open Source for Geospatial Foundation keynote — Tom Kralidis\ , Angelos Tzotsos\, Jeroen Ticheler\, Codrina Ilie URL:https://talks.osgeo.org/foss4g-europe-2026/talk/GFFRS3/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-71e6eaac-1cc0-5fd2-ab11-2541d9a4f9bc@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T113000 DTEND;TZID="+03:00":20260629T120000 DESCRIPTION:We will give a status report on the GDAL software\, focusing on recent developments and achievements in the 3.12 and 3.13 GDAL versions r eleased during the last year.\nThe discussed topics will be as various as the scope of GDAL is\, covering among other things:\n- Enhancements in the "gdal" front-end command line interface:\n * raster functionality: as-f eatures\, blend\, compare\, neighbors\, nodata-to-alpha\, zonal-stats\, et c.\n * vector functionality: check-coverage\, check-geometry\, clean-cov erage\, index\, layer-algebra\, make-point\, partition\n * dataset manag ement\n * mixed raster/vector pipelines\n * nested pipelines\n- GeoPar quet\, JSON Features and Geometries (JSON-FG)\, Zarr support enhancements\ n- New VRT pixel functions\n- C/C++/Python API for raster band algebra\n- and more confidential topics\, like CADRG NITF product generation\, new E5 7 raster driver\, IHO S-102/S-104/S-111 driver enhancements etc. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:State of GDAL: what's new in 3.12 and 3.13? — Even Rouault URL:https://talks.osgeo.org/foss4g-europe-2026/talk/9AQJYA/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-792010fd-25ed-5422-bb85-f86ff62a7ce0@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T113000 DTEND;TZID="+03:00":20260629T120000 DESCRIPTION:A practical tour of GeoServer 3 covering upgrade steps\, new re quirements\, refreshed UI\, and updated module structure.\n\nLearn what’ s changed\, what remains familiar\, and how to transition from GeoServer 2 .x efficiently\, with a focus on real-world adoption and getting up to spe ed quickly.\n\nGeoServer 3 introduces a modernized foundation while mainta ining the familiar concepts and workflows that users rely on. This session offers a guided tour of the new release\, focusing on what has changed in practice and how to approach the transition from GeoServer 2.x.\n\nWe’l l walk through the upgrade process\, highlighting prerequisites such as up dated Java and servlet container requirements\, and what to expect when mi grating existing installations. The session will also showcase the refresh ed user interface\, discussing its evolution and the improvements it bring s in terms of usability and productivity.\n\nIn addition\, we’ll explore the updated module structure\, what is included in the core distribution\ , and how extensions are organized in GeoServer 3. Rather than covering ev ery detail\, the goal is to provide an overview of the new system and help users quickly get up to speed.\n\nJoin us for a practical overview of Geo Server 3\, designed to make adoption straightforward and predictable for b oth new and existing users. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:GeoServer 3 tour — Andrea Aime\, Jody Garnett URL:https://talks.osgeo.org/foss4g-europe-2026/talk/JDGFCR/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-49b182ad-1b1b-5900-8537-6239ca2f288c@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T113000 DTEND;TZID="+03:00":20260629T120000 DESCRIPTION:Efficient management of the integrated water cycle requires adv anced digital tools capable of centrally integrating\, analyzing\, and opt imizing hydraulic\, operational\, and territorial information. In this con text\, Giswater 4 represents a qualitative leap in the digitalization of w ater services\, incorporating substantial improvements in its architecture \, interoperability\, and analytical capabilities. This work presents the implementation and adaptation of Giswater 4 within the framework of the PE RTE project (Strategic Projects for Economic Recovery and Transformation) for the digitalization of the water cycle at Aigues de Manresa. Version 4 introduces a more robust and intuitive interface\, greater integration wit h other platforms through the development of a REST API\, and enhanced cap acity to work with hydraulic digital twins. Additionally\, it includes new functionalities aimed at advanced management of water supply and sanitati on networks\, such as traceability analysis\, scenario evaluation\, leak d etection\, and prioritization of infrastructure investments. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Giswater 4: Open Source Innovation in Water Network Planning — Da vid Cano URL:https://talks.osgeo.org/foss4g-europe-2026/talk/EVXR3K/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-c52502fc-7466-5d35-b2b4-0f601f7df924@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T113000 DTEND;TZID="+03:00":20260629T120000 DESCRIPTION:The European Space Agency (ESA) is these days developing a new unified Zarr-based file format for Sentinel (1\, 2\, and 3) mission produc ts under the Earth Observation Processing Framework (EOPF) initiative. EOP F Zarr enables scalable\, cloud-native access to Earth Observation data an d represents a significant shift in how EO products are distributed by ESA .\n\nThis talk introduces the EOPF Zarr format: its design\, current statu s\, and practical capabilities. We'll also cover the growing ecosystem of open-source tools being built around it\, from plugins for GDAL\, xarray\, QGIS\, R\, and Julia\, to interactive browser-based exploration of Sentin el imagery with no downloads or preprocessing required.\n\nWhether you're new to cloud-based EO workflows or want to learn about the new format\, th is session will give you a clear picture of where EOPF stands today and ho w to get started with it. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:The new format for all Sentinel products: EOPF Zarr — Felix Delat tre URL:https://talks.osgeo.org/foss4g-europe-2026/talk/UKQM9W/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-46d0331e-699e-5fa2-8a7c-5a996c527fc0@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T120000 DTEND;TZID="+03:00":20260629T123000 DESCRIPTION:This is a special moment in the evolution of QGIS. Version 4.0 was released earlier this spring and shortly version 4 will become the nex t long-term release. It’s been 7 years since we’ve had a new major ver sion of QGIS!\nThis talk will focus on what users can expect when they upg rade to QGIS 4.x. There were also quite a few notable features released wi th the last QGIS 3.x release – QGIS 3.44 Solothurn. This talk will inclu de features from 3.44 as they will be new to anyone migrating from the las t LTR (3.40 Bratislava).\n\nEach highlighted feature will not simply be de scribed but will be demonstrated with real data. If you want to learn abou t the latest features in QGIS\, this talk is for you!\n\nLikely topics inc lude GUI enhancements * Symbology * Annotations * Point cloud support * Da ta Providers * Processing * Model builder * 3D * Vector editing * Print c ompositions DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:QGIS Feature Frenzy - What's new in QGIS 4.0? — Kurt Menke URL:https://talks.osgeo.org/foss4g-europe-2026/talk/AFMBWP/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-81be677a-7d53-5edc-b3c4-6de7892114f3@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T120000 DTEND;TZID="+03:00":20260629T123000 DESCRIPTION:GeoServer 3 marks the completion of a long-planned modernizatio n effort aimed at keeping the project aligned with the current Java ecosys tem\, while preserving the stability and backwards compatibility that user s rely on. Now that GeoServer 3 has been available for a few months\, this session provides a final update on the work and its outcomes.\n\nWe’ll revisit the initial drivers behind the transition\, starting from the upgr ade of core dependencies\, how that cascaded to more updates\, resulting i n a coordinated effort across multiple projects. From there\, we’ll outl ine the main phases of the work: how the upgrade was organized\, funded\, managed new needs\, and ultimately delivered.\n\nThe talk focuses on the p rocess and its results: what it took to modernize a mature codebase while maintaining a high degree of compatibility\, the challenges encountered al ong the way\, and how they were addressed. We’ll also share early feedba ck from adoption and what users can expect when moving to GeoServer 3.\n\n Join us for a practical retrospective on the transition to GeoServer 3\, a nd a discussion of how the project continues to evolve while staying true to its core principles. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:GeoServer 3 complete - final update — Andrea Aime\, Jody Garnett URL:https://talks.osgeo.org/foss4g-europe-2026/talk/FSZ39Q/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-6a92bf21-f7ad-540d-ae37-bcfc6594293d@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T120000 DTEND;TZID="+03:00":20260629T123000 DESCRIPTION:This presentation introduces an integrated GIS–AHP framework for the spatial assessment of heavy metal (Cd\, Pb\, Ni) pollution risk in Serbian surface waters. Using data from 54 monitoring sites over 2019–2 023\, four complementary risk indices—Total Pollution Index (TPI)\, Bioa vailability Index (BI)\, Trend Index (IT)\, and Regulatory Risk Index (RRI )—were calculated and integrated via the Analytic Hierarchy Process (AHP ). The study identifies five high-risk locations influenced by mining\, in dustrial\, and urban pressures\, while 75.9% of sites remain in low-risk c ategories. Spatial statistics using Getis‑Ord Gi* reveal significant clu sters\, highlighting critical areas requiring targeted monitoring and mana gement. This approach demonstrates the utility of combining GIS and multi- criteria decision analysis for environmental risk assessment and can serve as a model for other regions and contaminants. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Spatial Risk Assessment of Surface Water Heavy Metal Pollution Usin g GIS–AHP in Serbia — Jelena Lukić URL:https://talks.osgeo.org/foss4g-europe-2026/talk/NJBTKW/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-610ac067-3e03-5d0f-b0e6-ddc28d66b1ba@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T120000 DTEND;TZID="+03:00":20260629T123000 DESCRIPTION:Building analysis-ready Earth observation products starts well before any algorithm runs. Source data need to be accessible\, complete\, up to date. That sounds obvious\, but doing it reliably across multiple sa tellite missions while backfilling years of historical archives is not an easy task.\n\nThis talk is about how we built that foundation. The startin g point is a simple Argo CronWorkflow that queries a STAC API and download s one day of data to S3. Nothing impressive\, but Argo already gives you t hings a cron job doesn't: built-in retries\, a web UI showing exactly whic h step failed\, and the full log. Your Python script doesn't change\, you' re just not the (only) one watching it anymore.\n\nThis talk follows what happened when we scaled this up across various satellite products. Each pr oblem we ran into pushed us to add something: fan-out parallelism when seq uential backfills were taking days\, STAC as a logbook of what had already been ingested and what is missing\, and eventually an observability layer when we needed to understand periods of higher error rate. \n\nThe combi nation of autonomous backfill and automated monitoring creates a system t hat self-corrects at two levels: individual failed items are retried via S TAC gap detection\, while systemic issues surface in daily reports for hum an intervention. \nAll the tools are open source: Argo Workflow s\, STAC API\, Python\, Kubernetes\, CI pipelines Attendees will leave wit h a concrete understanding of what Argo Workflows gives you at each stage of complexity\, from replacing a cron job to running a system you can trus t "unsupervised". DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:From Cron Job to Self-Healing Pipeline\, using Argo and STAC for EO Data Ingestion. — Loïc Houpert URL:https://talks.osgeo.org/foss4g-europe-2026/talk/JFCDW9/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-46c471be-7df8-5a99-99fa-3022499ff14f@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T123000 DTEND;TZID="+03:00":20260629T130000 DESCRIPTION:MapServer\, a founding OSGeo project\, is widely used for publi shing spatial data and interactive web mapping applications. This talk pro vides an overview of the new 8.6 release and a preview of the upcoming 8.8 release\, highlighting key enhancements and features. Integration with po werful new GDAL features\, such as pipelines and cloud-native drivers\, is demonstrated\, along with results from the first-ever MapServer User Surv ey.\n\nThis session is for both current MapServer users and anyone interes ted in exploring what MapServer can do. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:State of MapServer — Seth Girvin URL:https://talks.osgeo.org/foss4g-europe-2026/talk/HEVHTQ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-3b8b6e91-87c7-5a15-854b-67a1939bf7e3@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T123000 DTEND;TZID="+03:00":20260629T130000 DESCRIPTION:The OGC APIs are a fresh take at doing geo-spatial APIs\, based on WEB API concepts and modern formats\, including:\n\n- Small core with basic functionality\, extra functionality provided by extensions\n- OpenAP I/RESTful based\n- JSON first\, while still allowing to provide data in ot her formats\n- No mandate to publish schemas for data\n- Improved support for data tiles (e.g.\, vector tiles)\n- Specialized APIs in addition to ge neral ones (e.g.\, DAPA vs OGC API - Processes)\n- Full blown services\, b uilding blocks\, and ease of extensibility\n\nThis presentation will provi de an introduction to various OGC APIs and extensions\, such as Features\, Styles\, Maps and Tiles\, Processes\, STAC and CQL2 filtering. Some of sp ecs are finalized and complete enough that they have a GeoServer supported extensions\, while others are provided as community modules. Join us to f ind out the current state of implementation\, our future steps\, and how y ou can participate in it. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:OGC APIs with GeoServer 3: implementation\, avaialbility and next s teps — Andrea Aime URL:https://talks.osgeo.org/foss4g-europe-2026/talk/TDBVZY/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-7633b324-7760-5071-a3b8-993f7b70fb77@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T123000 DTEND;TZID="+03:00":20260629T130000 DESCRIPTION:Lounaistieto\, the regional geoinformation and open data networ k in Southwest Finland\, develops and maintains regional data services and supports municipalities\, public organisations and research partners in p roducing high quality\, interoperable datasets. Within this initiative\, L ounaistieto leads data enrichment\, municipal collaboration and the develo pment of sustainable practices for recreational data management.\n\nThe on going Digiretki project aims to improve the quality\, accessibility and in teroperability of recreational data in Southwest Finland. Its core objecti ves include integrating the regional recreational database with two nation al information services\, Luontoon.fi map service and the Lipas system\, a nd strengthening municipalities’ ability to produce and maintain accurat e\, up to date datasets. The work also supports nature tourism companies i n enhancing their digital visibility through Visit Finland’s DataHub dat abase.\n\nThe initiative advances open data availability and interoperabil ity by redesigning the regional Virma data model to align with national st andards and by implementing a technical transfer solution that allows enri ched Virma data\, including site descriptions\, images\, accessibility inf ormation and area based features\, to flow automatically into the Lipas sy stem. This ensures nationally compatible and openly accessible datasets an d strengthens the foundation for coherent outdoor recreation information a cross Finland. Municipal engagement\, data quality assessments and hands o n training further improve the region’s capacity for producing interoper able open data.\n\nThe project also connects directly to open source softw are development. The renewed Virma data model and associated documentation are openly published through Lounaistieto’s GitHub\, enabling other reg ions and organisations to adopt\, adapt and extend the technical solution. By following open source principles\, the initiative promotes transparenc y\, reusability and collaborative development and reinforces the broader m ission to build sustainable\, interoperable and openly available digital i nfrastructure for outdoor recreation\, municipal service provision and nat ure tourism innovation.\n\nIn the presentation\, we will introduce the pro ject’s outcomes and provide an overview of Lounaistieto’s work. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Towards open and interoperable recreational data infrastructure — Antti Vasanen URL:https://talks.osgeo.org/foss4g-europe-2026/talk/XQUK9R/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-0ee2ac6f-8e17-5bf3-9e25-e31dfa4ef299@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T123000 DTEND;TZID="+03:00":20260629T130000 DESCRIPTION:Over the past years\, mapchete has evolved from a tile-based ra ster and vector processing library into a modular ecosystem for building a nd operating large-scale geospatial data processing pipelines. Previous pr esentations at FOSS4G focused on the core package and touching scalable pr ocessing patterns using dask and mapchete.\n\nThis talk presents the next step: the open source publication of additional components developed in a production context\, including mapchete EO\, mapchete Hub\, and mapchete H ub CLI. These packages extend mapchete's core processing model towards Ear th Observation (EO) use cases and distributed execution\, with a focus on reproducibility\, scalability\, and a variety of (pre)processesing capabil ities relevant for EO.\n\nmapchete EO provides higher-level primitives for working with satellite imagery (primarily Sentinel-2)\, including typical preprocessing steps such as cloud masking\, BRDF correction\, and tempora l compositing. These components are derived from operational pipelines use d in the EOxCloudles (cloudless.eox.at) product line\, where consistent la rge-scale processing and data quality constraints are critical.\n\nmapchet e Hub introduces a service layer for orchestrating distributed processing of mapchete tasks. Processing jobs can be submitted\, scheduled\, and moni tored via an API. The API design is oriented towards the OGC API - Process es standard\, aligning mapchete-based workflows with emerging interoperabl e interfaces in the geospatial ecosystem. The accompanying CLI (mapchete h ub CLI) provides a minimal interface for interacting with this system with out requiring custom integration.\n\nIn addition to the software component s\, the talk covers recent changes in packaging and distribution. All pack ages are now published via both PyPI and Conda\, and container images are provided through GitHub Container Registry. All packages were moved to a d edicated mapchete organization. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:From Tile-Based Processing to Distributed Execution: Extending the mapchete stack — Joachim Ungar URL:https://talks.osgeo.org/foss4g-europe-2026/talk/PXCHPM/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-c2a6fc8d-f6a7-53da-a654-45986d78497c@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T143000 DTEND;TZID="+03:00":20260629T150000 DESCRIPTION:MapStore is an open source product developed for creating\, sav ing and sharing in a simple and intuitive way maps\, dashboards\, charts a nd geostories directly online in your browser. MapStore is cross-browser a nd mobile ready\, it allows users to: \n\nSearch and load geospatial conte nt served using widely used protocols (WMS\, WFS\, WMTS\, TMS\, CSW\, 3D T iles) and formats (GML\, Shapefile\, GeoJSON\, KML/KMZ etc..)\nManage maps (create\, modify\, share\, delete\, search)\, charts\, dashboard and stor ies directly online\nManage users\, groups and their permissions over the various resources MapStore can manage\nEdit data online via WFS-T with adv anced filtering capabilities\nDeeply customize the look&feel to follow str ict corporate guidelines\nManage different application contexts through an advanced wizard to have customized WebGIS MapStore viewers for different use cases (custom plugins set\, map and theme)\n\nYou can use MapStore as a product to deploy simple geoportals by using the standard functionalitie s it provides but you can also use MapStore as a framework to develop soph isticated WebGIS portals by reusing and extending its core building blocks .\n\nMapStore is built on top of React and Redux and its core does not exp licitly depend on any mapping engine but it can support both OpenLayers\, Leaflet and Cesium\; additional mapping engines could be also supported (f or example MapLibre GL) to avoid any tight dependency on a single engine.\ n\nThe presentation will give the audience an extensive overview of the Ma pStore functionalities for the creation of mapping portals\, covering bot h previous work (e.g. new features released during the last year) as well work for the future releases. Eventually\, a range of MapStore case studi es will be presented to demonstrate what our clients (like City of Genova\ , City of Florence\, Halliburton\, Austrocontrol and more) and partners ar e achieving with it. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:State of MapStore — Lorenzo Natali\, Tobia Di Pisa\, Stefano Bovio URL:https://talks.osgeo.org/foss4g-europe-2026/talk/QKFSSW/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-40123583-a597-5f89-ae22-2e1814c71e41@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T143000 DTEND;TZID="+03:00":20260629T150000 DESCRIPTION:You assumed you'd spend your time creating GIS layers\, but the computer said no.  Now you're spending your evenings reading logs.  The re's got to be a better way?\n \nWelcome to the story about how we rebuil t our 50 requests/s GeoServer setup\,  and what we learned along the way.   We'll take a look from an  IT/Operations point of view\, and describe how we automated GeoServer updates and built a cluster. What worked for u s and what did not? DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Lessons from running GeoServer in a mid-size production environmen t. — Hans Yperman\, Larissa Bonifacio URL:https://talks.osgeo.org/foss4g-europe-2026/talk/NSNJVB/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-dad1d3bd-1d9e-518e-aae5-ee64f1dcf409@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T143000 DTEND;TZID="+03:00":20260629T150000 DESCRIPTION:Open source and open geospatial data deliver clear technical be nefits\, yet their real impact is often difficult to communicate to public sector decision makers and governance stakeholders. Metrics familiar to t he FOSS4G community-adoption\, repositories\, contributors-rarely align wi th how impact is assessed in policy\, funding\, or institutional contexts. \nThis talk explores how open source impact can be framed in ways that res onate with public authorities and policymakers. Using examples from Europe an open geospatial initiatives\, it highlights how open source contributes to transparency\, resilience\, interoperability\, cost efficiency\, and l ong term public value-and how these outcomes can be communicated beyond te chnical audiences.\nThe session offers a practical framing approach to hel p practitioners translate open source principles into outcomes that suppor t informed decisions and sustainable public investment.\nAudience level: B eginner to intermediate\nKey takeaway: Open source impact is about outcome s and trust-not just technology. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Open Source\, Open Impacts: What “Impact” Means When Talking to Decision Makers — Octavian Borcan URL:https://talks.osgeo.org/foss4g-europe-2026/talk/RFHA7S/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-2e64caab-26e6-594f-b4d1-82cc04713b3a@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T143000 DTEND;TZID="+03:00":20260629T150000 DESCRIPTION:This talk looks at what it means to teach geoinformatics today\ , in a world where geospatial data\, tools\, and platforms are already wid ely available. As geoinformatics becomes part of many different discipline s and FOSS4G solutions make access easier than ever\, the real challenge i s no longer getting students to use the technology\, it’s helping them t hink spatially and critically.\n\nWe will reflect on how the explosion of Earth observation data\, open datasets\, and user-friendly tools has chang ed both the field and what we expect from graduates. While this accessibil ity is empowering\, it can also lead to shallow\, tool-driven learning if we don’t deliberately focus on concepts\, methods\, and reasoning.\n\nA key idea in the talk is the shift from teaching tools to teaching thinking . We will discuss why spatial thinking\, domain knowledge\, and the abilit y to critically evaluate data and results matter more than ever\, especial ly when automated workflows and ready-made solutions can hide important as sumptions and limitations.\nThe talk will also touch on how artificial int elligence is changing the classroom. As AI becomes part of everyday geospa tial workflows\, we need to rethink not only how we teach\, but also how w e assess students\, placing more value on interpretation\, transparency\, and critical engagement with machine-generated outputs.\n\nFinally\, I wil l share practical experiences from moving teaching from proprietary GIS so ftware to open-source environments. This includes both the benefits\, such as openness\, reproducibility\, and accessibility\, and the challenges of redesigning courses and supporting students with different backgrounds. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Teaching geoinformatics when tools are no longer the challenge — Evelyn Uuemaa URL:https://talks.osgeo.org/foss4g-europe-2026/talk/XGUURN/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-9fba06ff-7c8d-5917-ad49-ca4595032c75@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T143000 DTEND;TZID="+03:00":20260629T150000 DESCRIPTION:EOEPCA (Earth Observation Exploitation Platform Common Architec ture) is a European Space Agency (ESA) funded project led by Telespazio UK that defines a reusable exploitation platform architecture using open sta ndard interfaces. Its goal is to encourage interoperation and federation b etween operational exploitation platforms\, facilitating easier access and more efficient exploitation of the rapidly growing body of Earth Observat ion (EO) and other data. \n\nUsers are beginning to appreciate the advanta ges of exploitation platforms. However\, the market now offers a plethora of platforms with various added value services and data access capabilitie s. This ever-increasing offer is rather intimidating and confusing for mos t users. Users often face challenges such as inconsistent interfaces\, pro prietary software and limited interoperability. To fully exploit the poten tial of these complementary platform resources we anticipate the need to e ncourage interoperation amongst the platforms\, such that users of one pla tform may consume the services of another directly platform-to-platform.\n \nThe EOEPCA system architecture is designed to meet a set of defined use cases for various levels of user\, from expert application developers to d ata analysts and end users. The architecture is defined as a set of Buildi ng Blocks (BBs)\, exposing well-defined open-standard interfaces. These in clude Identity and Access Management\, Resource Discovery\, Data Access\, Processing Workflows\, Datacube Access\, Machine Learning Operations and m ore. Each of these BBs are containerised for Kubernetes deployment\, which provides an infrastructure-agnostic deployment target.\n\nThe recent stab le release of EOEPCA+ 2.0 delivers 11 production-ready building blocks\, e ach with deployment scripts\, documentation and interactive tutorials. Wor k is progressing towards version 2.1.\n\nAll EOEPCA+ source code is public on GitHub under open-source licences. We will outline how individuals and organisations can get involved\, and discuss how EOEPCA+ connects to the broader Open Science community and the future direction of the Common Arch itecture. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:EOEPCA+: Open Source Building Blocks for EO Exploitation Platforms: Architecture\, Community and the Road Ahead — Richard Conway\, James Hi nton URL:https://talks.osgeo.org/foss4g-europe-2026/talk/BW3SWP/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-15c1c189-8b5f-539c-8389-9d99969cd1c8@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T143000 DTEND;TZID="+03:00":20260629T150000 DESCRIPTION:The two papers by Cannata et al. (2023) and Collombin et al. (2 024) address a central paradox in open geospatial research: while geospati al web services (e.g. OGC-based services) foster data sharing in line with Open Science and FAIR principles\, they simultaneously challenge reproduc ibility. This core issue concerns particularly dynamic geospatial data. Un like static datasets stored in repositories with persistent identifiers (e .g. DOIs)\, data accessed through web services are continuously updated\, corrected\, or reprocessed. As a result\, the exact dataset used in a stud y may no longer be retrievable in its original state\, making it difficult or impossible to reproduce results. This issue is particularly critical f or time-varying datasets such as environmental monitoring\, sensor observa tions\, or cadastral data. Even when workflows and computational environme nts are reproducible\, reproducibility ultimately fails if the underlying data cannot be accessed in the same version used in the original analysis. Both works highlight that current geospatial infrastructures lack key mec hanisms such as data versioning\, persistent identification\, and temporal querying capabilities (“system-time”). Without these\, web services c annot guarantee access to historical data states. Addressing this limitati on requires moving beyond interoperability toward infrastructures that exp licitly manage data evolution over time\, enabling retrieval of past state s and supporting transparent and verifiable research. \n\nIn this context\ , istSOS4Things (https://github.com/istSOS/istSOS4) is introduced as a Sen sorThings API compliant solution that tackles these challenges by integrat ing mechanisms for temporal versioning\, traceability\, and controlled acc ess directly into the data service layer. Rather than acting as a simple i nterface to mutable data\, the system is designed as a version-aware and p olicy-enabled service\, capable of preserving and exposing the evolution o f geospatial data streams. A core element of this approach is the implemen tation of system-time versioning at the database level\, where each observ ation is associated with temporal attributes capturing both its validity a nd its transaction history. This enables reconstruction of the dataset as it existed at a specific point in time\, effectively introducing a “time -travel” capability. Users can therefore query not only the current stat e of the data\, but also past states\, addressing the reproducibility gap identified in the literature. \n\nFrom an architectural perspective\, istS OS4Things adopts a container-based\, microservice-oriented design\, where each component is deployed as an independent service and orchestrated thro ugh Docker. The core of the system is a PostgreSQL database extended with PostGIS. On top of the database\, the API layer is implemented using SQLAl chemy ORM with asyncpg as query engine and FastAPI for routing logic\, and served through Uvicorn as an ASGI server. To support performance and scal ability\, the architecture integrates Redis as an in-memory data store\, u sed for caching request to query conversion workload. This combination of FOSS ensures high performance\, asynchronous request handling\, and scalab ility of the SensorThings API endpoints. \n\nIn istSOS4Things\, the “tim e-travel” capability is exposed through an extension of the SensorThings API query model that introduces explicit temporal navigation parameters. In particular\, an as_of parameter allows retrieving the state of the data at a specific timestamp\, while a from_to parameter enables exploration o f how data evolved over a defined time interval. These parameters extend s tandard OData-based filtering mechanisms and bring system-versioned data c oncepts\, commonly found in temporal databases\, into web-based geospatial services. \n\nA key innovation is the introduction of a commit-based vers ioning model. Each modification to the dataset is recorded as a Commit ent ity\, representing a discrete change event that groups one or more operati ons. Each commit is associated with metadata such as timestamp\, descripti on\, and context\, and is linked to a User entity\, capturing the identity of the actor responsible for the change. This explicit association enable s tracking of who performed what modification and when\, introducing accou ntability and traceability into the data lifecycle. Observations are there fore not only versioned in time\, but also logically grouped into commits\ , forming a structured history of changes. This allows navigation across d ataset evolution both by timestamp (system-time) and by discrete change ev ents. In practice\, this enables reconstruction of the dataset at a given point or commit\, inspection of differences between versions\, and underst anding of the sequence of transformations applied to the data. The combina tion of temporal versioning and commit-based tracking provides a comprehen sive provenance model that goes beyond simple versioning. \n\nImportantly\ , the combination of service endpoint\, query definition\, and temporal re ference (e.g. via as_of) effectively defines a persistent and reproducible view of the dataset\, supporting reproducible data citation without requi ring static dataset snapshots. Building on this\, the system supports repr oducible data access through fully specified queries. By combining spatial \, temporal\, and thematic filters with temporal parameters\, users can re -execute the same query over a well-defined data state. This shifts reprod ucibility from static data publication toward reproducible data access pat terns\, where both the query and the temporal context define the dataset. \n\nAnother key aspect is the integration of fine-grained access control a nd policy enforcement mechanisms directly at the data layer. Access to dat a is regulated through a Role-Based Access Control (RBAC) model implemente d using PostgreSQL roles combined with Row-Level Security (RLS) policies. This enables permissions to be enforced not only at the table level\, but also at the level of individual records\, allowing selective visibility an d editing of observations based on the querying user (e.g. restricting upd ates to specific sensor networks). \n\nOverall\, this work promotes a shif t in how reproducibility is approached in geospatial research. Rather than relying on static data publication\, it embraces the dynamic nature of da ta and provides mechanisms to reconstruct past states\, document their evo lution\, and control access over time. By combining temporal versioning\, commit-based change tracking\, extended query capabilities\, provenance me tadata\, and policy-based access control\, istSOS4Things transforms geospa tial web services into reproducible\, auditable\, and governable data infr astructures\, directly addressing the limitations identified in prior rese arch. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:istSOS4Things: a reproducible\, auditable\, and governable sensor d ata infrastructures — Massimiliano Cannata URL:https://talks.osgeo.org/foss4g-europe-2026/talk/MTBKC7/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-fe9ffb7d-5056-5be7-83dc-bc5cf4404e2e@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T150000 DTEND;TZID="+03:00":20260629T153000 DESCRIPTION:The gap between desktop GIS and browser-based mapping is closin g fast. WebGIS solutions are increasingly taking on tasks that previously required dedicated desktop environments\, such as complex analytical proce ssing\, on-the-fly integration of massive datasets\, and workflow automati on. While proprietary systems have provided monolithic solutions for these tasks\, the open-source ecosystem is now catching up with more flexible\, modular approaches. \n\nHere\, we introduce [GOAT](https://github.com/pla n4better/goat)\, a refactored WebGIS platform built to bring analytical pr ocessing to the browser using modern open-source technologies. Traditional ly\, spatial analysis workflows are fragmented. Data is found on web porta ls\, downloaded\, processed locally\, and eventually pushed back to a visu alization tool. GOAT is designed to consolidate this cycle. Users can sear ch and load data via built-in catalogs\, direct uploads\, or OGC services\ , and apply styling directly in the browser. Beyond basic mapping\, the ap plication provides spatial modules for travel-time calculations\, geostati stics\, and general geoprocessing. To support reproducibility\, processing steps can be chained together in an automated workflow builder. This allo ws users to rerun complex analyses when new data arrives or parameters cha nge\, and includes support for custom SQL queries. These workflows can als o be mapped to UI inputs on the map\, allowing non-technical users to exec ute spatial pipelines by adjusting parameters.\n\nOnce the analysis is don e\, results need to be shared. GOAT includes a layout engine for designing and exporting high-resolution map series and PDFs. A dashboard builder le ts users combine maps with charts and metrics. Because the dashboards rema in linked to the underlying data\, they update automatically when the data changes\, turning static reports into interactive tools.\n\nUnder the hoo d\, the project is freely available under the GPL-3.0 license and managed as a monorepo. The frontend relies on React.js\, Next.js\, and MapLibre GL JS\, communicating over modern OGC protocols (Tiles\, Features\, Processe s). All endpoints are built in Python with FastAPI\, following both OGC st andards for spatial services and the OpenAPI specification. \n\nFor geopro cessing and data management\, the FastAPI backend leverages Python and Pos tgreSQL/PostGIS. One of our recent architectural shifts is the implementat ion of DuckLake\, a framework that combines the storage efficiency of Parq uet files with the analytical speed of DuckDB\, alongside PostgreSQL for m etadata. Due to scaling issues with PostgreSQL/PostGIS on large datasets a nd growing volumes of user data\, we adopted this hybrid approach. Parquet files allow us to store and query large spatial datasets efficiently\, wh ile DuckDB provides the processing speed needed for analytical workloads. This structure enables data to be stored in comparatively cheap volume sto rage and easily backed up in S3-compatible object storage. \n\nFor serving data\, we implemented a hybrid vector tile architecture. We rely on stati c vector tiles generated by Tippecanoe for maximum rendering speed\, while dynamic vector tiles are created on the fly using DuckDB for filtered or edited datasets. In practice\, this means we can render and interact with millions of building footprints or land-use parcels directly in the browse r through pre-generated tiles\, yet still maintain the flexibility to requ est dynamic tiles when users modify data or apply filters. \n\nTo prevent large analytical queries from slowing down the application\, we adopted an asynchronous architecture using Windmill to orchestrate Python jobs in th e background. Long-running geospatial tasks are defined in a core library powered by Python and DuckDB. Each tool is wrapped as a standard OGC Proce ss\, making it accessible from both the frontend and external APIs. This d esign ensures that processes run in isolation\, meaning individual tools c an be scaled independently based on their specific resource demands. As a result\, users can chain multiple processing steps into background workflo ws and continue interacting with the map uninterrupted. Finally\, the enti re platform is Dockerized and deployed via Kubernetes to ensure robust sca ling in production. \n\nWe have also built dedicated data pipelines to ing est base data\, such as street networks from OpenStreetMap\, spatial featu res from Overture Maps\, and public transit schedules via GTFS. Active mob ility is handled by custom algorithms\, while public transport routing is powered by the open-source Nigiri engine (from MOTIS). This combination al lows users to run complex\, large-scale spatial queries like spatial inter sections\, identifying gaps in public transit networks\, or evaluating nat ionwide accessibility.\n\nIn this talk\, we will share the technical chall enges we faced and the architectural decisions we made while building GOAT . Although GOAT has been primarily developed by Plan4better\, a core goal of this presentation is to encourage participation from the wider open-sou rce geospatial community. Alongside a live demo\, we will discuss practica l use cases in Germany. Finally\, we will touch on our latest technical ex periments\, such as integrating locally hosted open-weight LLMs to help us ers query spatial data via plain text\, and outline our roadmap for deeper integration with existing open-source GIS tools like QGIS. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Presenting the novel analytical WebGIS GOAT — Elias Pajares URL:https://talks.osgeo.org/foss4g-europe-2026/talk/FZELJW/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-4609e132-9c99-5664-b4f0-1ffc4ec1a1df@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T150000 DTEND;TZID="+03:00":20260629T153000 DESCRIPTION:The volume of data to be processed and published continues to g row rapidly\, particularly in domains such as maritime monitoring\, where continuous streams of AIS data must be ingested\, processed\, and visualiz ed. At the same time\, the infrastructure\, technologies\, and methodologi es required to manage these data streams are steadily advancing and maturi ng. GeoServer\, an open-source web service for publishing geospatial data\ , supports industry standards for vector\, raster\, and map delivery\, and is widely used by organizations to disseminate geospatial information at scale.\n\nIn this work\, we integrated GeoServer with established big data technologies\, including Apache Kafka and Databricks\, deploying the solu tion on Microsoft Azure. The resulting architecture is designed to support demanding maritime use cases\, enabling near real-time visualization of i ncoming AIS data while also supporting large-scale batch processing and an alysis of historical datasets.\n\nThis presentation describes the system a rchitecture and the key challenges addressed by GeoSolutions in publishing high-volume\, high-velocity data through GeoServer’s OGC services (WMS\ , WFS\, and WPS). Particular attention is given to achieving an effective balance between data ingestion throughput and visualization performance. T he solution integrates with a streaming processing platform responsible fo r ingesting\, transforming\, and storing data in an Azure Data Lake\, allo wing GeoServer to efficiently query the most recent features while enforci ng complex authorization policies. To meet these requirements\, several cu stom GeoServer extensions were developed\, addressing advanced authorizati on scenarios\, specialized styling needs for maritime data\, and seamless integration with big data platforms. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Operating Maritime AIS at Enterprise Scale with GeoServer — Andre a Aime\, Nuno Oliveira URL:https://talks.osgeo.org/foss4g-europe-2026/talk/L3YPNX/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-86ea6411-84fe-5181-990e-cff04915f70a@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T150000 DTEND;TZID="+03:00":20260629T153000 DESCRIPTION:Our climate is changing\, and not necessarily for the better. W e need to alter the landscape in our cities to cope with urban heat island s and flash floods and what not. This is up to the local governments\, but they often-times do not know where to start. And should they make a chang e to the landscape\, are they then on schedule\, or is it not good enough? \n\nBig data can help them at that. With GIS and remote sensing\, we can h elp urban policy makers make the right choices. And in most cases\, we can do this open source!\n\nBy saying open source I mean: open input data\, o pen resulting data\, open algorithms and open scripts.\n\nUsing landscape metrics like the 3+30+300-rule\, the EU Nature Restoration Law\, the Human Pressure Index: we can quantify in an open manor where the biggest issues are\, and if policy makers are on par.\n\nA true FOSS programme has been conducted in The Netherlands on this\, and we would like to share our insi ghts to other FOSS enthusiasts that would want to make their city a nicer place to live in. In our presentation we will go over the process\, the ap plicability to policy\, and the impact that has been made with FOSS in thi s field. Finally\, we would love to cooperate with other fellow European F OSS-enthusiasts to make their cities greener and more liveable. A picture says more than a thousand words! Let’s make that picture\, and convince your local mayor\, journalists and citizens! DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Making cities more liveable in a FOSS way: open data to the rescue! — Prof. Hans van der Kwast URL:https://talks.osgeo.org/foss4g-europe-2026/talk/8UL8BU/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-76063ab4-66fc-5ade-b939-ebec825c8a10@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T150000 DTEND;TZID="+03:00":20260629T153000 DESCRIPTION:The entry level for students to get started with “doing Geo ” never has been so low. Open-source software has been enabling young pr ofessionals on small budgets to gain hands-on experience – creating a vi brant\, young community of FOSS “aficionados” in and around university classrooms. Now\, we are seeing a second wave of development: genAI makes open-source tools even more accessible\, by tutoring students through the process of installation\, analytical workflows\, troubleshooting\, and ev entually code line commands. In this talk\, I will show some impressive ex amples of the level at which students can arrive with the help of generati ve AI and vibe coding with the GAMA modelling software for agent-based mod els.\nIn a deeper dive into this topic\, I further ask: which competences are left behind with vibe coding? And more fundamentally: if “doing Geo ” has become so simple\, what is the role of formal Geoinformatics educa tion? When “humans in the lead” turn to “humans in the loop” and b eneficiaries of “smart agentic systems”\, what will this do to the pro ductive work with FOSS GIS and decision making? How can we humans determin e the stages\, at which human validation is needed. And how can one valida te the outcomes\, who wasn’t capable of producing them? By relating to e xamples from the Spatial Simulation class\, I will finish off the talk wit h some lessons learned in terms of highlights and challenges when integrat ing (Geo)AI into courses and curricula\, and what this implies for future learning\, teaching and “doing” Geoinformatics in and beyond Higher Ed ucation. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Classroom vibes: AI-supported coding for "doing Geo" — Gudrun Wal lentin URL:https://talks.osgeo.org/foss4g-europe-2026/talk/8U7RAB/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-0238d408-caa2-5d01-98b6-6b9c759335d1@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T150000 DTEND;TZID="+03:00":20260629T153000 DESCRIPTION:As large repositories of EO data become increasingly available\ , the ability to search across these repositories and archives of data is paramount importance to address the geospatial data and metadata explosion .\n\nDistributed search requires standard for metadata encodings\, and beh aviour of how to delegate requests against remote catalogues. In addition \, metadata mappings and crosswalks are critical when attempting to harmon ize across metadata standards as part of real-time distributed search.\n\n This presentation will provide an overview of recent work in pycsw in the context of the ESA EOEPCA project\, as well as updates to the OGC API - Re cords standard to add formal specification of this behaviour. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Federated search using pycsw — Tom Kralidis\, Angelos Tzotsos URL:https://talks.osgeo.org/foss4g-europe-2026/talk/MPLR3B/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-964244dd-1d55-519e-9fda-7212f6a4e0c8@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T150000 DTEND;TZID="+03:00":20260629T153000 DESCRIPTION:Metadata are a foundational component of any data infrastructur e\, as they enable dataset discovery\, evaluation\, and reuse. Metadata cr eation and maintenance\, however\, is typically a costly\, inconsistent\, and largely manual process. In the European context\, this bottleneck is visible in major data sharing initiatives such as the INSPIRE Directive an d the Common European Data Spaces\, where high-quality\, interoperable met adata are a legal requirement as well as a precondition for data market pa rticipation.\nTwo main challenges affect the creation and maintenance of g eospatial metadata. The first is schema heterogeneity\, since existing sch emas (including ISO 19115\, DCAT\, GeoDCAT-AP\, Dublin Core\, INSPIRE prof iles) show partially overlapping semantics but incompatible serialisations . Migration between schemas is typically performed through hand-crafted tr ansformations encoding explicit field-to-field mappings: brittle\, schema- specific artefacts requiring specialist maintenance. The second challenge is content inconsistency: even within a single schema\, records produced b y different operators (including within the same organisation) may exhibit inconsistent terminology\, structure\, and level of detail in free-text f ields – which undermines catalogue-level discoverability.\nGenerative Artificial Intelligence (GenAI) and Large Language Models (LLMs) in partic ular offer promising capabilities to address these challenges. AI-assist ed metadata management (acquisition\, cleaning\, verification and maintena nce) has been already explored in literature [1]\, but to our knowledge no t in the case of geospatial datasets. Existing work includes for example A I support for digitizing libraries\, classifying research resources\, and create website content. Whatever the purpose\, research has focused on how to instruct LLMs to produce structured outputs for high-quality metadata [2] or to address the limitations of metadata schemas\, particularly free- text attributes whose definitions are often self-referential or provide in sufficient contextual meaning for GenAI to process [3].\nThis work extends such literature by proposing an open-source\, AI-powered geospatial metad ata editor. The core design principle is schema agnosticism: output schema s are defined as declarative configuration files\, and any new schema can be registered without modifying the application code. Field extraction and generation are driven by attribute type classification\, independently of field names or schema-specific logic\, with GeoDCAT-AP 3.0.0 as the curre nt default.\nThe tool recognises three different types of metadata attribu tes and tackles them differently. Type A attributes\, such as title\, keyw ords\, and description\, are characterised by a free-text nature and as su ch\, they are suitable for automatic generation using LLMs and prompts wit h contextual information. Type B are technical attributes such as spatial resolution\, bounding box\, file extension\, etc. that can be automaticall y extracted from the dataset by standard functions. Finally\, Type C are o rganisational attributes\, such as publisher\, contact point and licensing : these can be usually reused across several records within the same organ isation.\nInput handling is multimodal. For extraction of Type B attribute s\, the tool accepts native geospatial datasets processed via GDAL/OGR\, o r the URL to the OGC service serving the dataset. As a third option\, usef ul for large datasets\, the textual output of the gdalinfo or ogrinfo insp ection utilities can be provided directly. Type A attributes are generated using accompanying documentation on the relevant dataset\, such as techni cal reports and scientific publications\, which are indexed as corpus cont ent. The generation phase implements Retrieval-Augmented Generation (RAG): semantically oriented queries are issued against the vector corpus for ea ch free-text attribute\, results are ranked by relevance\, and a context p assage is assembled to inform generation. The LLM component is any OpenAI- compatible inference endpoint\, supporting both cloud-hosted and fully loc al deployments.\nThe tool supports three modes of operation through a unif ied processing pipeline\, with differences arising solely from the inputs provided. In the creation mode\, the user supplies a geospatial dataset a nd supporting documentation. Technical (Type B) attributes are populated d eterministically from the dataset\; publisher’s information (Type C attr ibutes) is parsed from the structured publisher document provided as input . Finally\, by querying the assembled corpus and including the Type B and C metadata attributes\, the LLM generates free-text fields (Type A) such a s title\, description\, keywords\, and provenance. A shared\, versioned pr ompt template encodes conventions – expected content sections\, field or der\, and level of specificity – applied consistently across all generat ed metadata records. This template functions as a content harmonisation in strument: metadata produced by different operators for different datasets converge on a common descriptive structure\, improving catalogue-level dis coverability without requiring ad-hoc normalisation. The use of a template and of different prompting techniques to reduce model hallucination and i mprove harmonisation across datasets has been investigated in an article c urrently under review [4].\nIn the schema migration mode\, the user addit ionally supplies an existing metadata record in any supported structured f ormat. The legacy record is parsed into field candidates and indexed in th e retrieval corpus. During generation\, the LLM receives the legacy metada ta as contextual input\; the mapping from source schema to target schema f ields emerges from the model semantic knowledge of both standards rather t han from explicit transformation rules\, generalising to schema pairs for which no hand-crafted converter exists.\nFinally\, in the enrichment mode\ , the user supplies a partial record or publisher documentation declaring organisational fields such as publisher\, license\, and contact point\; t hese are incorporated at the extraction time\, while remaining free-text f ields are generated and harmonised through the prompt template.\nIn all th ree modes\, the LLM is invoked only during the generation phase and only u pon explicit user action\, preserving a human-in-the-loop validation step before the export.\nSource code was submitted for intellectual property an d security screening for release under the open-source European Union Publ ic License (EUPL) according to the organisation policy. Schema definitions and prompt templates are expressed as human-readable declarative files\, versioned and customisable without modifying application code. \nThe empir ical evaluation in [4] is currently bounded by the institutional homogenei ty of JRC-produced metadata\; future research will address this limitation by incorporating records from Member State authorities engaged in the INS PIRE GeoDCAT-AP Pilot [5]\, enabling a more representative assessment of t he tool's harmonisation capacity across heterogeneous producer communities . DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:An Open-Source AI-Powered Geospatial Metadata Editor for Schema-Agn ostic Generation\, Migration\, and Content Harmonisation — Margherita Di Leo URL:https://talks.osgeo.org/foss4g-europe-2026/talk/SAADFE/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-89fe1629-551a-5c99-9721-b8fa029b2b0a@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T153000 DTEND;TZID="+03:00":20260629T160000 DESCRIPTION:GIS works really well for most geospatial workflows\, but when it comes to real-time or time-series data\, things are still not very smoo th. The OGC SensorThings API offers a way to access this kind of data thro ugh an open standard\, but bringing it into everyday GIS workflows is not always straightforward.\nIn this talk\, I’ll walk through a practical wo rkflow for working with SensorThings data\, from connecting to an API to e xploring and visualising time-series data directly in QGIS using the OGC S ensorThings plugin and the SensorThings Inspector.\nFrom there\, I’ll sh ow how the same data can be brought into a web environment using QWC\, and what needs to be considered when moving from desktop to web.\nThe focus i s on the workflow itself: what steps are needed\, what works well\, what s till feels a bit rough\, and how real-time data can fit more naturally int o open source GIS. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Exploring real-time geospatial data with SensorThings: from QGIS to QWC — Mariano Salas URL:https://talks.osgeo.org/foss4g-europe-2026/talk/ZLQF7J/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-99c2466f-245d-5b3d-b233-f5537de75e2d@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T153000 DTEND;TZID="+03:00":20260629T160000 DESCRIPTION:Building a production-grade WMTS for satellite imagery sounds s traightforward—until you hit cloud-native reality. This talk charts UP42 ’s journey from a 2024 hackathon to a live beta service\, exposing the h ard lessons learned while delivering STAC-catalogued imagery to profession al GIS tools at scale.\n\nThe Architecture Battle\nWhy GeoServer? While co mmercial options were cost-prohibitive and emerging tools like TiTiler lac ked maturity\, GeoServer offered OGC-compliance and a proven REST API. How ever\, "standard" setups quickly crumbled under B2B demands. We’ll dive into:\n\nThe FUSE Trap\nHow GCP Cloud Storage FUSE crippled tile-seeding p erformance\, and why we pivoted to native GCP BlobStore plugins to unlock massive throughput.\n\nThe Scaling Wall\nWhy vanilla GeoServer’s cluster ing failed us\, necessitating a strategic (and bumpy) migration to GeoServ er Cloud’s microservices architecture.\n\nThe Integration Tax\nReal-worl d troubleshooting of Helmfile fixes\, CSI driver misconfigurations\, and t he "silent" bugs that haunt cloud-native geospatial stacks.\n\nHard-Earned Takeaways\nWe’re sharing our internal RFCs and benchmarks so you don’ t have to learn the hard way. Learn why you must evaluate plugin maturity over hype\, why FUSE is a bottleneck for tile writes\, and why continuous load testing is the only way to survive the jump from "it works on my mach ine" to "it works for the world." DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Scaling the Sky: From Hackathon to Production on scale with GeoServ er Cloud — Matheus Pinheiro dos Santos\, Jeremiah Dominguez Gorrin URL:https://talks.osgeo.org/foss4g-europe-2026/talk/VLTRPL/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-0e25b4e5-9598-55a4-95cd-2ffbb60d9c53@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T153000 DTEND;TZID="+03:00":20260629T160000 DESCRIPTION:As part of its data production workflows\, the IGN (the French National Mapping Agency) has developped many QGIS plugins that can be of i nterest to the QGIS community and we have created QGIS Plugin to ease the access to services of the Geoplateforme \n\n* Géoservices : \n - The GPF Isochrone–Isodistance–Routing plugin brings Géoplateforme’s mob ility services into QGIS\, offering fast isochrone\, distance\, and routin g calculations. IGN supervised its development with Oslandia. \n - The French Locator Filter adds high‑quality French geocoding to QGIS using the Géoplateforme API. IGN funded the feature and coordinated the subcont racting with Oslandia. \n\n\n* Data production tools : A first plugin\, “Espace co\,” has recently become available\; its purpose is to allow users to populate specialized collaborative databases\, such as BDTopo (th e French national database). It is available here : https://plugins.qgis .org/plugins/ign_espace_collaboratif/ \n\n* Other plugins are currently un der development\, and we will strive to make them all available. A non-ex haustive list of what we plan to develop: \n - View plugin to have pr edefined styles based on data at your fingertips and to be able to share t hese styles among people working together. \n - Plugin for improved Z- axis management (visualization and correction) in QGIS \n - Plugin for managing lists of objects\, saving them\, and creating new ones… \n - Plugin for calculating the shortest path\, \n - Plugin for digitiza tion direction\, \n\nWe are offering this presentation to explain our appr oach: why we chose to develop QGIS plugins and why we chose to make them a vailable. We will present examples of use cases based on our own needs. \n\nThis presentation will allow us to gauge whether the QGIS community mi ght be interested in these developments\, potentially use them\, and perha ps even contribute to them. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Boosting QGIS: What France’s Mapping Agency Adds to the Toolbox — lavenant\, Rémi Ferrier URL:https://talks.osgeo.org/foss4g-europe-2026/talk/VLFQFH/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-f16fa532-5fb9-56ed-a354-51d0e95d651c@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T153000 DTEND;TZID="+03:00":20260629T160000 DESCRIPTION:Like WMS and WFS\, MapServer mapfiles are an essential componen t for publishing geospatial data via Open Geospatial Consortium (OGC) serv ices. However\, the standard workflow for managing these files can be a co nfusing experience\, where analysts often find themselves toggling between text editors and server environments. MapFile Preview is an evolving\, br owser-based development environment designed to simplify this process\, br inging the creation\, management\, and testing of MapServer configuration files into a single\, intuitive interface.\nIn this abstract\, we present the current progress of this tool\, which aims to transform MapServer admi nistration from a high-touch technical chore into a visual\, validated\, a nd efficient process. Currently a work in progress\, the application bridg es the gap between raw code and live services through several core\, modul es:\n• Integrated Workspace Management: The tool provides a centralized UI for navigating workspace directories. Analysts can open existing files via a system of aliases\, which replaces the need to manage long\, complex file paths during the preview process. The "Quick New" and guided form fe atures allow for the rapid generation of starter templates.\n• Real-Time Validation and Formatting: To avoid publishing an invalid Mapfile after s ubmission\, the application uses a local MapServer binary to perform insta nt syntax validation. This identifies errors or warnings before a file is ever published to a production environment. Furthermore\, an automated for matting engine "pretty-prints" the code\, enforcing consistent indentation that simplifies peer review and long-term maintenance.\n• Service Previ ewing: The platform comes with specialized modules for WMS and WFS service testing. GIS Analysts can visualize map layers\, legends\, and capabiliti es within the application. The WFS preview includes a layer picker\, enabl ing users to isolate specific data layers to verify that geometry and attr ibute tables are rendering as intended. Another tool\, “CGI Smoke Test\, ” helps determine whether an issue comes from network connectivity or fr om the mapfile configuration.\n• Auto Metadata and AI Assistance: Unders tanding the complexity of OGC standards and the potential for manual entry errors\, the "Auto Metadata" tool of the application generates metadata b locks for WMS\, WFS\, and WCS services automatically. To further support t he user\, the "Mapfile Teacher" tool integrates the Gemini AI model with a conversational interface for technical guidance. This AI model uses the o fficial MapServer documentation\, so the tool can offer a context-specific LLM for troubleshooting complex logic or learning new syntax.\nAs an ongo ing development project\, MapFile Preview can be a tool for a more accessi ble GIS administration. By combining mapfile editing\, validation\, and pr eview within a single environment\, Mapfile Preview reduces time spent ide ntifying syntax errors and supports the faster and finer publication of sp atial data services. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:MapFile Preview: A Browser-Based Tool for Editing and Testing MapSe rver Mapfiles — Stathis Petridis\, Dimosthenis Paradeisis\, Andreas Gkar avelis URL:https://talks.osgeo.org/foss4g-europe-2026/talk/7LNC9E/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-f85f57fb-46b5-56ab-b8bf-04f6d8602763@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T153000 DTEND;TZID="+03:00":20260629T160000 DESCRIPTION:ROCS is building Romania’s Earth Observation infrastructure u sing FOSS4G tools like STAC\, COG\, Zarr\, ~~MinIO~~ SeaweedFS and Kuberne tes but also leveraging components from ESAs EOEPCA+ stack. The platform e nables scalable\, cloud-native data access\, processing and analytics. Rea l-world use cases include crop monitoring\, forest compliance\, EO educati on\, all developed in an open and reusable manner.\n\nThe ROCS project rep resents a national effort to build a scalable\, cloud-native infrastructur e for EO data management and analysis in Romania\, fully based on FOSS4G t ools. The presentation will cover the project’s architectural design\, t echnical stack (including STAC\, COG\, Zarr\, OGC APIs and Kubernetes) and implementation of federated data centers that ensure efficient\, distribu ted EO processing.\nA key focus is on real-world applications\, including automated crop monitoring\, forestry compliance (e.g.\, EUDR)\, and the in tegration of EO tools in education. ROCS is committed to open development\ , reproducibility and interoperability\, aiming to contribute back to the FOSS4G community. The session will be valuable for developers\, platform b uilders and public sector stakeholders interested in building sustainable\ , cloud-ready EO platforms with open-source technologies.\n\nThe talk will also reflect on practical challenges encountered\, including the growing concern over license volatility in widely used open-source projects and ho w this affects long-term sustainability. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:ROCS: Extending Romania’s National Infrastructure within the Euro pean Collaborative Ground Segment with FOSS4G Solutions — Marian Neagul URL:https://talks.osgeo.org/foss4g-europe-2026/talk/EWDVAY/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-a9dd5ce3-98c7-5db5-931e-b8470799b6c8@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T153000 DTEND;TZID="+03:00":20260629T153500 DESCRIPTION:The reproducibility and transparency of scientific research are fundamental prerequisites for building trust in knowledge production and for addressing global challenges such as those outlined in the United Nati ons Sustainable Development Goals (SDGs). However\, many scientific public ations still lack the necessary information to reproduce results\, particu larly with regard to underlying software\, data\, and computational workfl ows. This situation\, commonly referred to as the replication crisis\, und ermines the reliability and sustainability of scientific practice (Baker\, 2016).\n\nTo address these challenges\, the paradigms of Open Science and FAIR (Findable\, Accessible\, Interoperable\, Reusable) have emerged as g uiding frameworks. Open Science promotes transparency through open access publications\, open data\, and open source software\, while the FAIR princ iples define minimum standards for the structured availability and reuse o f research outputs. A critical but often underrepresented component in thi s ecosystem is the proper citation and recognition of research software\, including free and open source geospatial (FOSS4G) tools (Smith et al.\, 2 016).\n\nThe Open Source Geospatial Foundation (OSGeo) represents a mature ecosystem of approximately 50 open source geospatial software projects\, supported by a global community. All OSGeo projects undergo a formal incub ation process\, ensuring adherence to best practices such as open licensin g\, publicly accessible repositories\, and transparent governance. These p ractices inherently support several FAIR principles\, particularly Findabi lity and Accessibility (Tzotsos et al.\, 2016). However\, gaps remain in l ong-term preservation\, persistent identification\, and formal recognition through standardized citation mechanisms.\n\nSoftware is commonly referen ced using URLs pointing to code repositories. While suitable for short-ter m access\, URLs lack long-term reliability\, as they may become invalid du e to infrastructure changes or resource removal. This creates challenges f or reproducibility\, as references in scientific publications may no longe r resolve to the original artifacts (Fenner et al.\, 2019).\n\nPersistent Identifiers (PIDs)\, particularly Digital Object Identifiers (DOIs)\, prov ide a robust solution. DOIs enable stable referencing of digital objects i ndependent of their location\, supported by infrastructures such as CrossR ef and DataCite. Platforms such as Zenodo\, operated by CERN and supported by the European Union\, facilitate DOI assignment for software and datase ts\, enabling long-term archiving and citation. The importance of software citation has been formalized by initiatives such as FORCE11\, which defin ed community principles for software citation (Smith et al.\, 2016)\, and the Research Data Alliance\, which promotes global standards for data and software interoperability.\n\nAn increasing number of OSGeo projects have adopted DOI-based citation practices. Currently\, more than 20 projects pr ovide DOIs\, allowing both version-specific citation and project-level ref erencing. This development aligns with broader trends in geospatial resear ch\, where open source GIS has become a central component of scientific wo rkflows (Brovelli et al.\, 2020). However\, implementation depth and autom ation vary across projects\, and the scientific publishing ecosystem has n ot yet fully adapted to consistently support DOI-based software citation.\ n\nA key challenge lies in the heterogeneity of publisher workflows. While some journals encourage or require DOI-based software citation\, the inte gration of these references into metadata systems such as CrossRef is not always reliable. As a result\, even correctly implemented FAIR practices m ay fail to produce visible and citable references. This lack of transparen cy creates uncertainty for researchers\, developers\, and reviewers and ma y lead to what can be described as an “information catastrophe\,” wher e contributions remain effectively invisible within the scientific record (Fenner et al.\, 2019).\n\nThe FAIR4G project (www.fair4g.org) addresses t his challenge by introducing a transparent\, data-driven approach to monit oring and documenting FAIR software citation practices in the open geospat ial domain. Launched in 2025 as a volunteer-driven initiative\, FAIR4G pro vides continuously updated analyses of DOI-based citations for OSGeo proje cts\, based on CrossRef metadata from scientific journals and books.\n\nTh e FAIR4G web portal serves as a centralized\, low-barrier information reso urce for stakeholders across the Open Science ecosystem. For each particip ating software project\, it offers tabular overviews of DOI-based citation s\, including publication date\, publication type\, publisher\, journal ti tle\, and the DOI of the citing work. Additional contextual information\, such as links to project websites and Zenodo landing pages\, enhances tran sparency and usability.\n\nThese data provide significant added value for multiple stakeholder groups. OSGeo projects can track the scientific reuse of their software across disciplines and optimize citation guidelines. In dividual contributors gain visibility into how their work is reused in sci entific and societal contexts. Researchers can identify journals that succ essfully implement FAIR software citation practices\, enabling more inform ed publication strategies. Publishers and journals can use FAIR4G data to benchmark and improve their workflows\, supporting their transition toward s Open and FAIR practices.\n\nThe Geospatial Data Abstraction Library (GDA L) illustrates these dynamics. Since registering a DOI in 2022 and archivi ng releases via Zenodo\, GDAL has seen increasing adoption in both downloa ds and DOI-based citations. FAIR4G analyses show a steady growth in citati ons across a wide range of scientific disciplines\, highlighting the centr al role of open geospatial software in contemporary research.\n\nFAIR4G is an evolving project that aims to expand its analytical capabilities and d ata services. Planned developments include temporal and thematic analyses of DOI adoption across publishers and journals\, as well as the provision of FAIR-compliant\, machine-readable datasets. These efforts are intended to foster dialogue among stakeholders and support the continuous improveme nt of standards and infrastructures for software citation.\n\nIn conclusio n\, FAIR4G addresses a critical gap at the intersection of Open Science\, FAIR principles\, and open geospatial software. By increasing transparency and providing actionable insights into DOI-based software citation practi ces\, it supports reproducibility\, recognition\, and sustainability in sc ientific research. As such\, FAIR4G contributes both a practical tool and a conceptual framework for strengthening the role of FOSS4G within a more open and sustainable scientific ecosystem. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:FAIR4G: Advancing FAIR Software Citation and Transparency for Open Geospatial Science — Peter Löwe URL:https://talks.osgeo.org/foss4g-europe-2026/talk/E9HEQB/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-59ba4802-1bb5-5a29-af0d-10e2ae6ef2d0@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T153500 DTEND;TZID="+03:00":20260629T154000 DESCRIPTION:Urban Heat Islands (UHI) have emerged as a critical environment al and socio-spatial challenge in rapidly urbanizing regions worldwide. Th e phenomenon is primarily driven by land-use transformations\, increasing building density\, and the progressive reduction of vegetation cover\, all of which contribute to elevated land surface and air temperatures in urba n areas compared to their rural surroundings. The UHI effect has far-reach ing implications\, significantly affecting public health\, increasing ener gy consumption for cooling\, and reducing overall urban livability. In rec ent years\, it has also been increasingly recognized as an issue linked to fundamental human rights\, including the right to health\, adequate housi ng\, and a sustainable and safe environment. Urban populations are particu larly vulnerable to climate change impacts such as extreme heat events due to high population densities\, sealed surfaces\, and limited access to gr een spaces. Consequently\, international policy frameworks emphasize the u rgent need for climate-resilient urban planning and the adoption of nature -based solutions to mitigate these risks.\n\nThe city of Tirana represents a compelling case for investigating the dynamics of the Urban Heat Island effect. Over the past three decades\, Tirana has undergone rapid and ofte n unregulated urban expansion\, characterized by intensive construction ac tivity\, densification\, and significant land-cover changes. These process es have substantially altered the urban morphology and have intensified th e UHI effect\, particularly in densely built central areas. While recent s tudies have documented temperature variations across the city and identifi ed key drivers such as reduced vegetation\, increased impervious surfaces\ , and urban density\, there remains a lack of systematic\, spatially expli cit\, and reproducible analyses. Furthermore\, limited attention has been paid to linking these environmental patterns with urban planning policies and the existing legal framework\, creating a gap between technical assess ments and policy-oriented applications.\n\nWithin the Albanian legal conte xt\, the Urban Heat Island phenomenon is not explicitly defined as a stand alone concept. However\, it is indirectly addressed through a set of inter related legal instruments\, including legislation on territorial planning and development\, environmental protection\, climate change mitigation and adaptation\, energy efficiency\, and the energy performance of buildings. These laws collectively promote principles of sustainable development\, e ncourage the integration of green infrastructure\, and support measures ai med at enhancing climate resilience. At the local level\, the Tirana Gener al Local Plan (TR030) incorporates provisions related to ecological corrid ors\, natural systems\, and the expansion of public green spaces. Although these instruments do not directly target UHI\, they establish an institut ional and regulatory framework that contributes to mitigating urban heat\, highlighting an implicit obligation for public authorities to address the phenomenon more explicitly in future planning processes.\n\nThis study ai ms to investigate the spatial and temporal dynamics of the Urban Heat Isla nd effect in Tirana over a ten-year period. The research adopts a fully op en and reproducible approach by relying exclusively on Free and Open-Sourc e Software (FOSS) and openly available Earth Observation data. The primary objectives are to identify UHI hotspots\, analyze their relationship with vegetation cover and built-up expansion\, and evaluate how these spatial patterns correspond to existing planning and legal instruments. By doing s o\, the study seeks to bridge the gap between geospatial analysis and poli cy-making\, offering insights that can inform evidence-based urban plannin g.\n\nThe methodological framework is based on satellite imagery obtained from Landsat 8 and Landsat 9 missions. Land Surface Temperature (LST) is d erived using established radiometric calibration and atmospheric correctio n techniques to ensure accuracy and comparability over time. Vegetation dy namics are assessed through the Normalized Difference Vegetation Index (ND VI)\, which is further used to calculate the Proportion of Vegetation (PV) \, providing a more detailed understanding of vegetative cover distributio n. Urban expansion and built-up intensity are analyzed using the Normalize d Difference Built-up Index (NDBI)\, enabling the identification of areas experiencing significant urban growth.\n\nAll data processing\, analysis\, and visualization are conducted using open-source tools\, primarily QGIS\ , alongside Python-based libraries such as GDAL\, rasterio\, and NumPy. Th is approach ensures that the entire workflow is transparent\, reproducible \, and accessible\, aligning with the principles of open science and the F OSS community. Moreover\, it demonstrates that advanced geospatial analysi s can be conducted without reliance on proprietary software\, making it pa rticularly relevant for researchers and institutions with limited resource s.\n\nPreliminary findings reveal a strong spatial correlation between ele vated Land Surface Temperatures and densely built areas with limited veget ation cover\, particularly in the central zones of Tirana. In contrast\, a reas characterized by higher NDVI values\, including parks\, green corrido rs\, and peri-urban zones\, consistently exhibit lower temperatures\, conf irming the cooling effect of vegetation and green infrastructure. Addition ally\, areas undergoing rapid urban development show a noticeable increase in thermal intensity over time\, suggesting that current planning measure s may be insufficient to counterbalance the thermal impacts of urbanizatio n.\n\nThe study contributes to the broader geospatial and FOSS community b y presenting a comprehensive\, open\, and transferable methodology for ana lyzing Urban Heat Islands in medium-sized cities. It highlights the value of integrating geospatial technologies with legal and planning analysis\, thereby bridging the divide between technical research and policy implemen tation. The findings support the need for more proactive and climate-sensi tive urban planning strategies\, including the expansion of green spaces\, the use of permeable and reflective materials\, and stricter regulation o f building density and land use.\n\nUltimately\, this research underscores the critical role of open-source tools in advancing sustainable\, climate -resilient\, and human-centered urban development. By providing a robust e vidence base and a reproducible analytical framework\, it aims to support decision-makers\, planners\, and researchers in addressing the growing cha llenges posed by the Urban Heat Island effect in Tirana and beyond. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Urban Heat Island Dynamics in Tirana: A FOSS-Based Analysis within the Urban Planning and Legal Framework — Leonora Haxhiu URL:https://talks.osgeo.org/foss4g-europe-2026/talk/YPABRR/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-da5ccfc7-5932-5f2a-a1e5-27811b90ba39@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T154000 DTEND;TZID="+03:00":20260629T154500 DESCRIPTION:*Introduction*\nEuropean landscapes have experienced drastic an d accelerating changes in recent decades\, particularly since World War II . Understanding landscape change from a historical perspective is essentia l in assessing the impact of previous land management choices on current-d ay landscapes\, habitats and biodiversity. While conservation policies typ ically consider current situations\, the lack of historical context might lead to shifting baselines to fit a deteriorating trend. \nThe Habitat Map of Switzerland is a high-resolution thematic product mapping the differen t Swiss habitats [1]. The classification is based on TypoCH\, a Swiss-spec ific hierarchical habitat typology\, which can be translated into the pan- European EUNIS classification system. TypoCH contains land cover classes o n the first level and becomes increasingly more detailed\, with plant comm unities and species on the lower levels [2]. Recently declassified Swiss-w ide imagery from 1946 with 1m spatial resolution\, in conjunction with reg ularly updated aerial imagery since the 1980s\, offers an unprecedented op portunity to map landscape and habitat change in the past century. In the perspective of multi-temporal classification\, a proof-of-concept study wa s performed on selected study areas in Switzerland\, using grayscale 1946 aerial imagery\, and object-oriented analysis and classification [3]. \nTh e gap bridged by this project is creating consistent multi-temporal mappin g for Switzerland\, with potential to apply the methodology in other count ries with similar historical data. The inherent inconsistencies in histori cal aerial image quality\, the limited spectral information (grayscale) an d habitat heterogeneity and complexity are the most challenging. Consisten t mapping is important for robust change detection and comparison between time steps. Therefore\, a flexible habitat typology and scalable method sh ould be determined.\nThis study aims to map habitat status and explore hab itat change in Switzerland over 5 times steps (1946 – present) using dee p learning image segmentation methods. Given the varying quality and spect ral resolution of imagery over time\, the first aim of this project is to determine which habitats can be consistently mapped from 1946 to the prese nt. This will be done in a data-driven approach\, developing a hierarchica l\, modular and flexible open-source deep learning methodology to check ha bitat mapping feasibility. The further aims are to develop a method to con sistently classify habitats across this time-series\, detect landscape cha nge\, and relate results to the current biodiversity status. \n\n*Methodol ogy*\nTo determine which habitats can be mapped from grayscale imagery\, a data-driven approach will be used\, starting from current-day aerial imag ery and Habitat Map of Switzerland\, integrated into a preliminary archite cture based on a hierarchical U-Net structure. The current-day aerial imag ery will be degraded to simulate historical aerial imagery\, using state-o f-the-art algorithms to add noise\, scratches\, distortions and blurring [ 4]. The Habitat Map of Switzerland will be used as training\, validation a nd test data. \nThe first level of the U-Net architecture will segment the first level of the habitat typology\, which mainly corresponds to land-co ver classes. The current Habitat Map of Switzerland includes habitats up t o the third level of the TypoCH typology. The U-Net will be trained to fir st separate the TypoCH classes\, which correspond to the first level of th e TypoCH typology. For each class\, a new U-Net will be trained to separat e the groups within the class\, which correspond to the second level of th e TypoCH typology. Then\, for each group\, new U-Nets will be trained to s eparate types within each group\, which correspond to the third level of t he TypoCH typology.\nThis approach will inform about habitats which are mo re difficult to map\, as well as habitats which might be easily confused w ith other habitats. This in turn will inform on class-specific or group-sp ecific variables which would need to be added to address uncertainty and t he limited spectral information. In conjunction with a previous ecological priority review\, adjacent data will be researched for habitats which are more difficult to map but are of high ecological importance in terms of l ong-term landscape change. Potential auxiliary sources include digitized d ata [5] or even automated feature extraction from topographical maps (Sieg fried maps).\nThe data for the model was chosen using a stratified random sampling technique. The extent of Switzerland was gridded into 512x512px t iles. The choice of the tiles was stratified in a first phase using the 12 biogeographical regions of Switzerland. Upon preliminary results\, additi onal stratification on habitat composition\, certain habitat coverage perc entage or elevation might be considered. 5% of tiles of each biogeographic al region were randomly selected\, resulting in 7356 tile-mask pairs. Per region\, the tile-mask pairs were separated into 70% for training\, 20% fo r validation and 10% for testing. \nThe lack of validation data for histor ical imagery is one of the biggest challenges of the project. Therefore\, in the first step\, the model will be trained and tested on current aerial imagery converted to grayscale and degraded with artifacts common to hist orical imagery. This way\, the feasibility of mapping the wide range of Ty poCH habitats will be tested with robust validation based on the current H abitat Map of Switzerland. In further steps\, the model will be strategica lly applied on historical imagery and potentially active learning and/or z ero-shot segmentation algorithms will be used to generate historical train ing data\, aided by time-series comparisons. \n\n*Expected results\, impl ications and conclusions*\nThe first part of the project will show which h abitats can be mapped from historical imagery\, providing a methodology wh ich can be transferred in other areas with historical data availability. T hen the method will be scaled Swiss-wide on multiple time steps\, showing types and rates of habitat change and link the results to management pract ice and the current biodiversity status. The results will have broad impli cations on future conservation measures\, land management policies\, and r estoration actions. Given the amount of data available for Switzerland\, t raining a geofoundation model specialized on historical grayscale imagery and object change detection would be an idea to be explored as a future pa rt of this project using the knowledge and data obtained from preliminary model testing. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Habitat Change Mapping Using Historical Aerial Imagery and Deep Lea rning — Francesca Drăguț URL:https://talks.osgeo.org/foss4g-europe-2026/talk/BGWUCE/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-4a926ead-bec9-59b2-8209-098a34a9097c@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T154500 DTEND;TZID="+03:00":20260629T155000 DESCRIPTION:Earth system science is increasingly driven by an unprecedented influx of heterogeneous Earth observation and model data\, but these data typically arrive as disparate products\, tiles\, and collections rather t han as uniform analysis-ready cubes. In response\, a growing set of data c ube frameworks aims to integrate heterogeneous datasets into common\, inte roperable spatio-temporal structures. Earth System Data Cubes (ESDCs) are one such framework (Mahecha et al.\, 2020)\, and can be understood as labe lled\, multi-dimensional arrays of Earth system data that organize variabl es consistently across space and time (or any other dimension)\, enabling uniform operations across common grids. Concretely\, ESDCs comprise (1) la belled dimensions defining the data cube axes\, (2) one or more grids with coordinate values distributed along these dimensions\, (3) univariate val ues associated with each grid cell\, and (4) a suite of attributes that ch aracterise the data variables\, the dimensions\, and the cube entity as a whole. In practice\, however\, building such data cubes still requires sig nificant engineering to discover datasets\, harmonize metadata\, and creat e consistent arrays that Artificial Intelligence (AI) models can consume ( Montero et al.\, 2024a).\n\nIn recent years\, the SpatioTemporal Asset Cat alog (STAC) specification has become a widely adopted way to describe and access cloud-hosted geospatial assets\, enabling programmatic discovery an d standardized links to imagery and other derived products. Building on th is ecosystem\, we developed cubo (Montero et al.\, 2024b)\, an open-source Python tool for creating AI-focused ESDCs from STAC catalogues\, producin g data cubes (as xarray objects) on regular spatial grids with consistent array shapes (e.g. matching pixel counts along x and y or longitude and la titude). Yet a large portion of routinely used Earth observation data is a ccessed through Google Earth Engine (GEE)\, a cloud-based platform that ho sts a large\, curated catalogue of geospatial datasets and provides scalab le\, planetary-scale analysis via both JavaScript and Python APIs (Gorelic k et al.\, 2017). The catalogue spans long optical and radar satellite arc hives (e.g. Landsat and Sentinel-1 and Sentinel-2)\, widely used global pr oducts (e.g. MODIS\, ERA5 reanalysis\, SRTM)\, and thematic layers and der ived datasets such as land cover and vegetation indices.\n\nAs a result\, users face a fragmentation problem: cubo can readily create ESDCs from STA C catalogues\, but datasets that are primarily accessed via GEE remain out of reach for the same data cube specification and output conventions.\n\n Here we present a Google Earth Engine (GEE) backend for cubo that generate s on-demand AI-focused Earth System Data Cubes (ESDCs) directly from GEE\, using the same data cube specification concept developed initially for ST AC catalogues and returning consistent xarray outputs (Hoyer and Hamman\, 2017).\n\nThe optional GEE backend mirrors the STAC workflow in cubo: user s specify cube centre coordinates (longitude and latitude)\, a temporal wi ndow\, bands\, cube edge size (pixels)\, and a target spatial resolution\, and cubo derives the corresponding bounding box in the local Universal Tr ansverse Mercator (UTM) Coordinate Reference System (CRS). This keeps the data cube definition explicit and comparable across studies\, and it makes the data preparation step a parameterized part of the workflow. The key d ifference is the data access layer: instead of retrieving assets via STAC (using stackstac: https://github.com/gjoseph92/stackstac)\, cubo queries G EE collections through xee (https://github.com/google/Xee)\, an xarray int erface to Earth Engine that returns the result directly as xarray objects. From the user perspective\, the same cube specification is reused\, with the collection identifier now pointing to a GEE collection. The only addit ional argument in the main cubo function is selecting the GEE backend (via a boolean flag). This keeps data cube construction consistent across back ends while leveraging GEE as a scalable data access and processing environ ment.\n\nBy aligning GEE-based cube creation with an existing STAC-based c ube workflow\, the GEE backend lowers the practical barrier to switching b etween catalogues and platforms without rewriting entire pipelines. It als o opens up access to datasets that are primarily available through GEE (e. g. CloudScore+\, Dynamic World\, or the novel AlphaEarth Embeddings) while still adhering to the same cube specification and output conventions. Ret rieving data cubes from GEE and from STAC catalogues using the same cube s pecification also enables users to merge data cubes across backends with m inimal effort\, since they share consistent dimensions and coordinates. Th is is particularly relevant for open geospatial ecosystems\, where interop erability and transparent data preparation are prerequisites for comparabl e results across studies.\n\nWe release the Earth Engine support as an opt ional backend in cubo (installable via the extra cubo[ee])\, which is free and open source\, hosted on GitHub (https://github.com/ESDS-Leipzig/cubo) \, and distributed through common Python channels (PyPI and conda-forge). We expect users to benefit from this update since they can now retrieve da ta from both STAC catalogues and GEE in the same way for their scientific workflows\, using consistent cube specifications across backends.\n\nLooki ng forward\, we plan to extend cubo so that multiple datasets can be retri eved and organised directly into a single data cube without rerunning the full workflow for each collection\, regardless of the backend they come fr om. We also plan to broaden the set of supported backends to additional wi dely used packages in the open geospatial ecosystem\, such as odc-stac. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:A unified framework for building AI-focused Earth System Data Cubes across STAC and Google Earth Engine — David Montero Loaiza URL:https://talks.osgeo.org/foss4g-europe-2026/talk/BVBPNG/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-e37e84e4-0062-598e-a9cc-cc74e3fdc0b2@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T163000 DTEND;TZID="+03:00":20260629T173000 DESCRIPTION:Stay tuned! More info coming soon! DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Surprise Keynote! — Marian Neagul URL:https://talks.osgeo.org/foss4g-europe-2026/talk/FZKUP3/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-d804b34a-ad51-5664-a959-7ab2dd5724d4@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260629T180000 DTEND;TZID="+03:00":20260629T200000 DESCRIPTION:The B2B networking event offers a unique opportunity to connect with businesses\, experts\, and fellow participants in a relaxed atmosphe re just across the university main venue and near the Bega River.\n\nFinge r food buffet (tortilla with smoked salmon\, avocado and mixed salad\, foi e gras terrine with red onion jam\, wagyu beef bruschetta and tonkatsu dre ssing\, sandwich with brisket\, horseradish and cedar sauce\, hummus with pomegranate caviar and pickled cucumbers\, toast with pork tenderloin and mushroom mousse\, cedar cheese balls in charcoal crust\, bison miniburgers with mammouth hot sauce) with open bar (water\, coffee\, beer\, local win es) will be provided during the event.\n\nThis event is available to those who have purchased a B2B ticket.\n\nWe look forward to welcoming you in T imisoara. DTSTAMP:20260602T160506Z LOCATION:ZAZA Resto Pub SUMMARY:Business-to-business — URL:https://2026.europe.foss4g.org/schedule/b2b/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-72c820c4-7138-5c7d-946d-6a7e50d930cc@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T093000 DTEND;TZID="+03:00":20260630T103000 DESCRIPTION:Stay tuned! More info coming soon! DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Surprise keynote — Marian Neagul URL:https://talks.osgeo.org/foss4g-europe-2026/talk/8DGWWG/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-ec82aae6-a6e2-5ec4-9ad9-9e4378468502@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T103000 DTEND;TZID="+03:00":20260630T110000 DESCRIPTION:As a public agency\, IGN has an obligation to publish in open f ormat the data it produces and some of the code it develops. But our commi tment to Open Source goes beyond giving access to the code produced and fo r more than ten years\, IGN (the French map agency) has been engaged in cr eating Digital Commons\, both in terms of data and in terms of code. In ad dition to contributing to well-known open-source libraries (pdal\, gdal\, etc.)\, our developers push a large part of their code on public repositor y on github. And\, for some\, we are working to build and animate a commun ity of contributors and users. \n\nIn this conference\, we will explain wh y a national mapping agency has chosen to adopt such an approach and why w e believe Digital Commons are strategic to build a sustainable and collabo rative future. We will give a quick overview of the code we are making ope n source and the organization that this involves (in particular\, the crea tion of an Open Source Program Office - OSPO). \n\nFinally\, we will prese nt our recent activities\, organizational (internal drafting of guides\, F AQs\, etc.) and technical (new project and ongoing developments) and also contributions we can make with other organizations and companies involved in open source initiatives (notably participation in Tosit\, a gathering o f French companies focused on open source). DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:National map Agency - how to build Digital Commons ? — lavenant\, Rémi Ferrier URL:https://talks.osgeo.org/foss4g-europe-2026/talk/GW3YWD/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-b93b3ca6-7c8a-51b0-ae71-6270001ab4d9@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T103000 DTEND;TZID="+03:00":20260630T110000 DESCRIPTION:For some of us\, terminal windows are ubiquitous. Whether we lo ve them or just find them convenient\, there's always one open. However\, we best know them as grids of text. Can we escape this 80x25 prison and bu ild something that resembles an interactive GIS application?\n\nDuring thi s talk\, we'll take a look at some terminal protocol extensions and librar ies in the Rust ecosystem. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Escaping the cell grid: Terminal GIS — Laurențiu Nicola URL:https://talks.osgeo.org/foss4g-europe-2026/talk/DAUWH8/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-999e8ee0-03e2-59af-9890-27fcada682ab@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T103000 DTEND;TZID="+03:00":20260630T110000 DESCRIPTION:PostgreSQL and PostGIS remain the default choice for geospatial data management. Their strict ACID compliance and extensive spatial capab ilities cover most standard use cases. However\, scaling a dynamic\, multi -tenant WebGIS platform\, where users continuously upload custom datasets\ , reveals the scalability boundaries of traditional relational architectur es.\n\nDuring the development of the WebGIS platform\, [GOAT](https://gith ub.com/plan4better/goat)\, we encountered these constraints directly. Init ially\, all spatial data was stored in a monolithic PostgreSQL database. T o prevent the system catalogs from overloading due to creating thousands o f user-specific tables\, we consolidated datasets into multi-tenant tables grouped by geometry type. This stabilized the table count\, but as platfo rm adoption increased\, individual tables rapidly exceeded 50GB. The resul ting volume of data and indexes degraded query performance and complicated maintenance.\n\nAttempting to resolve this computationally\, we implement ed Citus to shard and distribute the data. While this approach provided ve rtical scaling\, managing a distributed PostgreSQL cluster introduced sign ificant operational complexity. Furthermore\, the application logic requir ed extensive refactoring to accurately route queries using distribution co lumns. When we evaluated horizontal scaling through read replicas\, the in frastructure cost of duplicating a multi-terabyte database proved prohibit ive for a small team. Even with a strong preference for the PostGIS ecosys tem\, we were maintaining a fragile system that was slow to back up and di fficult to sustainably host.\n\nA common structural response to this chall enge is separating storage from compute via a lakehouse architecture. We e valuated managed solutions like BigQuery and Databricks\, which offer expa nding spatial support. Yet\, for an open-source project\, these platforms present distinct disadvantages: high costs\, vendor lock-in\, and an inabi lity to be self-hosted\, bypassing data sovereignty requirements for certa in clients. Focusing on open-source frameworks\, Apache Iceberg stood out as a mature\, production-ready standard. However\, we ultimately opted to test a novel framework still in its early stages: DuckLake. \n\nDuckLake p rovides a strict separation of concerns. It manages metadata within a ligh tweight relational database while storing the actual data in highly compre ssed Parquet files. Built around DuckDB\, it allows direct access to DuckD B's native spatial functions\, including vector tile generation.\n\nWe int egrated DuckLake despite its beta status\, primarily to test DuckDB's mini mal storage requirements\, strong analytical capabilities\, and open-sourc e foundation. The infrastructural shift was measurable. Transitioning larg e-scale system layers—such as nationwide street networks—and user data from PostGIS to Parquet reduced our total storage footprint by at least 9 0%. This was achieved through a combination of Parquet's columnar compress ion and the elimination of traditional database indexes\, which previously accounted for a massive portion of our storage.\n\nCurrently\, our data i s stored on scalable volumes and backed up to S3-compatible object storage . Analytical compute has been decoupled and is managed by Windmill\, orche strating background Python jobs to execute DuckDB queries on demand. While a minor subset of highly specific queries show slight performance regress ions compared to PostGIS\, the vast majority execute significantly faster. This shift is particularly noticeable during large-scale spatial analytic s\, as columnar storage outperforms row-based continuous reading when scan ning and aggregating massive datasets. \n\nBecause Parquet files are high ly compressed and immutable\, they cannot be edited in place. To support d ata mutations\, DuckLake writes edits to separate delta files\, which are dynamically merged during query execution. Furthermore\, DuckLake can save small edits directly to PostgreSQL using inlining. The underlying metadat a layer\, responsible for tracking these file shifts\, is managed by Postg reSQL. Since PostgreSQL is optimized for rapid transactions\, this hybrid approach allows us to retain the metadata management of a relational datab ase while utilizing the storage efficiency of Parquet for massive spatial datasets. Additionally\, DuckLake provides built-in support for versioning and time travel\, maintaining a history of data mutations.\n\nWhile analy tical workloads benefited from this architecture\, we encountered distinct challenges regarding the high-frequency queries required by web mapping. Although Parquet files can be optimized through sorting and partitioning\, they are not naturally designed for the low-latency\, point-lookup access patterns required by vector tile or feature services. Notably\, standard Parquet implementations do not inherently support spatial indexes\, meanin g spatial queries often trigger full file scans rather than targeted reads .\nSpecifically\, generating dynamic vector tiles requires evaluating and filtering entire Parquet files for every incoming user request\, creating a severe performance bottleneck on larger datasets. Additionally\, maintai ning continuous access to the PostgreSQL metadata layer via DuckDB frequen tly exhausted database connection limits\, which introduced noticeable lat ency during initial query execution.\n\nTo mitigate these issues\, we intr oduced connection pooling using PgBouncer and caching strategies via Redis . However\, these solutions only masked the underlying problem for large d atasets. Ultimately\, we adopted a hybrid vector tile architecture to bypa ss these limitations: we rely on static vector tiles generated by Tippecan oe for base layers\, reserving DuckDB's dynamic\, on-the-fly vector tile g eneration strictly for volatile\, filtered\, or actively edited datasets.\ n\nDuring the development of GOAT\, testing DuckLake demonstrated both its current utility and its limitations. While the framework is still in its early stages and requires architectural workarounds—like our hybrid vect or tile setup—to handle low-latency web mapping\, it functions as a prac tical complement to PostgreSQL and PostGIS for heavy analytical workloads. The upcoming native support for GeoParquet is expected to address several of the current performance bottlenecks by introducing geometry as a nativ e Parquet type\, which should improve execution times for spatial bounding box and intersection queries. For analytics-heavy platforms managing mult i-tenant data\, the combination of DuckLake and DuckDB offers an alternati ve approach to scaling spatial infrastructure while maintaining manageable server costs. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:DuckLake: A scalable data lakehouse for web mapping? — Majk Shkur ti URL:https://talks.osgeo.org/foss4g-europe-2026/talk/33YRC7/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-6fd6d89b-b3af-51bf-99f9-bc2a8be2f047@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T103000 DTEND;TZID="+03:00":20260630T110000 DESCRIPTION:The presentation will provide a comprehensive introduction to G eoServer’s authentication and authorization subsystems. The authenticati on section will cover the supported protocols (e.g.\, Basic/Digest authent ication) and identity providers (such as local configuration files\, datab ases\, LDAP servers\, and OAuth2/OpenID Connect)\, including scenarios whe re the same source may fulfill both roles.\n\nIt will explain how to combi ne multiple authentication mechanisms into a unified and coherent security framework\, and will present examples of custom authentication plugins fo r GeoServer\, enabling integration with bespoke security architectures. Th e presentation will then address authorization\, describing GeoServer’s pluggable authorization model and comparing it with external proxy-based s olutions. The default service and data security system will also be examin ed\, highlighting its strengths and limitations.\n\nFinally\, we will expl ore the advanced authorization provider\, GeoFence. The various levels of integration with GeoServer will be presented\, ranging from simple\, seaml ess direct integration to more sophisticated external deployments. We will conclude by showcasing GeoFence’s powerful authorization capabilities\, including:\n\n* User- and role-based access control\n* OGC service\, work space\, layer\, and layer group restrictions\n* CQL read and write filters \n* Attribute-level security\n* Spatial filtering of raster and vector dat a based on areas of interest DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Mastering Security with GeoServer\, GeoFence\, and OpenID — Andre a Aime URL:https://talks.osgeo.org/foss4g-europe-2026/talk/SPFHGR/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-5975d7ce-481e-537d-8f3d-fb8c5c28aa09@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T113000 DTEND;TZID="+03:00":20260630T120000 DESCRIPTION:Europe is entering a new geopolitical and economic phase. Resil ience\, competitiveness\, and digital sovereignty are moving to the centre of public debate. In that context\, open source is no longer seen only as a software development model or a community ethos. It is becoming part of how Europe thinks about digital capacity and sovereignty.\n\nFor the geos patial community\, this shift matters deeply. Open-source geospatial softw are forms part of the operational backbone through which data is processed \, interpreted\, and turned into public value. Despite Europe’s strong c ommunities\, mature projects\, and world-class technical leadership\, cybe rsecurity\, scaling and long-term sustainability remains fragile. This is now being recognised more explicitly at European level\, including through the European Open Digital Ecosystem Strategy and the Horizon 2026 Work Pr ogramme. The former is a component of the upcoming European Commission’s Technological Sovereignty package\, whose adoption is expected for Q2 202 6\; the latter offers an opportunity for the community to address sustaina bility considerations through economic leadership.\n\nThis talk reflects o n that changing landscape through the lens of research\, innovation\, and Europe’s evolving strategic context. It explores how emerging debates on digital sovereignty\, AI\, and open digital ecosystems are beginning to r eshape the wider landscape for FOSS4G in Europe. Together\, we will discus s what digital sovereignty may mean in practice for geospatial open source \, what kinds of support structures are needed to move from individual pro ject success to durable ecosystem capacity\, and how developers\, communit ies\, institutions\, and companies can help define models of sustainabilit y that preserve openness while strengthening European capacity.\n\nThe aim is to look beyond policy slogans and consider the deeper shift now underw ay. If geospatial open source is becoming part of Europe’s strategic fut ure\, would the community be ready to respond\, and how? What are the exis ting gaps to fill\, challenges to address\, and opportunities to be aware of? And what kind of European digital future does it want to help build?\n \n* Call for Evidence on the European Open Digital Ecosystem Strategy: htt ps://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/162 13-European-Open-Digital-Ecosystems_en \n* A services and business incubat or for geospatial open-source developments: https://ec.europa.eu/info/fund ing-tenders/opportunities/portal/screen/opportunities/topic-details/HORIZO N-CL6-2026-03-GOVERNANCE-06?keywords=incubator&isExactMatch=true&status=31 094501\,31094502\,31094503&programmePeriod=2021%20-%202027&frameworkProgra mme=43108390&order=DESC&pageNumber=1&pageSize=50&sortBy=relevance\n\n* Di Marco D.\, Thabit S.\, Kotsev A.\, Christensen A.\, Minghini M. et al.\, O pen but Not Powerless:\nTowards a Common Understanding of EU Digital Sover eignty\, European Commission Ispra\, 2025\, JRC144908: https://publication s.jrc.ec.europa.eu/repository/handle/JRC144908 DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Open Source\, Digital Sovereignty and Europe’s Geospatial Future — Marco Minghini\, Stefanie Lumnitz URL:https://talks.osgeo.org/foss4g-europe-2026/talk/GDZ9SQ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-45c6f127-abb5-53e9-ad1d-aad21b63cc31@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T113000 DTEND;TZID="+03:00":20260630T120000 DESCRIPTION:**This introductory talk aims at giving a conceptual overview a nd application examples for using Discrete Global Grid Systems in daily GI S analysis and visualisation tasks.**\n\nNear-real-time data\, time series data and other spatio-temporal event data are often subject to the need f or cartographic visualisation sooner or later\, regardless of their intend ed purpose of analysis. If a web visualisation is planned\, data preparati on is a challenging task\, as a prototypical quick-and-dirty web presentat ion in the browser quickly reaches its performance limits with large amoun ts of data. Depending on the application\, the raw data volumes can be hug e. The provision of raw data via OGC web services also scales poorly with increasing data volumes.\n\nThis is where aggregation or generalisation of the data becomes necessary. Self-defined grids\, official or national gri d systems and discrete global grid systems (DGGS) are very well suited for this. Some variants such as the INSPIRE-based [geographical grid for Germ any](https://gdz.bkg.bund.de/index.php/default/inspire/sonstige-inspire-th emen/geographische-gitter-fur-deutschland-in-lambert-projektion-geogitter- inspire.html)\, [Uber's hexagonal grid system H3](https://h3geo.org/) and [Google's hierarchical grid system S2](http://s2geometry.io/) will be brie fly compared in the presentation.\n\nAlthough web mapping frameworks such as OpenLayers already offer practical methods such as [HexBin](https://vig lino.github.io/ol-ext/doc/doc-pages/ol.source.HexBin.html) for creating a hexagon grid for a spatial aggregation of source data\, all source data mu st first be transferred to the client's browser\, which — experience has shown — quickly leads to performance problems. \n\nTwo project examples are giving a glimpse on more effective approaches for efficiently aggrega ting time series data in the hexagonal grid system H3:\n\n- Via post-proce ssing at database level using the PostgreSQL extension [h3-pg](https://git hub.com/postgis/h3-pg) and\n- in real time during streaming data processin g with Apache Flink by using the [H3 implementation in Java](https://githu b.com/uber/h3-java).\n\nThe ultimate goal in both cases is always a high-p erformance provision of the aggregated result data via OGC web interfaces such as WMS/WFS or API – Maps/API – Features. In this way\, results ar e easily exchangeable and can be used flexibly in analysis tools of variou s players.\n\nFinally\, [DGGAL](https://dggal.org/) and [Vgrid](https://vg rid.gishub.vn/) with bindings for Python and QGIS will be recommended as h andy open-source tools. We may also take a look at the DGGS working group of the OGC and the OGC standard [API – DGGS](https://www.ogc.org/de/stan dards/dggs/).\n\nThe talk aims to present an approach to grid aggregation that is as generic as possible\, so that the transferability of this pract ical methodology to numerous other statistical use cases is conveyed. In p articular\, traffic data\, movement data and sensor data can be elegantly visualised with little effort and prepared for further analysis applicatio ns. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Discrete global grid systems for spatio-temporal aggregation and vi sualisation — Michael Scholz URL:https://talks.osgeo.org/foss4g-europe-2026/talk/JZNM93/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-b79de715-04c5-5bdf-87df-b5b1f3f76ae4@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T113000 DTEND;TZID="+03:00":20260630T120000 DESCRIPTION:An overview of the osm2pgsql commandline tool. The talk shows t he basic features\, the latest developments and demonstrates how to use it for importing OpenStreetMap data into a PostgreSQL / PostGIS database. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:osm2pgsql - Processing OpenStreetMap data with PostGIS — Jakob Mi ksch URL:https://talks.osgeo.org/foss4g-europe-2026/talk/XWGPXA/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-39bb344a-dbc7-516e-8893-50dfc8e9a3b8@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T113000 DTEND;TZID="+03:00":20260630T120000 DESCRIPTION:mapchete EO extends mapchete with abstractions and utilities to read from Earth Observation (EO) archives\, with a primary focus on Senti nel-2 data. While mapchete provides a tile-based execution model for raste r and vector processing\, mapchete EO enables reading multidimensional arr ays (time series) from well known data archives.\n\nClass-based abstractio ns for handling Sentinel-2 products were engineered to also enable usage o utside of the mapchete context. They provide a unified interface to variou s data and metadata archives to automatically mask data using all availabl e metadata masks (SCL\, L1C\, etc.) as well as to apply BRDF correction wh ile reading the datza.\n\nThe second part of the talk focuses on operation al experience from processing Sentinel-2 data at global scale for the EOxC loudless product line. At this scale\, the system has to have multiple lay ers of fallbacks and retries in order to accomodate I/O related and tempor ary failures.\n\nAdditional challenges arise when processing data across t he antimeridian\, where data coverage is not consistent between various ar chives. These edge cases expose limitations that are not apparent in small er-scale workflows and require careful handling within global processing p ipelines.\n\nThe presentation will outline these challenges and discuss th eir implications for the design of robust\, large-scale Sentinel-2 process ing pipelines within an open source framework. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:mapchete EO: Abstractions for Sentinel-2 Data Access and Processing — Joachim Ungar URL:https://talks.osgeo.org/foss4g-europe-2026/talk/FZYGGU/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-b54a7709-8e0d-5e2f-8a1d-364c0138953d@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T113000 DTEND;TZID="+03:00":20260630T120000 DESCRIPTION:Discrete Global Grid Systems (DGGS) are increasingly adopted as a unified spatial reference framework for organising and analysing multi- source geospatial data at global scale. Among hexagonal DGGS configuration s\, refinement ratio 7 systems exhibit particularly desirable properties: they preserve hexagonal symmetry across refinement levels and produce unam biguous indexing hierarchies where each cell maps to exactly one parent (S ahr\, 2011). The recently introduced IGEO7 system and its associated Z7 hi erarchical integer indexing scheme (Kmoch et al.\, 2025) provide a pure ap erture 7 equal-area hexagonal DGGS implemented in the open-source DGGRID s oftware. While IGEO7/Z7 offers significant theoretical advantages over sys tems such as H3\, such as true equal-area cells versus H3’s ±50% cell s ize variation\, practical challenges remain in translating these advantage s into efficient\, scalable computational workflows. This paper addresses three interconnected challenges: (1) the algorithmic foundations of Z7 nei ghbourhood computation using Generalised Balanced Ternary (GBT) arithmetic on the int64 bit-packed index\, (2) the alignment of Z7’s hierarchical index structure with cloud-native storage layouts in Zarr via monotonic pa rent-based range indexing\, and (3) a practical demonstration through slop e gradient computation as a representative focal operation on hexagonal DG GS.\nA Z7 index is a 64-bit unsigned integer where the first 4 bits encode the base cell number (0–11\, corresponding to the 12 pentagonal cells a t the icosahedron vertices)\, and the remaining 60 bits encode up to 20 re solution digits at 3 bits each (values 0–6\, with 7 marking digits beyon d the cell’s resolution). This compact bit-packed representation enables efficient hierarchical operations through bitwise manipulation: parent ex traction requires only masking and setting trailing digit groups to 7\, wh ile resolution determination reduces to scanning for the first occurrence of the sentinel value 7. The encoding ensures that all children of a given parent cell share a common bit prefix\, a property that is fundamental to both neighbourhood computation and storage optimisation.\nNeighbourhood f inding in Z7 leverages GBT arithmetic\, which is a generalisation of balan ced ternary to the three axes of a hexagonal grid (Sahr\, 2019). Each of t he six neighbours of a cell is computed by performing digit-wise addition of a direction vector (digits 1–6) to the cell’s index implemented via bitshifting\, starting at the finest resolution digit and propagating car ries toward coarser levels. Because the aperture 7 grid alternates orienta tion between successive resolutions (approximately ±19.1° rotation)\, th e addition tables alternate between clockwise and counter-clockwise varian ts at odd and even resolutions respectively. Each per-digit operation invo lves a table lookup (a 7×7 matrix yielding both the result digit and a ca rry digit)\, making the overall algorithm O(r) in complexity where r is th e resolution. When the carry propagates beyond the first resolution digit\ , the neighbour crosses into an adjacent base cell\, requiring a lookup in the icosahedral adjacency table and potential rotational corrections at p olar base cells. We present a Python/Numba implementation of this algorith m that operates directly on arrays of uint64 Z7 indices\, achieving vector ised batch neighbourhood computation suitable for large-scale raster-style analysis.\nThe hierarchical prefix property of Z7 indices\, where all chi ldren of a parent share a common bit prefix\, directly enables an efficien t storage layout for cloud-native Zarr archives. When Z7 indices at a give n resolution are sorted numerically\, cells within the same parent region are stored contiguously. This creates a monotonic range index where any pa rent zone’s children can be retrieved through a simple range query on th e sorted 1-D index dimension. We describe how xarray-xdggs (XDGGS\, Kmoch et al\, 2024) exploits this property: DGGS-indexed data is encoded as 1-D Zarr arrays with the Z7 cell ID as the coordinate dimension (but stored on ly as the start and end IDs)\, and chunking boundaries are aligned with co arser-resolution parent boundaries (e.g.\, chunking at resolution N-4 or N -5 while storing data at resolution N). This alignment ensures that hierar chical queries\, i.e. aggregation from index children to logical parents\, or drill-down from parents to children\, traverse contiguous storage bloc ks\, minimising I/O operations in cloud-object-storage environments. The a pproach mirrors the storage optimisation patterns known from quad-trees ov erviews or the HEALPix nested indexing but extends naturally to aperture 7 hierarchies. We also discuss how Zarr’s metadata attributes are used to record DGGS parameters (grid type\, indexing scheme\, refinement level)\, enabling self-describing archives that can be leveraged for large scale c omputations.\nAs a practical demonstration\, we implement a slope gradient computation\, a classical focal GIS operation in terrain analysis\, opera ting entirely within the Z7 index space. For each cell\, the algorithm ret rieves the six neighbours via GBT arithmetic\, obtains the elevation value s and their relative directions to each other\, calculates the elevation d ifferences along the three hexagonal axes onto two orthogonal components\, and computes the slope from the combined partial derivatives. This finite -difference approach\, adapted from Li et al. (2022)\, benefits from the u niform adjacency and equal weighting inherent to hexagonal cells\, elimina ting the directional bias present in rectangular grid slope computations. We implement this using Xarray for data management\, Numba-accelerated fun ctions for batch Z7 neighbour lookups on uint64 arrays\, and demonstrate t he end-to-end workflow from Zarr-stored elevation data through to a Zarr-s tored slope product. All data is indexed by Z7 cell IDs without any interm ediate coordinate transformations.\nOur results show that the combination of Z7’s bit-packed int64 representation\, GBT-based neighbourhood arithm etic\, and parent-aligned Zarr chunking provides a coherent\, performant s tack for DGGS-native geospatial analysis. The approach is implemented usin g open-source Python tools (Numba\, Xarray\, XDGGS\, Zarr) and is designed to integrate with emerging DGGS standards and cloud-native data infrastru cture. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Efficient Neighbourhood Computation and Cloud-Native Storage for th e IGEO7 DGGS Using the Z7 GBT Indexing — Alexander Kmoch URL:https://talks.osgeo.org/foss4g-europe-2026/talk/HSFXR3/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-39e28d19-c298-57b3-96ac-d1c16b2a029c@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T120000 DTEND;TZID="+03:00":20260630T123000 DESCRIPTION:Amid escalating geopolitical tensions and growing dependence on foreign digital infrastructure\, digital sovereignty has become an urgent priority for governments\, public institutions\, and scientific organizat ions in Europe. Despite marketing terms like *sovereign cloud*\, legal fra meworks such as the *U.S. CLOUD Act* and *FISA 702* continue to expose Eur opean data to extraterritorial access\, revealing a structural mismatch be tween political ambitions\, geopolitical threats\, and technological reali ty.\n\nThis talk explores how open‑source geospatial ecosystems offer a practical\, scalable pathway toward genuine digital autonomy. Open source provides transparency\, auditability\, and the ability to self‑host and adapt tools to local needs and jurisdiction. It enables reproducible analy tics\, secure handling of sensitive geodata\, and long‑term independence from vendor lock‑in. The presentation also discusses viable business mo dels for commercial open source\, showing how companies can sustainably bu ild services\, consulting\, hosting\, and innovation on top of open founda tions without compromising user sovereignty and by contributing to open so urce communities.\n\nHowever\, achieving sovereignty is not only a technic al challenge\, it is also a procurement and governance challenge. Current public‑sector tendering practices often unintentionally exclude open‑s ource solutions through over‑specification\, popularity bias\, certifica tion requirements\, and tight timelines. These structural barriers limit i nnovation and reinforce dependency on proprietary ecosystems or vendors wh o market themselves as “open” without adhering to open‑source princi ples.\n\nTo address this\, the talk argues for the development of a certif ication or trustmark for genuine open‑source companies\, helping public institutions distinguish between truly open providers and those using “o pen‑washing” to lock customers into non–big‑tech proprietary ecosy stems. Organizations such as OSGeo\, national QGIS and OSGeo user groups\, and broader open‑source communities can play a crucial role in defining such standards\, raising awareness among procurement officers\, and suppo rting fair\, transparent\, sovereignty‑aligned procurement processes.\n\ nUltimately\, the talk argues that sovereignty is not a checkbox but a lon g‑term commitment\, and that open source is not merely an alternative\, but a strategic necessity for Europe’s digital future. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Open Source for Digital Sovereignty: Business Models\, Trustmarks\, and Procurement Reform — Hans van der Kwast URL:https://talks.osgeo.org/foss4g-europe-2026/talk/LSNDUH/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-92dac988-58f3-548f-a41f-cb9ed90841f2@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T120000 DTEND;TZID="+03:00":20260630T123000 DESCRIPTION:The PROJ library (https://proj.org) is widely used in GIS and s urveying software. Most of the people know it because of its ability to pr eform projections (v.g. Transverse Mercator or Spilhaus).\n\nHowever PROJ is able to do more things in addition to projections. This talk will go th rough some of these features\, like datum transformations\, CRS catalogs ( like EPSG\, ESRI\, IGNF\, ...)\, grid files\, geodetic computation\, proje ction distortion factors\, transformation pipelines\, etc.\n\nThe presenta tion will use the page https://jjimenezshaw.github.io/wasm-proj/ to show s ome of these features. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:PROJ is not only about projections — Javier Jimenez Shaw URL:https://talks.osgeo.org/foss4g-europe-2026/talk/SSCMFH/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-5487c1e1-9fcb-5d95-8517-11a0b0a01e15@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T120000 DTEND;TZID="+03:00":20260630T123000 DESCRIPTION:Modern Enterprise GIS is nowadays built with FOSS4G softwares. Many organizations are in the middle of transition to build EntrepriseGIS and some organizations are still planning to move from old fashioned close d source software implementations to open source solutions. FOSS4G based E nterprise GIS is commonly built with PostGIS based GIS database\, QGIS des ktop software\, mobile applications (like QField and Mergin Maps) and web applications servers (like QGIS Server\, Geoserver). The most crucial and enduring component of an Enterprise GIS solution is the database. This pre sentation will cover how to design\, build and maintain a GIS database for Enterprise usage. The presentation also includes best practices and recom mendation of tools for Enterprise GIS database management.\n\nEnterprise G IS is an organization-wide suite of interoperable GIS software used to man age and process geospatial information. Following the basic principles of enterprise architecture\, its structure is based on three distinct layers: the User Interface\, the Application Server\, and Data Storage. This pres entation will focus on how to build a robust and efficient Data Storage la yer with PostGIS database.\n\nThis presentation will cover the following t opics:\n- GIS database design and modelling with open source solutions\n- Best practices for GIS data modelling and versioning of data models\n- Org anise and manage the Enterprise GIS database in PostgreSQL cluster\n- Best practices for access privileges in Enterprise GIS database\n- QGIS relate d data storage to PostGIS\n- Manage database connections and credentials i n QGIS\n\nThis presentation is essential for GIS database managers\, GIS m anagers\, and all users of Enterprise GIS solutions. Attendees will be equ ipped with the fundamental knowledge and practical best practices — incl uding valuable tips-and-tricks — required to effectively build and maint ain a robust Enterprise GIS database. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Enterprise GIS: Building and Maintaining the Database — Pekka Sar kola URL:https://talks.osgeo.org/foss4g-europe-2026/talk/Z7QGGL/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-8a950d92-d9b5-5480-8d42-68519a7a5740@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T120000 DTEND;TZID="+03:00":20260630T123000 DESCRIPTION:Never before has such a vast and diverse collection of satellit e imagery been available to both organizations and the general public. Wit h missions such as Landsat 8 and Sentinel\, the rapid growth of CubeSats\, and the open availability of global datasets through programs like the Eu ropean Copernicus initiative—alongside data captured by drones—we are now experiencing an unprecedented influx of Earth observation data.\n\nEff ectively managing\, discovering\, and visualizing this volume of imagery p resents significant challenges. This presentation explores how GeoServer a ddresses these challenges through real-world use cases\, including:\n\n- I ndexing and discovery of imagery using OpenSearch for EO and STAC protocol s\n- Efficient and cost-effective management of large datasets with Cloud Optimized GeoTIFFs (COGs)\n- Visualization of image mosaics and creation o f composites with flexible filtering and stacking strategies (e.g.\, most recent\, least cloudy\, or custom ordering)\n- Extraction of imagery at va rying scales using WCS and WPS protocols\n- Generation and visualization o f time-based animations over selected periods\n- Execution of band algebra operations using Jiffle\n\nJoin this session for an overview of the lates t GeoServer capabilities in the Earth Observation domain. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Serving earth observation data with GeoServer: addressing real worl d requirements — Andrea Aime\, Simone Giannecchini URL:https://talks.osgeo.org/foss4g-europe-2026/talk/YSDMSM/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-9c24e14d-b65b-5a61-bf88-d0023adf3e4b@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T120000 DTEND;TZID="+03:00":20260630T123000 DESCRIPTION:The FOSS4G Observatory is an initiative that started 10 years a go in quite a different world.\nIn 2016\, we were setting out to better un derstand what are the open source solutions in the geospatial realm\, foll owing the technological progress to answer the intimidating challenges on the horizon. Stable and operational stacks for serving impossible amounts of satellite data to thousands of users simultaneously\, allowing complex processing and fast visualisations\, integration of numerous types of data and state of the art cartographic digital representations become vital. \ nYears have passed and the FOSS4G observatory increased\, following the va st and fast expansion of the FOSS4G ecosystem\, documenting almost 600 ope n source projects and providing the international community (not only the geospatial one) a service that would allow a better\, clearer understandin g of the open source software available for a specific task\, its licenses \, standard compliances\, dependencies\, allowing objective comparisons ba sed on git-related information\, and more. \nToday\, our world is quite di fferent than the one a decade ago. Challenges\, of all kinds have signific antly increased\, but so did the potential of tools and data to answer the m. \nIn this talk\, the presenter will walk you through the vastness of th e FOSS4G ecosystem\, seen though the objective view of the Observatory\, d escribing the various indicators and providing a potential answer on why a nd how the open source model has contributed to the development of geospat ial technologies underpinning major European initiatives\, such as INSPIRE or the Copernicus Program. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Charting the Geospatial Commons: a decade of the FOSS4G Observatory — Codrina Ilie URL:https://talks.osgeo.org/foss4g-europe-2026/talk/LS7QCJ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-91e84df7-6046-517a-b71b-bc8d089cb8ad@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T120000 DTEND;TZID="+03:00":20260630T123000 DESCRIPTION:The subdivision control check (udstykningskontrol\, UKS) is the process of verifying that a land subdivision complies with planning and l and-use regulations. In Denmark\, chartered land surveyors are legally obl igated to complete this check for every cadastral case submitted to the Da nish Geodata Agency (Geodatastyrelsen). The UKS requires the surveyor to m anually gather data from 11 different legal themes\, ranging from protecte d nature areas and coastal protection lines to soil contamination\, road b uilding lines\, and local plans (resulting in querying 17 different geospa tial data themes)\, before verifying whether a proposed cadastral change i s legally permissible. Each theme is governed by its own sector legislatio n\, and the surveyor must cross-reference open government datasets from mu ltiple national portals including data themes such as nature\, environment al\, planning\, cadastral\, coastal zones\, heritage sites\, agricultural etc. In current practice this process is time-consuming\, fragmented\, and prone to human error [Hosseini et al.\, 2025b]\, yet it remains a mandato ry prerequisite before any cadastral case can be registered.\n\nResearch Q uestion\nThis paper presents a web-based\, AI-enabled PostGIS engine that automates the UKS workflow. The system accepts WFS links\, performs dynami c geospatial analysis\, and structures its output specifically to enable a generative AI model to interpret the geographic properties of each GIS an alysis. The central research question is: how can AI be utilised as a tool to streamline the subdivision control check\, and to what degree can a lo cally hosted\, open-source LLM produce legally grounded\, evidence-based a nswers when provided with deterministic geospatial results as context? Not ably\, while the cadastral use case drives the design\, the core contribut ion is a generalisable architecture: the combination of WFS ingestion\, Po stGIS analysis\, and AI interpretation can be applied to any regulatory co mpliance workflow where spatial evidence must be matched against legal req uirements.\n\nSystem Architecture and Open-Source Stack\nThe system is bui lt entirely on free and open-source components. The web application is dev eloped in Next.js\, which exposes the APIs that connect the user interface to the geospatial and AI backend. The data layer is managed through Supab ase\, which provides three databases built on PostgreSQL: a primary databa se storing case information and parcel geometries\; a results database hol ding PostGIS outputs in structured JSON\; a vector database for the CAG em beddings.\nAt the analytical core is PostGIS\, which performs all 17 geosp atial analyses deterministically against the parcel geometry retrieved fro m the Danish cadastral register. The system accepts WFS endpoints\, reads GetFeature responses\, and constructs a bounding box envelope around the s elected parcel. This envelope is used to query each WFS service\, and the returned features are parsed and stored. Spatial operations include within -polygon tests\, line intersections and distance calculations. The outputs are structured to serve as precise inputs for the AI interpretation phase \, since the quality of the LLM response is only as good as the spatial ev idence it receives.\nFor natural language interpretation\, the system uses Ollama\, an open-source platform for running LLMs locally\, serving the M eta Llama 3.1 8B model [Ollama\, u.d.a]. The relevant legal texts are embe dded using the Nomic-embed-text model and stored in the vector database. T his constitutes a Cache-Augmented Generation (CAG) architecture [Chan et a l.\, 2025]: rather than expecting the model to recall Danish land law from its training data\, the system caches the legislation and injects it as c ontext at inference time. This constrains the model to a closed legal know ledge space\, which reduces the risk of hallucination.\n\nPipeline Phases and Case Demonstration\nThe processing pipeline consists of four phases. P hase 1 accepts a parcel identifier via the web interface\, retrieves the c adastral geometry\, and initialises the case. Phase 2 runs the orchestrato r\, which queries all WFS endpoints in parallel and populates the database . Phase 3 executes the PostGIS analyses\, producing a structured result re cord per theme with a preliminary decision flag\, spatial evidence\, and a n agent log. Phase 4 passes these results alongside the embedded legislati ve context to the LLM\, which produces a completed draft of the UKS form. The paper includes a case-oriented walkthrough demonstrating the system on a real cadastral parcel\, showing the analysis outputs for each of the 17 themes and the corresponding AI-generated interpretations. Crucially\, th e geospatial results are themselves meaningful and verifiable independentl y of the AI layer: in many themes\, the spatial finding is already the ans wer\, and the AI provides the legal framing and documentation around it.\n \nResults\nThe system was evaluated against real cadastral cases and the g enerated UKS drafts were compared to manually prepared versions. The PostG IS layer correctly identified overlaps and distances across all 17 themes. The LLM layer produced coherent\, legislation-referenced responses in the majority of test cases\, with output quality closely tied to the specific ity of the spatial evidence provided. Beyond the cadastral domain\, the ar chitecture is directly applicable to other land-use compliance workflows w here spatial data must be checked against regulatory thresholds. Obvious e xamples include wind turbine siting (setback distances to dwellings and na ture areas)\, solar farm permitting\, and environmental impact screening.\ n\nRelevance for FOSS4G\nAll geospatial data originates from Danish nation al open data infrastructures operating under INSPIRE-compliant WFS standar ds. The full stack\, Next.js\, PostGIS\, Supabase\, Ollama\, Llama 3.1\, a nd Nomic-embed-text\, is open source. The architecture is generalisable to any jurisdiction exposing land-restriction data through WFS services. The system code and data schema will be made publicly available under an open -source licence and available on GitHub. The study contributes to a broade r discussion on responsible LLM integration into professional legal-techni cal workflows [Hosseini et al.\, 2025a]\, specifically the role of determi nistic spatial evidence as a grounding mechanism that makes AI output trac eable and verifiable.\n\nConclusion\nThe presented system demonstrates tha t a web-based open-source GIS and LLM pipeline can automate complex\, legi slation-bound cadastral workflows in a robust and practically useful way. Human oversight is preserved throughout\, as the surveyor reviews and appr oves all outputs. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Automating the Subdivision Control Check: An Open-Source GIS and LL M Pipeline for Cadastral Case Preparation — Lasse Hedegaard Hansen\, Nic klas Nordhaug URL:https://talks.osgeo.org/foss4g-europe-2026/talk/RKPEN9/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-ed1c4571-19b8-5a8d-83f6-1d69de46b907@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T123000 DTEND;TZID="+03:00":20260630T130000 DESCRIPTION:There's a lot of data out there that is mapped in HEALPix forma t\, like the ERA5 global climate and weather data. And while DGGS formats are nothing new\, visualizing them has traditionally required desktop tool s and offline workflows.\n\nTaking advantage of the latest web technologie s (namely deck.gl) we decided to explore this uncharted territory and buil d an interactive HEALPix viewer that runs entirely in the browser. This op ens the door to craft unique and engaging experiences for exploring HEALPi x data and perform analysis. Visualizing temporal data can become as simpl e as hitting a play button\, allowing users to discover and study patterns previously only accessible to sophisticated tools.\n\nIn this talk I'll s hare our journey into bringing HEALPix to the web while showing the potent ial this new technology has to change how HEALPix data is accessed and exp lored. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Tiling the Earth: Interactive HEALPix in the Browser — Daniel da Silva URL:https://talks.osgeo.org/foss4g-europe-2026/talk/9XMLKP/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-f6f8ca7c-9058-57c6-bc59-7077957b1225@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T123000 DTEND;TZID="+03:00":20260630T130000 DESCRIPTION:The European Space Agency (ESA) has adopted a variety of open-s ource software tools to manage\, visualize\, and distribute planetary data \, with a particular emphasis on Mars. These tools are essential for both internal operations and for providing crucial data access to the global sc ientific community. Below\, we detail the use of these technologies\, coll aboration on open-source projects\, and the underlying GIS architecture de veloped by the Planetary Science Archive (PSA). [Link](https://psa.esa.int /psa)\n\n## Tools Used\n\n1. **OpenLayers**:\n - **Functionality**: A Ja vaScript library for creating interactive maps in web browsers.\n - **Ap plication**: Used to build web user interfaces that allow scientists to vi sualize geospatial data of Mars and other planets\, offering an intuitive and accessible platform for the exploration and analysis of planetary data .\n\n2. **GeoServer**:\n - **Functionality**: An open-source map server that enables the sharing and editing of geospatial data.\n - **Applicati on**: Used to serve spatial data via standard protocols like WMS (Web Map Service). This facilitates the visualization of footprints with different base maps.\n\n3. **Three.js**:\n - **Functionality**: A JavaScript libra ry for creating 3D graphics in web browsers.\n - **Application**: It is employed to generate three-dimensional visualizations of the Rosetta comet .\n\n4. **PostgreSQL and PostGIS**:\n - **Functionality**: PostgreSQL is an open-source relational database management system\, and PostGIS is an extension that adds support for geographic objects.\n - **Application**: Are used to store and manage complex geospatial data. PostGIS allows for advanced spatial queries\, facilitating the analysis of large volumes of g eospatial data and its integration with other GIS tools like GeoServer.\n\ n## Collaborative Projects and Data Access\n\n1. **Astroquery**:\n - **D escription**: A Python library that facilitates access to online astronomi cal databases.\n - **Collaboration**: ESA contributes to Astroquery to e nsure that planetary data is easily accessible to researchers. This includ es data from planetary exploration missions and astronomical observations\ , integrating these data into scientific analyses efficiently.\n\n2. **Ant imeridian**:\n - **Description**: Tool for processing spatial data cross ing the antimeridian (the 180° line of longitude)..\n - **Collaboration **: Open Source project\, and the PSA plans to collaborate with the projec t by contributing code. This tool is crucial for planetary data where coor dinates can be extended beyond the traditional range of 0° to 180° longi tude\, allowing for continuous and accurate representation of planetary ma ps..\n\n## New Interface and GIS Architecture\n\nESA has developed a new i nterface for the Planetary Science Archive\, integrating the aforementione d tools into a cohesive and user-friendly platform. This interface allows scientists to:\n- **Explore Interactive Data**: Navigate through interacti ve maps of Mars\, Phobos and other planets\, applying filters and visualiz ing different layers of geospatial data. Users can overlay geological\, to pographical\, and spectral data layers to gain a more comprehensive view o f the terrain and use the different functionalities\, such as changing the projection (polar\, equirectangular)\, extracting information by region o f interest.\n- **3D Visualization**: Thanks to Three.js\, users can explor e the the 67P(Churyumov-Gerasimenko) comet in 3D for the Rosetta mission\, rotate\, and zoom into features for more detailed analysis. Ultimately\, we use Three.js to represent irregular bodies such as comets\, asteroids\, and asteroids.\n- **Real-Time Data Access**: Researchers can access the l atest information and perform real-time queries to obtain specific data ac cording to their needs.\n- **Data Download**: Scientists can download data sets directly from the interface for use in their own analyses and studies \, selecting and downloading specific subsets of data based on defined sea rch criteria.\n\n## GIS Architecture\n\nThe GIS architecture behind this n ew interface relies on a robust combination of open-source technologies:\n - **GeoServer Base Maps**: Acts as the distributor of base maps of Mars\, Phobos\, Cassis. They are cached using GWC to optimize access in all avail able projections.\n- **Frontend with OpenLayers and Three.js**: Provides 2 D and 3D visualization capabilities\, offering a rich and interactive user experience. OpenLayers is used for 2D interactive map visualization\, whi le Three.js is employed to generate three-dimensional visualizations of pl anetary surfaces.\n- **Database with PostgreSQL and PostGIS**: Used to sto re and manage complex geospatial data. PostgreSQL and PostGIS enable advan ced spatial queries\, facilitating the analysis of large volumes of geospa tial data and its integration with other GIS tools.\n- **Integration with Data Access Tools**: Projects like Astroquery and Antimeridian are integra ted to facilitate the access and manipulation of specific data\, solving c omplex issues like the management of data crossing the antimeridian. This integration allows scientists to access and analyze planetary data more ef ficiently and accurately.\n\n## Benefits for the Scientific Community\n\nT he use of advanced technologies and a robust GIS architecture developed by ESA offers several significant benefits for planetary research:\n- **Open and Transparent Access**: Although the code is not public\, ESA uses open -source tools that ensure data and resources are available to the entire s cientific community. This promotes collaboration and knowledge sharing\, a llowing researchers to access information without restrictions and work to gether more efficiently. Another benefit for the scientific community is t o be able to cross different instruments/missions in a single interface\, e.g.\, give me all the CaSSIS and HRSC data of this particular crater. For more information about ESA projects\, you can visit their [GitHub reposit ory](https://github.com/esa).\n- **Solutions to Specific Problems**: Tools like Antimeridian [Antimeridian GitHub](https://github.com/gadomski/antim eridian) address unique technical challenges\, ensuring precise and contin uous representation of planetary data. This facilitates the analysis and i nterpretation of geospatial data\, ensuring that visualizations and maps a re accurate and reliable.\n\n## Conclusion\n\nThe adoption of open-source software and the development of an advanced GIS architecture enable ESA to offer a powerful and accessible platform for planetary research. This ben efits not only its own scientists but also the global scientific community \, promoting knowledge sharing and collaboration in the exploration of the Solar System. Tools such as OpenLayers\, GeoServer\, Three.js\, PostgreSQ L\, and PostGIS\, along with collaborative projects like Astroquery and An timeridian\, are fundamental for the efficient management and precise visu alization of planetary data.\n\nWith all this\, the summary of the talk is to show how free software is used in the PSA for planetary data and more specifically in Mars data. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Use of Open Source Software in the ESA Planetary Science Archive — Fran Raga URL:https://talks.osgeo.org/foss4g-europe-2026/talk/KJ3MWT/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-50ba9e90-0b50-5455-9258-744eb9a47aaf@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T123000 DTEND;TZID="+03:00":20260630T130000 DESCRIPTION:The Géoplateforme is the new national infrastructure for geogr aphic data in France\, designed to offer administrations a unified\, scala ble\, and sovereign environment for storing\, distributing\, and visualisi ng geospatial information. It provides a full suite of mutualized services —from secure hosting and high‑performance data distribution to ready ‑to‑use visualization tools—that allow public bodies to focus on the ir missions rather than on infrastructure. On top of these core capabiliti es\, the platform also delivers reference geocoding and reverse‑geocodin g\, altimetry services\, and route and itinerary computation\, making it a comprehensive ecosystem for producing and consuming geodata at national s cale. This infrastructure guarantees sovereign and secure access to geogra phical data and maps without relying on Gafam services. \n\nTo build this platform\, we relied heavily on open‑source technologies\, combining ma ture\, community‑driven components with tools specifically developed at IGN to meet national requirements. \n\nFinally\, we are committed to open ‑sourcing the code behind our infrastructure and progressively sharing t he building blocks that power the Géoplateforme and cartes.gouv.fr. Our s trategy is not only to publish code\, but to build a real community around it\, inviting administrations\, researchers\, companies\, and contributor s to shape its evolution. By opening the doors to collaborative developmen t\, we aim to create a sustainable and transparent geospatial commons for France—one that grows through shared expertise\, pooled investment\, and a collective ambition to strengthen national geodata services through ope n innovation. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Powering France’s Maps: The Open Tech Behind Géoplateforme & car tes.gouv.fr — lavenant\, Rémi Ferrier URL:https://talks.osgeo.org/foss4g-europe-2026/talk/VKNKM3/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-cf5c703c-af15-5dcb-be5f-b4ed88865076@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T123000 DTEND;TZID="+03:00":20260630T123500 DESCRIPTION:Temporal and spatial monitoring of geomorphic features associat ed with natural hazards are important for disaster prevention\, helping to identify vulnerable areas and anticipate potential risks. Remote sensing data has become a cornerstone for natural hazard monitoring\, allowing reg ular mapping of remote areas and larger regions with reduced time and cost s. The unprecedented and continuously growing volume of Earth Observation (EO) data has prompted the use of EO data cubes (EODCs) for efficient stor age\, management\, and analysis (Sudmanns et al.\, 2023). EODCs are mostly focused on raster and array structures due to the gridded nature of EO da ta. However\, previous work (Abad et al 2022) has shown how raster data cu bes are limited by their gridded representation in geomorphic feature dete ction. \nWhile pixel-level analysis is valuable for long time series EO da tasets\, it often disregards the spatial information (Sudmanns et al.\, 20 20) essential for geomorphic feature analysis\, treating pixels in isolati on rather than as meaningful objects. Segmenting pixels into objects\, or object-based image analysis (OBIA)\, is an established concept that allows better representation of natural phenomena with diverse characteristics a nd appearances\, such as different types of glacial lakes\, landslides\, o r lava flows (Hölbling\, 2022). Individual geomorphic features are treate d as aggregates of pixels and are grouped into objects\, providing additio nal information on topological relations.\nAdvances in object detection an d image segmentation have opened new opportunities for tracking evolving f eatures over time. Segmented results can be represented as a time series o f evolving vectors within EODCs\, taking advantage of vector data cube inf rastructure. Vector data cubes work well with stationary objects\, but the varying extent and shape of geomorphic features pose a challenge for exis ting data cube structures. Abad et al. (2024) addressed this by introducin g summary geometries to define a constant spatial dimension while storing changing geometries as data cube elements\, assigning each feature a uniqu e ID based on the centroid of the union and dissolve of all corresponding polygons over time. While effective\, this approach only accounted for spa tial extent\, leaving open how to handle other potential spatiotemporal dy namics\, such as merging\, splitting\, disappearing\, or reappearing. The method may face difficulties in such cases where feature grouping may diff er according to interpretations. For example\, when two nearby glacial lak es expand over time and merge\, should they be considered as one lake befo re they merge? Or if a lake dries out and a new one appears over time\, sh ould both lakes have their own unique ID? In the case of several shape-evo lving features\, whether of the same type (e.g.\, glacial lakes)\, or diff erent (e.g.\, landslides and landslide-dammed lakes)\, such questions beco me important when quantifying geomorphological dynamics. In this study we aim to investigate the implementation of grouping algorithms with features experiencing different spatiotemporal dynamics. \nTo investigate diffe rent grouping algorithms\, we first built a vector data cube with a spatio temporal polygon dataset of a geomorphic feature. As study area\, we selec ted the glacial lakes at the southern margin of the Vatnajökull ice cap i n southeast Iceland\, particularly Jökulsárlón\, Breiðárlón\, and Fj allsárlón\, due to the lake’s constant evolution. We acquired Landsat 4-8 data from 1985 to 2015 and Sentinel-2 data from 2016 to 2025 from Open EO and Google Earth Engine. Annual summer composites were created to minim ise ice cover and fill gaps caused by frequent cloud cover\, proximity to satellite scene edges (Sentinel-2)\, and stripe errors (Landsat-7)\, which partly influenced mapping accuracy\, though exact lake delineation was no t essential for this study. The OBIA classification used spectral indices and k-means segmentation to map annual lake extents. The annual glacial la ke polygons were used to build a vector data cube based on the notebook by Abad et al (2024). Different feature grouping methods were investigated\, including the spatial overlap or proximity within a threshold over time\, the centroid and the bounding box of the union and dissolve operation of all polygons over time\, as well as a representative point of a feature se t.\nAn advantage of the vector data cube over raster representations is th e ability to attach attribute information (such as lake area) to individua l geometries\, making it easier to visualise and query the temporal dynami cs. Results highlighted the importance of feature grouping selection\, as different approaches can lead to meaningfully different interpretations of lake evolution. Some methods treated lakes that would later merge as a si ngle waterbody from the beginning\, producing a smooth\, continuous growth curve. Others assigned separate IDs until the moment of merging\, resulti ng in an abrupt jump in area for one lake as it absorbed the other. The la tter approach\, however\, is more logically consistent. For example\, smal l lakes currently forming above Breiðárlón are clearly distinct feature s today\, regardless of whether they will eventually merge with the larger lake. Treating them as one lake at their current state would be unreasona ble.\nHowever\, when dealing with larger datasets\, we might face difficul ties with the number of geometries and scalability. When lakes merge\, the other unique ID is still present in the data cube with empty geometries. In a large dataset\, handling such lack of data could become an issue as h ighlighted by Abad et al (2024). The scalability issue requires further ex ploration in the future. Inconsistent segmentation was another limitation\ , especially in the 1990s and early 2000s. This prevented reliable detecti on of disappearing and reappearing lakes\, as the algorithm would have ass igned new IDs to the same lake over time. Temporally consistent input data is therefore a prerequisite for accurately capturing the full range of ge omorphic dynamics.\nOur work directly addresses the gap of how to structur e and analyse evolving vector features over time within data cubes in open -source geospatial workflows. The methods were built on open-source tools (OpenEO\, Python) and data (Sentinel and Landsat) when possible and extend s on previous work of the community making our work relevant to the FOSS4G conference. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Representing spatiotemporal dynamics of glacial lakes with vector d ata cubes — Julia Engblom URL:https://talks.osgeo.org/foss4g-europe-2026/talk/BLRKM9/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-1cf617db-14b2-5c13-abc2-9a1a7c622539@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T123500 DTEND;TZID="+03:00":20260630T124000 DESCRIPTION:The increasing availability of geospatial data and the growing maturity of open-source technologies have created new opportunities for ad dressing complex challenges across domains such as maritime surveillance a nd urban mobility. However\, despite significant progress\, the geospatial community continues to face limitations in accessing high-quality\, inter operable\, multimodal\, and semantically enriched open datasets. This work addresses this gap by presenting four open-access geospatial datasets dev eloped within a unified vision of openness\, interoperability\, and reprod ucibility: two datasets targeting vessel monitoring and two focusing on ur ban mobility. These datasets are part of the MUltiSensor Inferred Trajecto ries (MUSIT) project\, an international\, interdisciplinary initiative fun ded by the European Union's Horizon Europe program. MUSIT aims to transfor m heterogeneous tracking sensor data into complete\, semantically enriched trajectories\, opening new perspectives in mobility monitoring and foster ing collaboration among academia\, industry\, and innovators.\nThe first d ataset\, namely Multimodal Maritime Dataset on the English Channel [1] (MM DEC)\, provides a comprehensive multi-source view of maritime activity wit hin a defined Area of Interest covering the western Celtic Sea\, the Engli sh Channel\, and part of the North Sea. Spanning a three-month period from July to October 2023\, MMDEC integrates heterogeneous data streams includ ing Automatic Identification System (AIS) signals\, satellite imagery\, me teorological and oceanographic data\, port locations\, and marine protecte d areas. By combining these diverse sources into a single\, harmonized dat aset\, MMDEC enables advanced analysis of maritime behavior\, anomaly dete ction\, and environmental monitoring. Its multi-layered structure reflects real-world operational complexity and supports a wide range of use cases\ , from maritime safety to ecological impact assessment. Within the MUSIT f ramework\, MMDEC represents a concrete realization of the project's data c ollection and integration pillar\, contributing a rich\, multi-sensor foun dation for subsequent trajectory reconstruction and analysis.\nComplementi ng this dataset\, AegeaNET [2] introduces a real-time dimension to maritim e monitoring through an open sensor network deployed across the Aegean Sea . AegeaNET comprises strategically positioned AIS and ADS-B receivers that capture maritime traffic\, providing continuous streams of positioning da ta to facilitate real-time tracking and situational awareness. As an acade mic and open initiative\, AegeaNET exemplifies how distributed\, community -driven sensor networks can enhance transparency and data availability in critical domains such as navigation safety and border monitoring. In align ment with MUSIT's core vision\, AegeaNET directly addresses the challenge of incomplete or fragmented tracking data by offering persistent\, sensor- based observations that feed trajectory inference and fusion pipelines. To gether\, MMDEC and AegeaNET demonstrate complementary approaches to mariti me data collection: one focused on multi-source historical integration\, a nd the other on real-time\, sensor-based observation.\nIn the domain of ur ban mobility\, we present two semantically enriched trajectory datasets ge nerated for the metropolitan areas of Paris and New York City [3]. The raw trajectory data underpinning both datasets consists of publicly available GPS traces voluntarily shared by users through OpenStreetMap\, retrieved via the OSM API over geographic bounding boxes covering each city. This ch oice of source ensures full openness and compliance with the Open Database License\, while avoiding the privacy issues that typically hinder the rel ease of mobility data. These trajectories are then semantically enriched w ith multiple contextual layers drawn from heterogeneous open sources. Spat ial context is provided through Points of Interest\, also extracted from O SM\, while weather conditions are integrated from meteorological data serv ices. Additional inferred attributes - including detected stops\, movement segments\, and transportation modes - are derived through spatio-temporal analysis of the raw GPS signal. A particularly novel contribution is the inclusion of synthetic yet realistic social media posts\, generated by a L arge Language Model carefully instructed to simulate user-generated conten t associated with observed movements. This multimodal enrichment opens new possibilities for research at the intersection of mobility analysis and n atural language processing. Consistent with MUSIT's emphasis on cross-doma in representation and information fusion\, the datasets are released in bo th tabular and Resource Description Framework formats\, supporting semanti c reasoning\, knowledge graph construction\, and compliance with the FAIR (Findable\, Accessible\, Interoperable\, Reusable) data principles. Togeth er\, these design choices make the datasets valuable resources for a wide range of tasks\, including behavior modeling\, mobility prediction\, and L LM-based applications.\nA key contribution of this work lies not only in t he datasets themselves but also in the reproducible and extensible process es used to generate them. By openly sharing both the data and the underlyi ng pipelines\, we aim to empower the community to replicate\, adapt\, and extend our approach to other geographic regions and application domains. T his is particularly important in the context of semantically enriched mobi lity data\, where the combination of heterogeneous contextual information remains a significant barrier to entry for many researchers and practition ers. The MUSIT project\, through its training and mobility programs and it s commitment to open knowledge exchange\, actively encourages reproducibil ity and community-driven engagement.\nFrom a broader perspective\, these f our datasets illustrate the potential of open geospatial data to bridge do main gaps and foster cross-disciplinary innovation. The maritime datasets highlight the importance of integrating heterogeneous environmental and op erational data sources\, while the urban mobility datasets demonstrate how semantic enrichment can unlock insights into human movement patterns. Bot h cases emphasize the role of open standards\, open-source tools\, and col laborative infrastructures in advancing the state of the art - values that are central to MUSIT's mission of building a dynamic community capable of turning research into tangible societal value.\nFinally\, this work align s closely with the principles of the open geospatial ecosystem by promotin g transparency\, accessibility\, and reuse. By contributing these datasets to the community under the MUSIT project\, we seek to support ongoing res earch\, policy-making\, and industry applications\, while also encouraging further contributions and collaborations within and beyond the consortium . DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Advancing Open Geospatial Data: Multi-Source Maritime Monitoring an d Semantically Enriched Urban Mobility Datasets — Jelena Panagiotakou\, Ioannis Kontopoulos URL:https://talks.osgeo.org/foss4g-europe-2026/talk/MX3ZAN/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-fbfbe73a-a720-5001-b8c6-40436c72ec85@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T124000 DTEND;TZID="+03:00":20260630T124500 DESCRIPTION:The integration of WebGIS platforms into energy planning proces ses and territorial governance has become a widely recognized approach at the international level\, owing to the ability of these tools to support c omplex analyses and strategic decision‑making in the fields of sustainab le development. In this context\, spatial analyses are increasingly requir ed to assess renewable energy potentials\, evaluate land‑use and environ mental constraints\, support multi‑energy system modelling and inform st rategic decision‑making. By enhancing data sharing\, accessibility and a ctive engagement of multiple stakeholders\, WebGIS platforms significantly broaden the opportunities for collaborative planning. The distinctive fea tures of these tools - namely spatial and temporal analytical capabilities \, management of large volumes of heterogeneous data and interactive visua lization - make them particularly well suited to supporting complex and mu ltidisciplinary decision‑making processes\, such as those characterizing the governance of the decarbonization process across different administra tive levels. \n\nOver the past decade\, RSE has developed and maintained a broad ecosystem of WebGIS tools and processing services to support energy planning processes in Italy [1]. This ecosystem includes several thematic atlases dedicated to renewable energy resources\, as well as an integrate d national energy atlas to assess energy sources integration in the territ ory and a centralized geospatial database collecting datasets at multiple spatial and temporal resolutions. These platforms have been designed follo wing open data principles and are freely accessible online\, primarily rel ying on free and open-source software geospatial components and standards. Access to data is currently provided through web-based visualization inte rfaces\, standard OGC services\, and\, where possible\, data downloads in common GIS formats. \n\nWhile this approach has proven effective in suppor ting data dissemination and exploratory spatial analysis\, it increasingly shows limitations in responding to evolving user needs. In particular\, p ublic administrations\, researchers and technical users are progressively moving beyond map-centric usage patterns\, requiring more flexible\, progr ammatic and automated access to geospatial energy-related data. Users ofte n need to integrate datasets from multiple sources into custom workflows\, advanced modelling environments\, dashboards or decision-support systems. \n\nFrom a technical perspective\, the current architecture is character ized by a strong emphasis on visualization and bulk data access\, which li mits the effective reuse of open geospatial data in more advanced and auto mated contexts. While users can explore datasets through WebGIS interfaces and\, in some cases\, download them\, more targeted operations\, such as obtaining the value of a dataset at a specific location\, computing an agg regate over an area of interest (AOI) or extracting a time series\, are no t directly supported as machine-accessible services. At the same time\, da ta extraction is currently implemented through multiple heterogeneous port als and ad hoc services\, each with its own interaction model. Users may b e required to browse large catalogs\, generate scripts for local execution or submit requests that are processed asynchronously through separate sys tems. As a result\, even simple analytical needs often require downloading entire datasets and performing local processing\, which disrupts automate d and reproducible workflows\, while fragmentation across ad-hoc data extr action services leads to inconsistent user experiences\, duplicated logic and greater access complexity. Thus\, traditional WebGIS interfaces and vi ew-oriented services alone are no longer sufficient. \n\nOvercoming these limitations requires a rethinking of the existing infrastructure\, shiftin g from a model centered on visualization and bulk downloads to one based o n programmatic\, query‑driven access [2]. \n\nThis contribution presents the conceptual design and early implementation of a centralized and modul ar REST API intended to act as a unified access layer across the entire RS E geospatial data ecosystem. The API is designed to decouple data access a nd analytical capabilities from specific user interfaces\, enabling consis tent and programmatic interaction with geospatial datasets and services. \ n\nThe proposed API addresses the previously detailed limitations by intro ducing a unified\, query-driven access layer that complements existing Web GIS interfaces. Users can issue parameterized requests to retrieve only th e specific information they need\, including point-based queries\, nearest -feature searches\, spatial aggregations\, time series extraction and filt ered data subsets. These requests can be executed both interactively and p rogrammatically\, enabling direct integration into automated workflows\, m odelling pipelines and external applications. \n\nIn addition\, the API ex tends the capabilities of WebGIS clients beyond standard OGC-based interac tions. While WMS and GetFeatureInfo remain available for visualization and basic inspection\, the API enables richer server-side operations triggere d by user interactions\, returning structured results suitable for advance d visualizations such as charts\, indicators and dynamic summaries. \n\nA further key aspect is the integration of existing domain-specific tools an d processing services. Currently exposed as standalone web applications or custom WebGIS components\, these tools are preserved and made accessible through the API as part of a consistent access model. In this configuratio n\, the API acts as an orchestration layer\, routing requests to the appro priate internal service\, harmonizing inputs and outputs and enforcing com mon policies for authentication\, authorization\, and usage control. \n\nO verall\, the API would establish a single\, consistent entry point for que rying\, extracting and processing geospatial data\, shifting the ecosystem to a more flexible\, query-driven model. This transition would significan tly improve the accessibility\, usability\, and interoperability of open g eospatial data\, enabling more efficient\, reproducible and scalable appli cations across a wide range of use cases. Moreover\, by serving as a unifi ed access layer\, the API acts as an encapsulation boundary: it hides inte rnal changes to data structures\, storage systems\, or processing workflow s behind a stable interface\, so client applications can remain unaffected as the system evolves. \n\nWithin the FOSS4G context\, the proposed archi tecture demonstrates how mature open-source geospatial components can be e nhanced with modern API-driven paradigms to support more dynamic and inter operable data ecosystems. In the specific case of the RSE tool ecosystem\, this approach enables the incremental evolution of existing infrastructur es\, preserving consolidated tools while improving data accessibility\, co herence and interoperability both among datasets and with external informa tion systems. Overall\, it represents a practical and transferable example of how open geospatial platforms can increase the value and usability of information assets without requiring disruptive redesigns. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Towards a modular and open API for interoperable energy WebGIS plat forms — Matteo Gobbi Frattini URL:https://talks.osgeo.org/foss4g-europe-2026/talk/UGKGSH/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-bf4f501f-4afe-5509-a7b6-ec6764c10c81@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T124500 DTEND;TZID="+03:00":20260630T125000 DESCRIPTION:Spatially explicit biogas potential assessment requires integra ting land cover dynamics\, agricultural census records\, livestock invento ries\, and municipal waste generation data into a unified analytical frame work. In most national contexts\, each of these dimensions is maintained b y a distinct government agency operating at incompatible spatial resolutio ns\, under divergent update schedules\, and without a shared classificatio n ontology. The result is not data absence but institutional fragmentation \, and fragmentation is a structurally different problem from scarcity: th e data exists\, is publicly available\, and is updated regularly\, but no coordinating infrastructure connects it into an analysis-ready form. This distinction has direct consequences for platform design. A system built to address data scarcity aggregates and estimates\; a system built to addres s institutional fragmentation must integrate\, reconcile\, and make the re conciliation process itself transparent and reproducible.\nPILAR-2b (Plata forma Inteligente de Localização e Aproveitamento de Resíduos para Biog ás e Bioprodutos) is an open-source spatial decision-support platform dev eloped at CP2b/NIPE-Unicamp\, Brazil\, to produce municipally disaggregate d biogas potential estimates for São Paulo State's 645 municipalities thr ough a reproducible pipeline that treats data integration as a primary com putational challenge rather than a preprocessing step. The platform integr ates five heterogeneous government datasets: IBGE agricultural census reco rds\, SNIS municipal waste inventories\, MapBiomas 30-metre land cover ras ters\, ANEEL energy infrastructure layers\, and CETESB environmental licen sing records. These sources present four structurally distinct incompatibi lities: administrative unit definitions differ across agencies\; coordinat e reference systems require transformation to SIRGAS 2000 UTM Zone 22S\; u pdate cycles range from annual to decennial\; and feedstock classification schemes lack a common ontology across sources. The data integration pipel ine resolves each incompatibility through a fully scripted\, version-contr olled transformation chain implemented in Python with GeoPandas\, Shapely\ , and Fiona\, with no manual reconciliation steps at any stage. Every tran sformation from raw institutional input to analysis-ready geospatial layer is traceable\, independently executable\, and documented in a public repo sitory under GPL 3.0.\nThe platform architecture follows a three-tier micr oservices model\, separating presentation\, application logic\, and data p ersistence into independently deployable cloud components. The presentatio n layer is implemented in Next.js 15 with Mapbox GL JS vector tile renderi ng\, enabling simultaneous display of all 645 municipal polygons with sub- second pan-and-zoom response without requiring a client-side GIS installat ion. The application layer is built on FastAPI 0.104.1 with an asynchronou s Python runtime\; NumPy vectorization across all municipalities reduced p er-request computation time from approximately 8.2 seconds with sequential iteration to 0.9 seconds with vectorised batch processing. The persistenc e layer operates on PostgreSQL 15 with PostGIS 3.4\, hosted on Supabase\, with full operational costs ranging from zero to fifty US dollars per mont h\, depending on demand\, a range considered accessible for public sector and academic deployment without proprietary licensing.\nIntegrated feedsto ck inventories enter a correction factor methodology that decomposes theor etical biomass availability into practical mobilisable potential through f our sequential\, feedstock-dependent factors: collection efficiency (FC)\, competing uses (FCo)\, seasonal availability (FS)\, and logistical constr aints (FL). Each factor is independently parameterised per feedstock categ ory across 30 feedstock types in four sectors: agriculture\, industry\, li vestock\, and urban waste. The FC times FCo times FS times FL multiplicati on produces a transparent audit trail from gross theoretical potential to practically actionable municipal estimates\, enabling factor-specific sens itivity analysis that is structurally unavailable in single-factor yield a pproaches\, where corrections are embedded rather than decomposed.\nApplie d to São Paulo State's 645 municipalities\, PILAR-2b quantifies a theoret ical biogas potential of 133.82 million m³ CH4/day from consolidated feed stock inventories\, reduced to 19.69 million m³/day practical mobilisable potential through sequential correction factor application\, representing a 14.7% weighted average retention that encodes binding regulatory and lo gistical constraints directly in the correction structure. Spatial analysi s reveals that 25.1% of municipalities account for 67.0% of the state's pr actical potential\, a four-order-of-magnitude spread across the municipal distribution that confirms that state-level aggregation is analytically in sufficient for infrastructure investment decisions and that municipal-reso lution outputs constitute a structurally distinct planning information pro duct. Cross-validation against the 2025 São Paulo biomethane roadmap (Ins tituto 17\, PSR\, and Amplum Biogás\, published by FIESP) yields a mean a bsolute error of 13.2%\, approaching the 15-20% performance range document ed for the DBFZ Biomass Monitor operating under substantially denser Europ ean data conditions. All primary analytical workflows are complete within sub-3-second response times under 50 concurrent users in production condit ions.\nThe data incompatibility challenges resolved by this pipeline\, inc luding misaligned administrative units\, divergent update cycles\, and abs ent cross-agency classification standards\, recur structurally wherever po licy-relevant energy assessments depend on combining institutionally separ ated government sources. The São Paulo deployment demonstrates that these challenges are tractable within a fully open\, browser-accessible stack a t operational costs within reach of public institutions. PILAR-2b is desig ned for direct replication in any national or subnational context where Ma pBiomas-equivalent land cover data\, agricultural census records\, and mun icipal waste inventories achieve sufficient completeness\, a condition alr eady met across multiple Brazilian states and increasingly across Latin Am erican\, African\, and Southeast Asian contexts where open satellite and c ensus data are advancing faster than institutional coordination. The resul t is not a regional tool but a methodological blueprint: an open geospatia l integration architecture replicable wherever fragmented data governance\ , not technical capacity\, is the binding constraint on evidence-based ene rgy planning. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:PILAR-2b: An Open Geospatial Pipeline for Biogas Potential Assessme nt in Institutionally Fragmented Data Environments — Lucas Nakamura Cere jo URL:https://talks.osgeo.org/foss4g-europe-2026/talk/VJT8JW/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-433afbdf-561d-5971-8e5b-e4446e9b5dc8@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T143000 DTEND;TZID="+03:00":20260630T150000 DESCRIPTION:Europe is undergoing a significant transformation in its policy landscape\, driven by the rapid pace of technological advancements\, incr easing geopolitical pressures\, and growing concerns regarding digital sov ereignty. Concurrently\, the Competitiveness Compass has introduced a simp lification agenda aimed at streamlining the regulatory environment and red ucing the administrative burden on both businesses and public administrati ons. The Data Union Strategy\, adopted in late 2025\, prioritises initiati ves that facilitate data access\, enhance data reuse for artificial intell igence\, and safeguard EU data sovereignty.\nWithin this complex context\, the European Commission has proposed a major revision of the INSPIRE Dire ctive\, which has been in force since 2007\, as part of a broader package of initiatives known as the Environmental Omnibus\, designed to simplify e nvironmental legislation. Over the years\, INSPIRE has established a uniqu e and comprehensive framework for public sector geospatial data sharing in the EU\, serving as a global benchmark for similar Spatial Data Infrastru cture initiatives. The proposed revision\, currently under negotiation wit h the Parliament and Council\, seeks to modernise and streamline the Direc tive\, aligning it with today’s political and technological landscape th at has undergone considerable changes since the Directive's inception two decades ago. This modernisation effort involves simplifying various legal requirements and aligning them with those outlined in the Open Data Direct ive and its Implementing Act on high-value datasets\, which establish an o pen data regime for several public sector datasets\, including geospatial data.\nThe talk will provide a retrospective analysis of INSPIRE's achieve ments and lessons learned to date\, offer a comprehensive overview of the current European policy framework governing geospatial data sharing\, and examine the evolution of INSPIRE\, covering its past\, present\, and futur e developments\, while highlighting specific opportunities for stakeholder s and identifying key challenges that need to be addressed. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:The future of European geospatial data sharing in a new policy land scape — Marco Minghini URL:https://talks.osgeo.org/foss4g-europe-2026/talk/FFVTYV/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-5ca1edfc-fb7b-5a6b-a80d-391849034f63@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T143000 DTEND;TZID="+03:00":20260630T150000 DESCRIPTION:Subsea cable damage accounts for over 80% of insurance claims i n offshore wind\, making cable burial design a critical and high-risk deci sion. Despite this\, traditional 2-dimensional cable burial risk assessmen t (CBRA) methods were largely non-spatial\, relying on spreadsheets\, manu al interpolation\, and expert judgement. These approaches are difficult to reproduce\, error-prone\, and inefficient when route changes occur.\nThis talk presents a fully geospatial CBRA workflow built using PostGIS\, tran sforming a historically linear and manual process into a scalable\, data-d riven pipeline. We demonstrate how Automatic Identification System (AIS) v essel data is processed from raw point observations into tracklines and de nsity rasters\, and how post-construction rerouting scenarios can be model led to estimate shifts in marine traffic patterns.\nThese spatial outputs are integrated with geological ground models and seabed levels to determin e cable burial depth requirements along subsea cable routes. Using core Po stGIS capabilities such as spatial indexing (GiST)\, relational predicates (ST_Intersects) and geometric analysis (e.g. ST_HausdorffDistance)\, we c reate a reproducible workflow that supports rapid iteration as new data be comes available.\nThe approach reduces duplicated effort\, improves consis tency\, and enables more transparent decision-making in a high-cost engine ering context. It has already been applied to multiple offshore wind devel opments\, including the floating offshore wind farm\, Green Volt.\nThe tal k will explore how this workflow extends into 3-dimensional modelling thro ugh voxel generation\, highlighting opportunities for further integration with netCDF outputs and open geospatial ecosystems. Attendees will gain in sight into how PostGIS can be used to modernise risk modelling workflows\, where data availability can be variable. \nWe conclude by addressing that while the analytical pipeline contains as many open source elements as pr acticable\, the results are currently shared using the Esri JavaScript sof tware development kit (SDK) to support wider stakeholder engagement. Both the benefits and remaining challenges in transitioning fully to open-sourc e solutions will be discussed\, with invitation to collaboration on bridgi ng these gaps. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Reducing Subsea Cable Risk with PostGIS: A CBRA Workflow for Offsho re Wind — Hannah Jukes URL:https://talks.osgeo.org/foss4g-europe-2026/talk/RPPKRR/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-c1b310d1-885f-5094-922f-ee29acd74f60@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T143000 DTEND;TZID="+03:00":20260630T150000 DESCRIPTION:This presentation will introduce the attendees to GeoNode's new capabilities. We will provide a summary of the new features added to GeoN ode in the last release together with a glimpse of what we have planned fo r next year and beyond\, straight from the core developers. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:State of GeoNode — Giovanni Allegri\, Mattia Giupponi URL:https://talks.osgeo.org/foss4g-europe-2026/talk/HPFGGP/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-f6316109-9d04-57fb-a60b-fdbdf5e73a45@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T143000 DTEND;TZID="+03:00":20260630T150000 DESCRIPTION:Setting up GeoServer can be deceptively simple. Bringing it int o production—stable\, performant\, and capable of handling real-world tr affic—is a different challenge. This talk distills hands-on lessons from enterprise GeoServer deployments into a practical playbook\, covering the full journey from initial setup to a production-ready service\, including modern cloud-native approaches such as GeoServer Cloud.\n\nWe explore the configuration decisions that matter most in production: selecting output formats to avoid network bottlenecks\, preparing vector and raster data fo r the multi-resolution demands of web GIS\, and tuning SLD styling to bala nce visual quality with rendering performance. We then move to caching str ategies\, demonstrating how to configure GeoWebCache effectively for backg round layers\, and how to identify scenarios where caching can be counterp roductive.\n\nService limits\, the control-flow extension\, and the monito ring extension are presented as key operational tools for maintaining stab ility under real user load—helping identify slow requests\, resource-int ensive clients\, and the services and layers that require closer attention . JVM sizing and container configuration are addressed at a practical leve l\, focusing on actionable guidance rather than theory\, with notes on how these considerations evolve in containerized and cloud-based deployments. \n\nThe session concludes with real-world examples from enterprise deploym ents carried out by the speaker and colleagues at GeoSolutions\, spanning government SDIs\, environmental monitoring platforms\, and large-scale hum anitarian mapping systems. For each scenario\, we highlight the configurat ion choices and tuning strategies that made a measurable difference: which caching approaches were adopted and why\, how service limits were aligned with actual client behavior\, and how load testing validated each improve ment prior to go-live. Attendees will leave with concrete patterns they ca n immediately apply to their own installations. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Lessons from Running GeoServer at Scale — Andrea Aime\, Simone Gi annecchini URL:https://talks.osgeo.org/foss4g-europe-2026/talk/NCJR9L/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-00348d83-acd5-5808-b18b-e6795cf1e3c1@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T143000 DTEND;TZID="+03:00":20260630T150000 DESCRIPTION:Managing water supply networks requires coordinating between in frastructure data\, hydraulic analysis\, and operational records. When GIS data\, hydraulic models\, and maintenance attributes are stored in separa te and different systems without interoperability between them\, it become s difficult to handle a consistent overview of network conditions and oper ations. To address this\, Consortis Geospatial introduces MAPtheYA: an adv anced geospatial platform that bridges these gaps by providing an end-to-e nd solution for unified water network management.\nMAPtheYA\, a name deriv ed from the acronym of the Greek Water Utility Services (DEYA)\, is an onl ine information system for managing water supply networks. It visualizes t he hydraulic network and the technical characteristics of each asset. MAPt heYA provides search capabilities for network elements and allows multiple users to edit the network. Thus\, the utility’s technical staff can sup ervise\, expand\, and modify the hydraulic network.\nThe platform integrat es EPANET hydraulic modeling to allow technical teams to move beyond stati c geometry into simulation. By calculating flows\, pressures\, and tank le vels over time\, MAPtheYA supports complex hypothetical scenarios. The pre sentation will explain how operators can simulate valve closures\, pipe fa ilures\, or changes in pressure zones to assess their impact on their wide r water network. Results are then presented through thematic maps and grap hs for both daily operations and long-term strategic planning. \nThe next set of capabilities planned is for MAPtheYA to manage operational data suc h as the recording of technical inspections\, fault history\, intervention s\, and ongoing construction projects. This will create a traceable digita l record for every component of the infrastructure and allow organizations to have a full view of their network.\nThe platform will offer a full set of RESTful APIs allowing interoperability with existing systems such as S CADA platforms\, enterprise resource planning (ERP) systems\, consumer man agement systems (CMS)\, or IoT devices\, through its open architecture. Th is integration enables managers to access information such as consumption data or sensor alerts directly within the GIS environment\, supporting mor e coordinated monitoring and informed decision-making across the water net work.\nThe current work-in-progress interface will be introduced\, present ing the main workflows and the general direction of the user interface\, w hich can be divided into three pillars. Three main aspects will be explain ed: the editing and expansion of the hydraulic network\, the modeling capa bilities based on EPANET simulation and the monitoring of the hydraulic ne twork’s state using sample data from IoT and hydrometric stations. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:MAPtheYA – A Unified GIS Ecosystem for the Smart Water Network Ma nagement — Stathis Petridis\, Dimosthenis Paradeisis\, Andreas Gkaraveli s URL:https://talks.osgeo.org/foss4g-europe-2026/talk/NLX383/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-7b5ca4e8-4a23-5345-9153-dc824c75aca1@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T143000 DTEND;TZID="+03:00":20260630T150000 DESCRIPTION:Agriculture accounts for approximately 70% of global freshwater withdrawals and remains highly sensitive to climate variability. Therefor e\, timely estimates of agricultural water use are crucial for effective b asin planning\, water-stress diagnostics\, and informed climate adaptation strategies.\n\nIn Colombia\, the National Water Study (Estudio Nacional d el Agua\, ENA) is the official instrument for quantifying water demand acr oss sectors. It relies on an FAO-56 soil–water balance approach that req uires extensive input data and numerous intermediate calculations (IDEAM 2023). Because this method is so operationally demanding\, the ENA is publ ished only once every four years and suffers from a significant reporting lag. For instance\, the ENA 2022 report relies on data from 2020. Conseque ntly\, these estimates are often outdated by the time of publication\, and lack the capacity to capture intra-annual variability driven by phenomena such as El Niño and La Niña.\n\nThis research therefore investigates wh ether freely available satellite data can support the ENA reporting\, enab ling more continuous and timely monitoring. The study evaluates FAO's WaPO R (Water Productivity through Open access to Remotely sensed-derived data) through an open-source\, reproducible framework of publicly available not ebooks. It combines WaPOR's monthly actual evapotranspiration and intercep tion (AETI) and precipitation products with ENA's agro-climatic crop mask to restrict the analysis to agricultural areas and perform pixel-level cal culations of water consumption. \n\nThe resulting blue water volumes and i rrigation water withdrawals were aggregated at the sub-basin level and com pared with official ENA estimates for 2020. Apart from the country-level a nalysis\, the methodology was applied to a specific zoom-in area located w ithin the Magdalena province. This area is characterized by a high dominan ce of banana and oil palm (Cruz 2020)\, which allowed a specific compariso n between WaPOR-derived evapotranspiration values and the expected agricul tural patterns. This selection was based on two main criteria: first\, the area exhibits a relatively homogeneous surface according to the FAO-WaPOR (L3-AETI-M - spatial resolution of 30m) layer which facilitates the spati al analysis and interpretation of results\; however\, it should be noted t hat the Level 2 (L2-AETI-M - spatial resolution of 100m) product will be used for the analysis\, consistent with the methodology applied across the entire national territory. Second\, crop mask data from IDEAM reveal that the region contains a significant proportion of two key permanent crops: oil palm and banana \n\nThe results show a strong spatial agreement (R² = 0.83)\, indicating consistent identification of priority basins\, althoug h WaPOR estimates are approximately 66% of ENA values\, with similar patte rns for irrigation withdrawals. This systematic offset is consistent with the conceptual difference between the two approaches: ENA estimates potent ial crop water demand under optimal conditions using FAO-56 crop coefficie nts\, while WaPOR captures actual evapotranspiration under real field cons traints. This difference becomes evident when analysing seasonal behaviour : in the Caribbean and Magdalena basins\, which concentrate the largest ag ricultural areas\, spatial agreement is notably high during the dry season but drops significantly with the onset of the first rainy season. \n\nThe detailed analyses for the Magdalena area shows that WaPOR-derived evapotr anspiration values are slightly lower than ENA estimates for both banana a nd oil palm\, consistent with the national findings. The seasonal structur e of this disagreement reveals that January is the only month where the re lationship inverts\, with WaPOR marginally exceeding ENA\, a pattern consi stent with dry-season dynamics in which low atmospheric humidity allows Wa POR's energy balance approach to capture relatively high actual ET. From F ebruary onwards\, ENA overtakes WaPOR\, and the gap widens progressively t hrough the wet season transition\, reaching its annual peak in May — pre cisely when the first rainy season is established — and a secondary peak in October\, coinciding with the second rainfall peak over the region. Th is seasonally structured bias confirms that the difference between the two approaches is not a random but a response to Colombia's climate variabili ty.\n\nThe developed framework produces spatial outputs and results using freely available tools and data sources such as the WaPOR data which is provided in near-real-time layers of actual evapotranspiration\, biomass p roduction\, and water productivity at resolutions from 30 m to 300 m globa lly. The potential of these products for agricultural water monitoring is not new — WaPOR has already been applied in other contexts\, such as the assessment of irrigation performance at a sugarcane estate in Mozambique (Chukalla et al. 2022) but its application at a national scale in Colombia for water demand reporting remains largely unexplored. This study aims to contribute to that evidence base in Latin America\, and to motivate furth er exploration of WaPOR's potential in other regions where timely\, low-co st alternatives to conventional water accounting methods are needed. By op enly sharing the methodological framework through accessible notebooks\, t his research actively promotes reproducibility and collaborative science\, which are core tenets of the FOSS4G community. It empowers local water au thorities\, researchers\, and policymakers in data-scarce regions to indep endently verify\, adapt\, and scale the approach to their specific hydrocl imatic contexts. Furthermore\, integrating these Python-based workflows wi th QGIS demonstrates how open-source ecosystems can bridge the gap between complex satellite data and operational water management\, ultimately demo cratizing access to critical climate adaptation tools. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Evaluating the application of FAO-WaPOR data to support Colombia’ s National Water Study on water consumption in the agricultural sector — Laura Agudelo URL:https://talks.osgeo.org/foss4g-europe-2026/talk/QADHQX/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-42c66594-da1d-540d-9b72-2ccc1d0b9f01@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T150000 DTEND;TZID="+03:00":20260630T153000 DESCRIPTION:Across Europe\, open geospatial data is increasingly published through INSPIRE aligned infrastructures\, National Access Points (NAPs)\, and national open data portals. While access has improved significantly\, licensing has become one of the most common sources of friction and risk w hen data is reused across borders\, institutions\, and use cases.\nThis ta lk focuses on practical licensing challenges encountered in real European projects. It examines common pitfalls such as mixing share alike and permi ssive licenses\, using non commercial data in public private or downstream contexts\, and dealing with national constraints related to redistributio n or export control. Particular attention is given to differences in licen sing approaches across INSPIRE datasets and NAPs\, and how these differenc es impact interoperability and reuse.\nRather than legal theory\, the sess ion presents a hands on framework to help practitioners recognize high ris k patterns early and design data workflows that remain compliant as datase ts evolve.\nAudience level: Beginner to intermediate\nKey takeaway: In Eur ope’s open data ecosystem\, licensing is a technical constraint—and sh ould be treated as part of system design\, not an afterthought. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Licenses in the Real World: Avoiding Share Alike\, Non Commercial\, and Export Control Pitfalls in Europe — Octavian Borcan URL:https://talks.osgeo.org/foss4g-europe-2026/talk/N3D8SN/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-3af5a9a0-c1bc-507a-bef4-b5d2cdcf7f24@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T150000 DTEND;TZID="+03:00":20260630T153000 DESCRIPTION:The Province of South Holland manages one of the most densely p acked\, data-rich regions in Europe. Housing pressure\, nitrogen depositio n\, flooding risk\, ageing infrastructure\, biodiversity loss — the ques tions are urgent\, and the data to answer them mostly already exists. It's public\, it's free\, and almost none of it talks to anything else.\nWe bu ilt something to fix that.\nOver the past two years\, we've assembled a sp atial data warehouse for Zuid-Holland: an H3 geo-datacube at resolution 9\ , combining six years of Dutch open datasets — demographics and housing (CBS)\, land use and nature (LGN)\, water quality (IHW/KRW)\, air quality (RIVM)\, ground height (AHN)\, noise exposure\, and accessibility distance s. Every dataset on the same hexagonal grid. Every hexagon its own small s tory about a patch of land.\nThen we gave it a voice.\nA natural-language assistant — built entirely on open source tools — lets policy advisors \, planners\, and analysts ask questions in plain Dutch and get a map back in seconds. No SQL. No data wrangling. No waiting for a colleague who kno ws which table holds what. "Where did nature expand while population shran k between 2018 and 2023?" becomes a map. "Which areas combine flooding ris k with high housing pressure and poor accessibility?" becomes a map. Decis ions that used to take a week of preparation start with a conversation.\nT he stack is fully open: LangGraph for the AI workflow\, DuckDB for query e xecution\, FastAPI for the backend\, Deck.gl and MapLibre GL JS for render ing. The warehouse itself is built on Delta Lake — a living system\, not a static file — designed to grow as new provincial datasets are onboard ed.\nThis talk covers the architecture\, the hard-won lessons (LLM halluci nations hitting production queries is a fun problem to debug)\, and a live demo against the actual provincial data warehouse. We'll show what the he xagons reveal about Zuid-Holland that spreadsheets never could — and wha t it looks like when a province can finally ask itself the right questions .\nAll code is open source. The pattern is replicable. The data is already yours.\nStack: H3 · DuckDB · LangGraph · FastAPI · Deck.gl · PDOK · Delta Lake DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Asking a Province a Question: LLMs\, H3\, and Open Dutch Geodata — Thijs Oosterhuis URL:https://talks.osgeo.org/foss4g-europe-2026/talk/QZN7Q3/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-54710023-3f6b-5ab6-ba70-b2521b37ebc0@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T150000 DTEND;TZID="+03:00":20260630T153000 DESCRIPTION:Panoramic images are a great way for users to explore a locatio n without \nhaving to be there in person. They give a detailed view of the surroundings and can be used for various purposes such as site inspection s and urban planning. \n\nBy leveraging the GIS capabilities of the free a nd open-source VC Map framework and the 3D visualization power of CesiumJS \, we can create an open-source tool that goes beyond simply viewing panor amic images. Our goal is to provide a seamless experience for users to exp lore\, analyze and navigate their 3D\, 2D and panoramic data within a sing le application. \n\nPart of this work included developing a tiled data sp ecification with the goal of minimizing the need for file transfers and bo osting performance. This specification is built on cloud-ready OGC standar ds - Cloud Optimized GeoTIFF (COG) and FlatGeobuf\, allowing an easy creat ion using GDAL. \n\nThe images are rendered directly into the 3D scene\, w hich allows to blend in visualizations of GIS data from the 3D scene. To e nable analytical tools\, such as measurements\, we use additional depth in formation. \n\nWith this development we aim to demonstrate the power of us ing and developing open source tools with open data standards. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:VC Map Panorama: High Resolution Panoramic Images — Ben Kuster URL:https://talks.osgeo.org/foss4g-europe-2026/talk/TJKEE8/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-5b23fd7d-9f8e-5203-8e1f-16c91afacf61@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T150000 DTEND;TZID="+03:00":20260630T153000 DESCRIPTION:The IBERGIS platform integrates the 1D/2D hydrodynamic model of IBER and the SWMM urban drainage model into a single GIS environment insi de QGIS\, enabling an efficient workflow for urban flood analysis. Using a coupled 1D/2D approach\, both the drainage network and the surface runoff are modelled\, with depths\, velocity\, water elevation and extents obtai ned as outputs\, which can be visualised directly from the GIS interface. This integration enables rapid interpretation of critical areas and automa ted post-processing without external tools. These results demonstrate how GIS-based flood modelling can support urban planning and climate adaptatio n decisions. The applied case of Manresa provides a replicable workflow fo r municipalities seeking to enhance urban resilience through spatially int egrated hydraulic modelling. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:GIS Based 1D/2D Flood Modelling with IBERGIS: A Replicable Workflow for Urban Climate Resilience — David Cano URL:https://talks.osgeo.org/foss4g-europe-2026/talk/ZSUR83/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-cde87c00-b43c-5742-9ab6-7672b84cef0f@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T150000 DTEND;TZID="+03:00":20260630T153000 DESCRIPTION:Water-quality monitoring increasingly relies on heterogeneous s ensing systems that combine in situ probes\, automated acquisition pipelin es\, interoperable web services\, and data-driven analysis. Open geospatia l standards such as the OGC SensorThings API [1] were developed to enable interoperable management of observations and metadata from heterogeneous s ensor systems\, while platforms such as istSOS4 [2] show how these princip les can be implemented in open-source environmental monitoring infrastruct ures. At the same time\, recent literature highlights the growing relevanc e of citizen science and IoT-based participatory sensing for water-quality monitoring [3]\, both to expand observation capacity and to strengthen co mmunication and public engagement around environmental data. In parallel\, machine-learning approaches for algal bloom detection and prediction [4] increasingly combine physicochemical measurements with image-based or remo tely sensed observations\, indicating the potential of AI-enabled optical monitoring for aquatic environments. However\, the integration of open sen sor standards\, participatory monitoring\, and future AI-derived optical o bservations within a single geospatial framework remains limited. This con tribution addresses that gap through the following research question: how can an open geospatial infrastructure based on istSOS4 support multimodal and participatory water monitoring today\, while also providing a coherent integration path for future edge AI-derived optical observations? \n\nThe work is developed within the Interreg WINCA4TI project\, Water Interactio ns with Nature\, Climate and Agriculture for Ticino\, which aims to analys e and describe the interactions between water\, economy\, environment\, an d agriculture in the Ticino basin. Within this broader framework\, SUPSI p romotes participatory environmental monitoring initiatives on Lake Lugano\ , combining scientific observation\, local collaboration\, and territorial awareness. The monitoring activity described in this paper is part of thi s effort. Through a collaboration based on citizen science principles\, a local nautical club hosts and helps maintain our sensor infrastructure\, w hile receiving in return water-quality information and analytics through d edicated dashboards \n\nThe current deployment on Lake Lugano consists of a multisensor platform combining conventional aquatic measurements with an optical experimental subsystem. At present\, the system acquires fluorime tric measurements and dissolved oxygen observations\, together with image data collected by an in-house developed three-camera optical device. These sensing components coexist within the same monitoring initiative\, but th ey do not yet operate within a fully unified observation model. The geospa tial backbone of the proposed framework is istSOS4\, which implements the OGC SensorThings API and provides a machine-readable\, discoverable\, and reusable way to organize and expose environmental observations\, metadata\ , and temporal series. Additionally\, within this project\, the current AP I is planned to be extended to support the STAplus standard\, in order to better address citizen science requirements related to data attribution\, storage\, and handling. Within this architecture\, conventional sensors su ch as fluorimeters and dissolved oxygen probes naturally fit the SensorThi ngs observation model. The more challenging issue concerns the optical sub system\, whose outputs differ substantially from scalar probe measurements . \n\nThe methodological choice proposed in this paper is therefore to dis tinguish between raw optical acquisition and published environmental obser vations. Raw imagery is not ingested directly into istSOS4\; image acquisi tion\, storage\, and processing instead remain outside the observation ser vice. Building on this distinction\, the paper proposes that the optical s ubsystem should evolve into an edge AI sensor. In this envisioned configur ation\, images would be processed locally through dedicated computer-visio n pipelines running close to the sensor. These models would transform raw visual input into higher-level variables that can be represented as time-s tamped observations\, such as algal classification\, estimated algal conce ntration\, bloom-related indicators\, anomaly flags\, and associated confi dence scores. Once formalized as observations with explicit timestamps\, o bserved properties\, and provenance\, these outputs could be published thr ough istSOS4 alongside the measurements acquired by conventional probes. \ n\nThe current results of the work are both practical and methodological. First\, the project has produced an operational multisensor deployment on Lake Lugano that already collects conventional water-quality measurements together with optical data from the three-camera system. Second\, the proj ect has led to the definition of an integration framework in which istSOS4 supports current probe-based observations and is designed to accommodate AI-derived optical indicators. \n\nThis contribution is relevant to the FO SS4G Europe Scientific Track because it addresses a concrete environmental -monitoring problem through a geospatial and standards-based approach\; it highlights the role of free and open source geospatial software as an ena bling infrastructure connecting sensors\, metadata\, interoperability\, an d downstream analytics\; and it brings together themes like GeoAI\, remote sensing for water resources management\, participatory monitoring\, and o pen geospatial infrastructures for environmental observation. The original ity of the work lies in defining how AI-derived optical indicators\, rathe r than raw imagery\, can be integrated into an istSOS4-based observation f ramework alongside conventional water-quality measurements within a partic ipatory monitoring setting. The framework shows how a standards-based open -source infrastructure can support current sensor observations while remai ning extensible toward future AI-enabled optical sensing. \n\nReproducibil ity is a key aspect of the framework\, which uses istSOS4 and the SensorTh ings API to support explicit sensor descriptions\, consistent observation structures\, timestamps\, and traceable data access. By separating acquisi tion\, storage\, inference\, feature extraction\, and publication\, the ar chitecture clarifies provenance and supports reusable environmental observ ations. Grounded in the Lake Lugano deployment within WINCA4TI / Interreg and supported by local stakeholders\, the work proposes a generalizable fr amework in which istSOS4 acts as the interoperable layer for conventional and future AI-derived environmental observations. \n\n \n\n(1) Open Geospa tial Consortium\, OGC SensorThings API Standard\, 2025. \n\n(2) M. Cannata \, M. Antonovic\, M. E. Molinari\, and M. Pozzoni\, “istSOS\, a new sens or observation management system: software architecture and a real-case ap plication for flood protection\,” ISPRS Archives\, 2013. \n\n(3) S. Blan co Ramírez\, I. van Meerveld\, and J. Seibert\, “Citizen science approa ches for water quality measurements\,” Science of the Total Environment\ , 2023. \n\n(4) J. Park\, K. Patel\, and W. H. Lee\, “Recent advances in algal bloom detection and prediction technology using machine learning\, ” Science of the Total Environment\, 2024. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Integrating Participatory Water Monitoring and Edge AI Sensing thro ugh istSOS4: A Lake Lugano Case Study — alessandro centazzo URL:https://talks.osgeo.org/foss4g-europe-2026/talk/UY9NQK/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-c5ea384b-dec8-5b1f-a2f6-c4af59c14a73@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T153000 DTEND;TZID="+03:00":20260630T160000 DESCRIPTION:The rise of large language models is reshaping how we interact with information\, and geographic data should be no exception. In this exp loratory talk\, we present IGN’s early work on a Geo‑Context MCP\, a n ew interface designed to make France’s sovereign geodata directly access ible to AI agents. The goal is simple but ambitious: allow intelligent sys tems to query\, understand\, and reason over geographical data and OGC ser vices—just as easily as humans do today. \n\nWe will walk through the fi rst experiments that connect AI agents to WFS endpoints\, structured geogr aphic datasets\, and other key services from the Géoplateforme. By exposi ng geodata through a machine‑native contextual layer\, IGN aims to lower the barrier between spatial information and AI‑driven analysis. We hope this can open the door to new forms of automated geoprocessing\, enriched decision‑making\, and dynamic geospatial exploration. \n\nFinally\, thi s talk invites the community to imagine what comes next. IGN’s initiativ e is intentionally open\, experimental\, and collaborative—an invitation to researchers\, developers\, and public institutions to help prototype t he future of Geo‑AI interaction. How can we make geodata more “intelli gible” to agents ? Which tools\, standards\, or abstractions should we b uild together? This session is a first step toward that shared exploration . DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:“Beyond Maps: Prototyping a Geo‑Context Layer for the AI‑Driv en Future” — lavenant\, Rémi Ferrier URL:https://talks.osgeo.org/foss4g-europe-2026/talk/SM7QL9/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-b61c2a0d-8912-514d-89db-9612300d07ba@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T153000 DTEND;TZID="+03:00":20260630T160000 DESCRIPTION:The amount and the diversity of Earth Observation data and the multiple ways to get it\, make accessibility to the data quite difficult. \nEODAG offers an Open-Source Python or Command Line Interface client that federates and unifies access to cross-providers Earth Observation data. I t offers a solution that simplifies access to heterogeneous data from vari ous providers with different APIs\, through a unique interface based on ST AC. The design and open-source approach of EODAG allow for a balanced ease d extensibility toward other data sources and data types.\n \nEODAG capabi lities can be extended through the following related projects:\n- EODAG-La bextension\, a Jupyterlab extension allowing users to search and browse fo r remote sensed imagery directly from JupyterLab.\n- EODAG-Cube for having direct access to data as Xarray datasets.\n- STAC-FastAPI-EODAG\, EODAG b ackend for stac-fastapi\, which combines the capabilities of EODAG and ST AC FastAPI to provide a powerful\, unified API for accessing Earth observa tion data from various providers.\n \nIn this talk\, we will present the m ain functionalities of EODAG and related projects. We will focus on update s since our previous FOSS4G workshop\, particularly the use of STAC for AP I parameters and results properties. We will also describe the latest feat ures and upcoming developments. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:EODAG - Earth Observation Data Access Gateway — Sylvain Brunato\, Aubin Lambaré URL:https://talks.osgeo.org/foss4g-europe-2026/talk/UV8LCP/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-a02271d0-730e-5b57-8127-691d0286346e@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T153000 DTEND;TZID="+03:00":20260630T160000 DESCRIPTION:For any geospatial platform\, the ability to serve imagery at s cale is the ultimate "stress test." When our team at UP42 began building a production-grade WMTS service\, we quickly realized that moving from a fu nctional setup to a high-performance one requires more than just adding mo re hardware. This talk shares our iterative journey of migrating from a "V anilla" GeoServer architecture to a microservices-based GeoServer Cloud en vironment\, and the systematic load testing that guided every decision alo ng the way.\n\nWe will walk through our "detective-style" approach to perf ormance tuning. Using Apache JMeter to simulate heavy production loads\, w e treated our infrastructure as a series of integration points where bottl enecks could hide. Rather than a smooth transition\, the move to a cloud-n ative architecture revealed a new landscape of challenges that required us to look deeper into the system than we had ever anticipated.\n\nThroughou t our testing phases\, we uncovered a variety of hidden performance killer s\, including:\n- Storage Hurdles: How standard cloud-mount solutions stru ggled with tile-writing workloads and why native cloud storage plugins bec ame essential.\n- Concurrency Caps: The realization that default configura tions for thread limits and traffic control are often too conservative for modern cloud environments.\n- The Proxy Trap: How internal communication between services can become a bottleneck even when individual components a re performing well.\n- Resource Optimization: The relationship between CPU /Memory allocation and the ability to handle parallel tasks like simultane ous seeding and streaming.\n\nThis presentation is a practical guide for a nyone looking to push GeoServer beyond its default limits. We will share o ur "battle map" for isolating bottlenecks\, bypassing load balancers for d iagnostic testing\, and the critical importance of keeping load testing co ntinuous as your architecture evolves.\n\nKey Takeaways\n- The Migration R eality: GeoServer Cloud offers the foundation for horizontal scaling\, but it requires a specialized tuning strategy compared to standalone instance s.\n- Systematic Isolation: Learn how to test individual microservices (GW C\, Gateway\, etc.) in isolation to pinpoint exactly where latency is intr oduced.\n- Visibility Matters: The importance of combining log analysis\, thread dumps\, and performance metrics to solve "silent" performance issue s.\n- End-to-End Testing: Why you must test the full integration path earl y to find bottlenecks that only appear under high concurrency. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Scaling GeoServer: From Vanilla Architecture to Cloud Performance O ptimization — Jan Christian\, Matheus Pinheiro dos Santos URL:https://talks.osgeo.org/foss4g-europe-2026/talk/MLDRHM/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-ca3e8040-5b05-5c1e-97fc-adf9a2620ba3@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T153000 DTEND;TZID="+03:00":20260630T160000 DESCRIPTION:Snowpack plays a fundamental role in alpine and periglacial env ironments\, acting as a key regulator of surface and subsurface processes. Beyond its well-known hydrological importance as a seasonal water reservo ir\, snow exerts a strong control on ground thermal regimes by functioning as an insulating layer that decouples near-surface ground temperatures fr om atmospheric forcing. This insulation effect influences permafrost occur rence\, stability\, and degradation\, particularly in marginal periglacial environments such as those found in the Southern Carpathians. At the same time\, snow cover modulates biological activity by controlling soil tempe rature\, moisture availability\, and the duration of the growing season\, thereby shaping alpine ecosystem dynamics. Accurately characterizing snowp ack properties\, such as depth\, density\, and persistence is therefore es sential for understanding coupled cryospheric\, hydrological\, and ecologi cal processes in mountain regions.\nHowever\, capturing snow variability i n complex terrain remains challenging due to strong spatial heterogeneity driven by topography\, wind redistribution\, and micro-scale surface condi tions. These challenges are further exacerbated in regions such as the Rom anian Carpathians\, where the availability of in situ meteorological obser vations is limited\, particularly at high elevations and in remote alpine environments. The lack of dense and continuous meteorological measurements constrains the direct characterization of snow–climate interactions and limits the applicability of traditional observation-based approaches. Whi le climate reanalysis products provide continuous large-scale atmospheric forcing\, their coarse spatial resolution limits their direct use in mount ainous environments. Conversely\, field observations and high-resolution s urveys\, such as UAV-based measurements\, provide detailed local informati on but are spatially limited and episodic. Bridging these scales requires reproducible workflows that integrate climate data\, physically based mode ling\, and high-resolution observations within a coherent geospatial frame work.\nThis contribution presents an open geospatial workflow for climate- driven snow modeling in alpine terrain\, linking climate downscaling\, phy sically based snowpack simulation\, and UAV-based observations. The workfl ow integrates freely available hourly climate reanalysis data from the Cop ernicus Climate Data Store (ERA5)\, including both single-level and pressu re-level variables\, with topography-aware downscaling using the open-sour ce TopoPyScale tool. Implemented in a reproducible environment using Pytho n and Ubuntu via Windows Subsystem for Linux (WSL)\, the workflow transfor ms coarse-resolution atmospheric forcing (~31 km) into terrain-informed lo cal-scale inputs by incorporating high-resolution digital elevation models (DEMs) and its derived morphometric parameters such as elevation\, slope\ , aspect\, and sky-view factor\, as well as horizon-based radiation correc tions.\nThe downscaled climate forcing is subsequently used to drive snowp ack simulations using the SURFEX–Crocus model developed by Météo-Franc e. While the model is distributed under an open-source license with contro lled access\, it can be readily obtained for research purposes. Within thi s workflow\, SURFEX–Crocus is employed to simulate detailed snowpack evo lution at both point-based locations and clustered terrain representations . The model provides a comprehensive set of snowpack variables\, including snow depth\, snow water equivalent (SWE)\, snow temperature profiles\, de nsity\, stratigraphy\, hardness\, and snow microstructural properties such as grain size and shape. These outputs enable a process-based representat ion of snow accumulation\, metamorphism\, and melt\, offering insights int o both seasonal dynamics and interannual variability.\nTo demonstrate the integration of model outputs with observational data\, UAV-derived snow de pth is used as a high-resolution reference dataset. Repeated UAV surveys c onducted over an alpine site in the Retezat Mountains (Southern Carpathian s) across four winter seasons are processed using open-source photogrammet ric tools\, such as OpenDroneMap\, to generate digital surface models (DSM s) under snow-covered and snow-free conditions. Snow depth is then derived through a DEM of Difference (DoD) approach. The resulting high-resolution snow depth maps are spatially aggregated to match the resolution of the m odel outputs\, enabling direct comparison between simulated and observed s now conditions for selected time periods.\nThis study emphasizes the desig n of a transferable and reproducible workflow that enables the comparison of climate-driven snow simulations with user-collected high-resolution obs ervations. The integration highlights how physically based models capture broad-scale snow dynamics\, while UAV data reveal fine-scale variability a ssociated with terrain-driven redistribution processes that remain unresol ved at the model scale.\nThe presented workflow relies primarily on open d ata and open geospatial tools\, including ERA5 reanalysis\, TopoPyScale\, Python-based processing libraries (GDAL\, rasterio\, xarray\, pandas\, num py\, netcdf4)\, and open photogrammetric solutions. By combining these com ponents within a coherent processing chain\, the approach demonstrates how complex cryospheric analyses can be conducted in a reproducible and adapt able manner. The proposed framework provides a practical pathway for integ rating climate reanalysis\, terrain-aware downscaling\, snow modeling\, an d UAV observations in alpine environments. It can be readily adapted to ot her mountain regions and applications\, supporting improved understanding of snowpack dynamics and their implications for hydrology\, permafrost\, a nd ecosystem processes under changing climatic conditions. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Linking Climate Downscaling and UAV Observations: An Open Workflow for Snow Modeling in Alpine Terrain — Andrei Ioniță URL:https://talks.osgeo.org/foss4g-europe-2026/talk/SJEX8J/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-c0889665-f35e-520d-894f-cd34b8aee286@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T153000 DTEND;TZID="+03:00":20260630T160000 DESCRIPTION:## Motivation\n\nThe proliferation of waste-contaminated areas poses a significant challenge to global ecosystems\, harming wildlife and posing serious risks to human health. Riverine systems are particularly vu lnerable\, as floodplains act as temporary storage for mismanaged plastic and debris. During high-water events\, accumulated waste is transported do wnstream\, further contaminating aquatic environments.\nGovernmental and n on-governmental organizations work extensively to remediate these areas\, but identifying illegal dumpsites along long riverbanks is resource-intens ive and often requires field surveys by vehicle or boat. Efficient\, large -scale monitoring tools are therefore essential. Recent advances in remote sensing and machine learning offer promising solutions. This research aim s to develop an automated system for detecting plastic waste along riverba nks and water surfaces using multispectral satellite imagery.\n\n\n## Key Related Works\n\nThe field of satellite-based waste detection is rapidly e volving. Previous efforts by *Magyar et al. (2023)* laid the foundation fo r this study by employing a Random Forest (RF) model on PlanetScope and Se ntinel-2 imagery.\n\nOther researchers have utilized different sensors and algorithms\; for instance\, *Sakti et al. (2023)* introduced the "Adjuste d Plastic Index" to reduce noise from vegetation and buildings in Sentinel -2 data\, achieving 88% accuracy on vegetation but facing challenges with spectral similarities between buildings and debris.\n*Lanorte et al. (2017 )* demonstrated the effectiveness of Support Vector Machines (SVM) for agr icultural plastic waste detection using Landsat 8 imagery\, achieving over all accuracy up to 94%.\nDeep learning approaches have also been explored. *Sun et al. (2023)* utilized high-resolution satellite imagery (0.3m–1m ) to achieve a 98% detection rate for various waste types\, significantly reducing the time required for expert manual review. *Torres and Fraternal i (2021)* employed a Convolutional Neural Network (CNN) based on the ResNe t50 architecture to identify illegal landfills in 20cm resolution orthopho tos with an F-score of 88.2%.\nWhile these high-resolution studies show gr eat accuracy\, our research focuses on the operational utility of more fre quently available multispectral data like PlanetScope to monitor dynamic r iver environments.\n\n\n## Methodology\n\n### Data Acquisition and Feature Engineering\nThe study utilizes PlanetScope multispectral imagery\, which provides four spectral bands (RGB + NIR). To enhance the model's ability to distinguish waste from natural surfaces\, the following spectral indice s were calculated:\n - **Plastic Index (PI)**: Leverages the higher reflec tance of plastic compared to water in the NIR spectrum.\n - **Normalized D ifference Water Index (NDWI)**: Used to delineate water features.\n - **No rmalized Difference Vegetation Index (NDVI)** and **Reversed NDVI (RNDVI)* *: Used to identify and mask healthy vegetation.\n - **Simple Ratio (SR)** : Further assists in vegetation classification.\n\n### Training Dataset\nA comprehensive training dataset was compiled\, consisting of 27 million pi xels. This dataset includes 29 landfills in Romania — identified via loc al registries — and the Kisköre reservoir in Hungary\, which is a known site for floating waste accumulation. Every pixel was manually annotated into five categories: *Waste*\, *Water*\, *Pasture/Forest*\, *Bare land*\, and *Unknown* (including buildings and roads). To improve accuracy\, high -resolution aerial imagery was used to differentiate between plastic waste and construction debris.\n\n### Model Development and Optimization\nA Ran dom Forest classifier was implemented using the Scikit-Learn library. To m anage the large dataset\, the model was optimized by limiting tree depth t o 20\, reducing the model size from 14GB to a more manageable 2GB without significantly increasing the false positive rate. Furthermore\, because wa ste pixels are vastly outnumbered by other classes\, class weights were ap plied to mitigate the high false-negative rates caused by data imbalance.\ n\n### Advanced Processing Techniques\nSeveral techniques were explored to refine performance:\n - **Principal Component Analysis (PCA)**: Applied t o reduce parameter dimensions and suppress noise. It was found that three principal components retained 90% of the variance.\n - **Seasonal Separati on**: Separate models were trained for *summer* (March–October) and *win ter* (November–February) to account for variations in vegetation cover a nd atmospheric conditions.\n - **Water Masking**: An algorithm was impleme nted to mask areas distant from the river course\, thereby eliminating irr elevant false alarms in urban or agricultural areas.\n\n### Interactive We b Application\nThe results of our research are integrated into an interact ive web application that provides a platform for viewing detected waste lo cations. The application automatically downloads and classifies the latest satellite imagery for monitored areas. The implementation is open-source and is available on GitHub:\nhttps://github.com/GISLab-ELTE/WasteDetection /\n\n## Results and Discussion\n\nThe model was validated using test data from the Drina River\, a site not included in the training set\, featuring both land-based dumpsites and floating waste islands. The primary RF mode l achieved a Match Rate (True Positive) of 29.32% and a Commission Rate (F alse Positive) of 28.13%. While the Omission Rate (False Negative) was hig h (70.67%) — largely because the model only classified the core of waste islands — this was considered acceptable for operational purposes where avoiding false leads for clean-up crews is a priority. The model detects the core regions of waste accumulations while maintaining low false positi ves\, which is critical for operational deployment.\n\nPCA integration not ably improved noise suppression on water surfaces. The PCA-trained model i ncreased the Match Rate to 34.99%\, though at the cost of a higher Commiss ion Rate (39.01%). The summer-specific model showed a slight improvement i n reliability for summer imagery\, reducing the commission rate to 26.1%. Conversely\, winter detection remains a challenge due to shadows and poor weather conditions\, which hinder spectral accuracy.\n\nOur study contribu tes (i) a large annotated dataset\, (ii) an operational RF-based detection pipeline\, and (iii) an evaluation of trade-offs between accuracy and usa bility in riverine waste monitoring. DTSTAMP:20260602T160506Z LOCATION:A14 SUMMARY:Automated Riverine Waste Detection Using Random Forest and Multispe ctral Satellite Imagery — Máté Cserép URL:https://talks.osgeo.org/foss4g-europe-2026/talk/QYAHU8/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-a4dd7860-b8d4-5737-a44f-841163cefc14@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T163000 DTEND;TZID="+03:00":20260630T173000 DESCRIPTION:Stay tuned! More info coming soon! DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Sponsored keynote — Marian Neagul URL:https://talks.osgeo.org/foss4g-europe-2026/talk/TVDJKC/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-cb0f1665-d397-5c94-9843-61855600717f@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260630T173000 DTEND;TZID="+03:00":20260630T180000 DESCRIPTION:In 2025\, the Spanish Supreme Court ruled that source code for a piece of software developed for a Ministry (the BOSCO tool) needed to ha ve its source code released. Nowadays laws are being implemented as comput er code\; and for a democratic society to function as such\, the public ne eds to be able to know both the letter of the law and the source code of t he software used to enforce that law.\n\nThe BOSCO ruling sets an European precedent for algorithmic transparency and digital sovereignty. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:The BOSCO ruling: government software must be explainable — Iván Sánchez Ortega URL:https://talks.osgeo.org/foss4g-europe-2026/talk/XRE39X/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-770660a9-371a-580e-a37a-6337dee0603e@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T090000 DTEND;TZID="+03:00":20260701T100000 DESCRIPTION:When people think of forestry\, they usually picture muddy boot s\, measuring tapes\, and chainsaws—but today’s modern forester is jus t as likely to be found writing Python scripts and querying geospatial dat abases. The forestry sector is currently experiencing a quiet revolution f ueled by an explosion of free and open-source data\, transforming how we m onitor\, measure\, and manage complex woodland ecosystems.\nThis keynote e xplores the transition from traditional\, localized forest inventories to the vast\, open-source data ecosystem now available to researchers and pra ctitioners. We will dive into the wealth of global datasets reshaping fore st management\, including high-resolution canopy height models from Meta a nd other tech giants\, comprehensive datasets from the Horizon Europe PATH FINDER project\, and satellite-derived products for biomass estimation fro m missions like GEDI.\nFocusing on a case study in the diverse and challen ging landscapes of Romania\, we will demonstrate how these massive open-so urce datasets can be fused with local forest management data to create a c omprehensive understanding of forest structure and health. We will explore the practical realities of integrating varied data sources—bridging the gap between global satellite observations and ground-level realities—to support sustainable forest management under climate change scenarios. Ult imately\, this talk will prove that digital twinning in forestry is no lon ger just a buzzword\, but an accessible reality powered by the global open -source community. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Out of the Woods and Into the Code: The Rise of the Open-Source For ester — Mihai Daniel Niță URL:https://talks.osgeo.org/foss4g-europe-2026/talk/7GEBHV/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-5367da65-533d-5424-ae37-2ac552b35887@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T100000 DTEND;TZID="+03:00":20260701T103000 DESCRIPTION:The MapLibre community is currently in the midst of developing the MapLibre Tile Format\, a modern\, open\, and fully community-governed successor to the ubiquitus MVT format. While MVT has served the mapping ec osystem well for over a decade\, it also carries historical constraints th at limit interoperability\, formal specification quality\, extensibility\, and independence from proprietary platforms. As MapLibre continues to gro w as the central open-source foundation for web-based map rendering\, it h as become increasingly clear that a future-proof\, openly specified\, and collaboratively designed tile format is essential.\n\nThis talk will offer a look into\n- why we initiated this engineering effort and\n- what gaps the new format aims to close.\nI will explain the core design principles b ehind the specification- how properties\, geometries and IDs work\, how we do optional values and such.\nAttendees will gain a technical understandi ng of how the format works\, including its data model\, feature encoding s trategy\, metadata approach\, and how this is compatibse to existing infra structure.\n\nBeyond the current specification draft\, I will outline the major areas still under active development. These include\n- discussions a bout schema evolution\,\n- advanced geometry representations\,\n- compress ion strategies\,\n- and interoperability with raster\, elevation\, 3D and non-geographic datasets.\n\nI will also provide insight into the collabor ative workflow between maintainers\, researchers\, vendors\, and the wider open-source community\, highlighting how this is primarily based on the c ontributions and feedback from untold amounts of volunteers.\n\nFinally\, the talk will cover how the rollout is progressing in practice. This inclu des\n- early tooling support\,\n- reference implementations\,\n- testing f rameworks\, and\n- real-world trials by organizations exploring migration paths away from MVT.\n\nThe session will present an honest\, up-to-date sn apshot of the project’s status and a forward-looking roadmap for the nex t stages of development\, helping the community understand both what is re ady today and what is still on the horizon. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:State of the MapLibre Tile Format — Frank Elsinga URL:https://talks.osgeo.org/foss4g-europe-2026/talk/8D8RU9/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-701b457f-f043-52bf-a497-714905b35797@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T100000 DTEND;TZID="+03:00":20260701T103000 DESCRIPTION:The OSGeo project deegree is server-side open source software f or spatial data infrastructures (SDI) and the geospatial web. It implement s standards of the Open Geospatial Consortium (OGC) and the ISO Technical Committee 211. The project hosts official reference implementations of OGC standards such as OGC API - Features\, WFS\, WMS and GML.\n\nThis talk wi ll give an overview of the latest release 3.6 as well as recent developmen ts of version 3.7 featuring support of Java 21 and Tomcat 11. Additionally \, the deegree implementation of the OGC API - Features standard will be p resented.\n\nLastly\, future directions and planned core developments of t he project will be highlighted. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:deegree - Server-side open source software for the geospatial web — Dirk Stenger URL:https://talks.osgeo.org/foss4g-europe-2026/talk/CSQXBH/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-44f9436e-01ec-54b8-bb47-a7b9fbe85a0d@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T100000 DTEND;TZID="+03:00":20260701T103000 DESCRIPTION:This presentation explores GeoServer’s capabilities for publi shing rich data models\, including complex features with nested properties and multi-valued relationships\, through standard OGC services and OGC AP I - Features. It focuses on recent developments such as the Smart Data Loa der and Feature Templating extensions\, highlighting both current capabili ties and ongoing and planned enhancements within the GeoServer ecosystem.\ n\nGeoServer already provides strong support for implementing view and dow nload services for complex data models through its core architecture and a range of free and open-source extensions. Among these\, App-Schema has lo ng been the primary solution for modeling and exposing complex feature str uctures and enabling advanced vector data services\, despite its steep lea rning curve.\n\nBuilding on these foundations\, newer approaches are emerg ing to simplify and modernize the publication of rich data models. These i nclude direct integration with NoSQL data sources such as MongoDB\, levera ging their native document-oriented structures\, as well as support for mo dern output formats like JSON-LD\, which enables the embedding of explicit semantics alongside the data.\n\nThe session will conclude with real-worl d use cases from organizations that have adopted GeoServer and GeoSolution s solutions\, providing practical insights\, architectural patterns\, and lessons learned to help attendees effectively design and implement scalabl e\, production-ready services for complex data models. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Publishing rich data models in GeoServer with Smart Data Loader and Feature Templating — Andrea Aime\, Nuno Oliveira URL:https://talks.osgeo.org/foss4g-europe-2026/talk/E7GXTY/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-785082d7-58a1-566a-ba4f-eb6722afb19e@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T103000 DTEND;TZID="+03:00":20260701T110000 DESCRIPTION:A default web map takes data in latitude-longitude and displays it in spherical Mercator\, which makes two different coordinate systems. But the internal workings of a mapping library require handling even more coordinate systems internally.\n\nThis talk is a deep technical view into how some web map libraries (Leaflet\, MapLibre\, OpenLayers\, Gleo) handle coordinate systems internally\, and how their different strategies affect performance in specific scenarios. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:How many coordinate systems are in a web map? — Iván Sánchez Or tega URL:https://talks.osgeo.org/foss4g-europe-2026/talk/YRQJZW/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-7d04cd10-438c-5b71-a038-b36b54f5e163@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T103000 DTEND;TZID="+03:00":20260701T110000 DESCRIPTION:QField brings the power of QGIS to the field\, enabling efficie nt data collection based on QGIS projects\, both offline and online. The r elease of QField 4\, new features further improve performance\, usability\ , and flexibility of the application.\n\nTogether with QFieldCloud\, which enables seamless synchronization and collaboration between field and offi ce\, the ecosystem has introduced new exciting functionalities.\n\nIn this talk\, we will explore what’s new in QField 4 and QFieldCloud\, and sho w how they work together to create a smooth\, end-to-end field data workfl ow. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:QField 4 & QFieldCloud - your fieldwork companions — Ivan Ivanov URL:https://talks.osgeo.org/foss4g-europe-2026/talk/898S3H/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-e41f7c3c-be7b-5109-9247-e72fd69f4422@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T103000 DTEND;TZID="+03:00":20260701T110000 DESCRIPTION:Mapbender 5.0 is close to come out and comes with many great ne w features that will be highlighted in this talk. But not only the new fea tures are shown. You will discover what Mapbender offers and why it could be your Geoportal solution.\n\nMapbender is a great open source solutions for creating intuitive and high-performance WebGIS applications. Mapbender offers a set of widgets that you can combine.\n\nThis software solution e nables users to quickly and easily publish applications online without hav ing to write a single line of code.\n\nMapbender improved a lot. With the new version we have a refactored design and many new or improved features. You can integrated WMS Services\, WMTS Services\, OGC API Features Collec tions or Vector Tiles Services and configure them individually. \n\nYou ca n manage access rights for applications.\n\nYou can setup applications wit h search functionality and digitize functionality.\n\nMapbender 5.0 offers new features\n- Batch print functionality\n- Support for OGC API Features \n- Support for styles\n- interactive Help\n- and more DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Mapbender 5.0 - next level solution to create your powerful Geoport al — Astrid Emde URL:https://talks.osgeo.org/foss4g-europe-2026/talk/T3DDW7/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-da4cc833-e020-50c5-8ad4-0c1447069fe1@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T103000 DTEND;TZID="+03:00":20260701T110000 DESCRIPTION:The development is building on the rich ecosystem of European E O Platforms\, as well as on open-source building blocks developed under EO EPCA+. In this talk we will review the EarthCODE initiative\, archictectur e and suite of services offered to the community\, and we will set the sce ne for a community consultation to take place also at FOSS4G Europe. The s cope of the community consultation will be to identify areas for improveme nt with respect to interoperability and cross-platform integrations. The i dentified topics will be addressed in the upcoming EarthCODE hackathon (30 Nov - 04 December 2026). DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:EarthCODE - enabling FAIR Open Earth Science for Earth Action — A nca Anghelea\, Salvatore Pinto URL:https://talks.osgeo.org/foss4g-europe-2026/talk/ZE8ZPT/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-8b2670df-519a-590a-8954-d0437b6f25cf@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T103000 DTEND;TZID="+03:00":20260701T110000 DESCRIPTION:The growing availability of data from drones\, Earth observatio n\, and agricultural machinery (i.e.\, telemetry)\, combined with the adve nt of cloud infrastructure\, has significantly accelerated innovation in h ow farmers and agricultural systems are supported. These advances have dem ocratized access to data and capabilities\, enabling precision farming sol utions at an unprecedented scale.\n\nThis has become one of the main use c ases for GeoServer deployments in recent years. At GeoSolutions\, we have collaborated with a wide range of clients—from NGOs to large private com panies\, from startups to research institutions\, helping them to extract value from data through GeoServer and other open-source geospatial technol ogies deployed at scale in cloud environments.\n\nThis presentation summar izes 10 years of experience in ingesting\, managing\, and disseminating da ta at scale for the precision farming industry. Key topics include:\n\n* O ptimization and organization of raster data\n* Optimization and organizati on of vector data\n* Data modeling for performance and scalability in GeoS erver and PostGIS\n* Deployment guidelines for scaling and performance of GeoServer\n* On-the-fly styling for NDVI and other visualizations\n\nBy th e end of the presentation\, attendees will be able to design and plan GeoS erver deployments to efficiently serve precision farming data at scale. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Supporting precision farming with GeoServer: past experiences and way forward — Andrea Aime\, Simone Giannecchini URL:https://talks.osgeo.org/foss4g-europe-2026/talk/8QDHKS/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-857fb13c-ea41-5f5b-a39f-02dd1211c789@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T113000 DTEND;TZID="+03:00":20260701T120000 DESCRIPTION:How do you visualize decades of high-resolution national climat e projection data — wind speed\, solar radiation\, temperature\, degree days — directly in a web browser\, with smooth rendering and precise dat a picking\, all built on open source tools?\n\nAt Camptocamp\, we tackled this challenge during the Météo France hackathon in Toulouse\, where tea ms were given access to beta climate projection datasets from Météo Fran ce and the DINUM. Our goal: build a web application helping the renewable energy industry assess regional potential under different climate warming scenarios\, aligned with the French government's TRACC adaptation framewor k (+2°C\, +2.7°C\, +4°C milestones).\n\nThe data pipeline — built wit h Python\, GDAL\, Xarray\, and RioXarray — transforms NetCDF climate mod el outputs (CNRM-ALADIN64E1\, ~12 km resolution\, 2014–2100) into monthl y raster tilesets. The challenge then becomes how to render these rasters with maximum expressiveness on a map\, going well beyond what standard ras ter layer support in MapLibre GL JS offers out of the box.\n\nThis is wher e our open source library maplibre-gl-shader-layer comes in. Born from rea l production needs in meteorological data visualization\, this TypeScript/ WebGL library provides the building blocks to create fully custom tiled la yers for MapLibre GL JS\, powered by Three.js under the hood. Developers c an write their own GLSL fragment shaders and hook into per-tile uniform up dates — giving full control over color mapping\, encoding\, blending\, a nd animation.\n\nThe library's flagship component\, MultiChannelSeriesTile dLayer\, is designed specifically for scientific data: it decodes multi-ch annel PNG or WebP tiles where RGB channels encode up to 24-bit precision f loat values (similar to Mapbox Terrain-RGB)\, supports time/depth/scenario series interpolation\, and applies configurable colormaps from a built-in library (viridis\, inferno\, turbo\, and custom descriptions). Nodata han dling via the alpha channel and support for PMTiles archives round out the feature set for production use.\n\nWe will walk through the full open sou rce stack — from raw NetCDF to interactive browser map — and show how maplibre-gl-shader-layer makes it straightforward to build expressive\, pe rformant meteorological visualizations without sacrificing flexibility. De mos will include climate indicator overlays\, a warming scenario slider\, and seasonal navigation — all rendered in WebGL.\n\nThe library is MIT-l icensed\, available on npm\, and actively maintained by the Camptocamp geo blocks team.\n\nRepository: https://github.com/geoblocks/maplibre-gl-shade r-layer DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Rendering National Climate Data in the Browser: WebGL Custom Shader s with MapLibre GL JS — Florent Gravin URL:https://talks.osgeo.org/foss4g-europe-2026/talk/QD9HHC/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-09cae6b2-0f1e-5a5c-8a80-adfda41fb78b@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T113000 DTEND;TZID="+03:00":20260701T120000 DESCRIPTION:Maintaining spatial consistency between different thematic geog raphic datasets and reference layers (such as cadastral parcels or base ma ps) is a persistent challenge in GIS workflows. Manually snapping boundari es to match updated reference data is not only time-consuming and prone to human error but also difficult to reproduce. To address this\, Athumi (Th e Flemish Data Utility Company) & Flanders Heritage Agency developed brdr\ , an open-source Python library\, and its companion QGIS plugin\, brdrQ\, designed to automate and streamline the alignment of geometries to referen ce borders. \n\nBy decoupling the alignment logic (brdr) from the user int erface (brdrQ)\, the project offers flexibility for both developers and GI S analysts. Developers can integrate the alignment engine into automated d ata pipelines\, while analysts can leverage the QGIS plugin for visual val idation and manual fine-tuning. Both ways of working ensure a significant reduction in workload to obtain higher-quality data. \n\nIn this presentat ion\, we will demonstrate the underlying algorithm\, showcase the QGIS int egration\, and discuss real-world use cases where these tools have improve d the efficiency of spatial data management at the Flanders Heritage Agenc y. \n\n### Python library: brdr \n\nAt its core\, brdr is a Python library built to detect and resolve geometric discrepancies through a series of d eterministic spatial calculations. Unlike simple snapping tools\, the brdr -algorithm evaluates candidate reference geometries by calculating relevan t intersections and differences. It uses these metrics to generate alignme nt predictions: the library calculates the most likely intended geometry b ased on geometric stability. This predictive approach allows for a high de gree of confidence in automated workflows\, as ‘brdr’ can distinguish between a deliberate gap and a registration error\, maintaining the overal l structural integrity of the original dataset. \n\n### QGIS plugin: brdrQ \n\nbrdrQ integrates the 'brdr'-library into a user-friendly QGIS-plugin\ , making the 'brdr' logic more accessible through visual GIS-workflows. br drQ offers several tools\, including: \n\n- Feature Aligner: An interactiv e tool for record-by-record inspection\, allowing users to compare "predic tions" (suggested alignments) with a correctness score before committing c hanges. \n- AutoCorrectBorders: A processing algorithm for bulk alignment of datasets. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Pushing the boundaries: Automated Geometry Alignment with 'brdr' an d ‘brdrQ’ — Yanko Godaert URL:https://talks.osgeo.org/foss4g-europe-2026/talk/79DYEL/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-2234bc8e-d4b5-574e-9f9d-5f3cb74c5051@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T113000 DTEND;TZID="+03:00":20260701T120000 DESCRIPTION:The QGIS Web Client (QWC) is a fully-fledged application for pu blishing QGIS projects on the web. It offers both 2D and 3D views.\n\nWith the QGIS Web Client (QWC)\, you can publish your projects on the internet with the same visualisation as QGIS Desktop\, thanks to the QGIS Server. The environment consists of a modern web application written in JavaScript based on ReactJS and OpenLayers\, as well as the qwc-services\, an ecosys tem of server-side Python/Flask microservices that can be used\, for examp le\, to manage user permissions and process geodata within the web applica tion.\n\nThe new 3D view\, developed using THREE.JS and Giro3D\, also offe rs the ability to display and sketch 3D scenes based on 3D tiles\, and is a comprehensive tool for urban planning.\n\nQWC is modular and extensible\ , offering both a standard web application and a development framework. Yo u can easily start with the standard application and then customise your a pplication as required\, depending on your needs and development capabilit ies.\n\nThis talk will give an overview of the QWC’s architecture and in troduce the numerous new features developed over the past year. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:QGIS Web Client - Latest from the project — Sandro Mani URL:https://talks.osgeo.org/foss4g-europe-2026/talk/U7H9TV/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-9567fb06-aa8b-508f-9331-a65e01a011e6@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T113000 DTEND;TZID="+03:00":20260701T120000 DESCRIPTION:IGN (French National Map Agency) and its partners are launching the JUNN project : A dynamic 3D digital replica of the territory with o nline services to interact with (visualization\, immersive navigation\, si mulation). A tool that aims to federate data\, technologies\, communities and existing initiatives to collectively gain efficiency for the ecologica l transition.​ \n\nThis digital twin of France and its territories is a tool-based approach\, supported by a consortium of public and private play ers\, enabling the development of a common Open-Source architecture built in support of identified business usescases. \n\nObjectives are multiples: \n* Reducing the cost of local initiatives and facilitate their replicat ion in other areas\, \n* Establishing a framework for interoperability and interface between different projects \n* Setting up a science platform to facilitate the development of technological advances from R&D\, \n* Build ing an ecosystem of services and business applications with high added val ue \n\nThe project will include 3D data production with 3D mesh data and C ityGML LOD 2.2 data. The 3D meshes will be generated using the Wasure soft ware (https://github.com/lcaraffa/sparkling-wasure)\, which was developed based on research conducted by the Lastig research laboratory. This softwa re will be further refined during the project\, in collaboration with INRI A and GeometryFactory. \n\nSome of the CityGML data will also be produced by the IGN. Initial tests using the Open-Source Roofer software (https://g ithub.com/3DBAG/roofer) have yielded promising results (https://batiment3d .ign.fr/) regarding what the Digital Twin data might look like. \n\nThis p latform is intended to serve as a hub for scientific research\, where it w ill be possible to connect simulators that have access to the platform’s extensive dataset. This will be the case\, for example\, with the ICI pro ject (https://x-ngilet.gitlabpages.inria.fr/html_covici/index.html)\, whic h offers models of epidemic spread and whose access to the data will impro ve predictions \n\nFor visualization\, we will use the open-source renderi ng engine iTowns (https://www.itowns-project.org/)\, to which IGN is a maj or contributor. Already high-performing\, the close collaboration between the Digital Twin team and the iTowns development team will ensure that thi s tool is fully compatible with what we will be offering. \n\nWe are propo sing this presentation to give the OSGeo community an overview of the proj ect. This presentation will introduce the various open-source software com ponents we will be using\, some of which we will be enhancing (Wasure\, iT owns\, Rok4\, Roofer\, etc.). DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:JUNN – a french DigitalTwin initiative — lavenant\, Rémi Ferrier URL:https://talks.osgeo.org/foss4g-europe-2026/talk/JM8S7N/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-6b11ae5a-3927-5dd6-a961-3fc75c9371bb@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T113000 DTEND;TZID="+03:00":20260701T120000 DESCRIPTION:Five years ago\, **Awesome Spectral Indices** (ASI) was launche d to address a persistent gap in Earth observation workflows: while hundre ds of spectral indices existed in the literature\, their definitions were fragmented\, inconsistently documented\, and rarely designed for direct pr ogrammatic use. What began as a curated effort to standardize and consolid ate these definitions has since evolved into shared open geospatial infras tructure.\n\nThe first public release in 2021 included 66 indices structur ed under a common schema with explicit naming\, formulas\, application dom ains\, and bibliographic references. A key design decision was the introdu ction of a cross-sensor band naming standard aligned with widely used sate llite platforms such as Landsat\, Sentinel\, and MODIS. By enabling expres sions like “`(N - R) / (N + R)`” to be both human-readable and machine -executable\, ASI moved from being a static catalogue to a lightweight and interoperable specification.\n\nOver the past five years\, the project ha s grown to more than 260 indices (v0.9.0) and expanded beyond a single rep ository into a multi-language ecosystem. Open-source APIs operationalize t he specification in Python (*spyndex*)\, the Google Earth Engine Code Edit or (*spectral*)\, and Julia (*SpectralIndices.jl*)\, alongside community-d riven implementations such as the R package *rsi*. With over 1k GitHub sta rs\, more than 200k downloads across PyPI and conda-forge\, and alignment with the electro-optical STAC extension\, ASI now functions as reusable in frastructure embedded in reproducible Earth observation workflows.\n\nThis talk reflects on five years of technical and community development: the e volution from list to specification\, a design that supports scientific co mpleteness and implementation simplicity\, and the role of metadata and ve rsioning in ensuring long-term sustainability. It concludes with the next phase of development\, including extensions to the band standard\, richer metadata\, expanded categorization\, and API refinements aimed at strength ening interoperability and ensuring that spectral indices remain stable an d accessible within the open geospatial ecosystem. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:From NDVI to an Open Ecosystem: Five Years of Awesome Spectral Indi ces — David Montero Loaiza URL:https://talks.osgeo.org/foss4g-europe-2026/talk/YWDSJ9/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-9925710e-3df2-56f8-8d3e-8a4f2dcd35bc@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T120000 DTEND;TZID="+03:00":20260701T123000 DESCRIPTION:Learn everything MapLibre has been up to\, from the new tile fo rmat to Martin tile server\, MapLibre GL\, MapLibre Native\, and many othe r projects DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:MapLibre Tiles - next generation tech and other MapLibre news — Y uri Astrakhan URL:https://talks.osgeo.org/foss4g-europe-2026/talk/PSPMUT/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-50a9bd37-2855-5611-a8b5-aa47c7e77edc@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T120000 DTEND;TZID="+03:00":20260701T123000 DESCRIPTION:Cadastral data collection and land allocation is a key requirem ent in the world system of today.\nIn Laos\, a complete dataset of the cou ntry remains missing and is continuously being updated. There is a central database (LaoLandReg) which is gradually being supplemented with paper fo rms. Land rights are scanned analogously with fingerprints and signatures and painstakingly entered into LaoLandReg.\n\nThis presentation will outli ne the project that has been ongoing for the last year in collaboration wi th the Laotian Ministry of Land Management\, commissioned by KfW\, to full y digitize cadastral management. The goal was to make the entire process m ore efficient\, transparent\, and future-proof.\n\n**Current Status:**\n\n Currently\, copies of the central LaoLandReg database are distributed to t he individual provinces and used offline on local computers. State personn el use GPS devices to record the corner points of buildings and land parce ls on-site. Attribute data\, fingerprints\, and signatures of neighbors ar e also collected. This information is then manually entered into the local database and\, after several months\, transmitted to the central system – a time-consuming and error-prone process.\n\n**The Solution:** Don't d espair – ask Open-Source GIS! Using QGIS\, QFieldCloud\, and QField\, in particular\, we automated and optimized this complex workflow. Intelligen t workflows\, data linking\, and flexible layouts make the entire process now significantly more efficient and transparent.\n\n**Special Feature:** \nThanks to this project\, the new feature of [COGO - Coordinate Geometry] (https://github.com/opengisch/QField/pull/6923) found its way to QField. C OGO is a framework that allows you to define a precise location of any spa tial feature\, making use of mathematical functions and measurements. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Systematic Land Regulation Tool (SLRT) - Digitalization that goes b eyond borders — Berit Mohr URL:https://talks.osgeo.org/foss4g-europe-2026/talk/HJJQLS/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-64769757-238e-56f1-8c61-ef184d98874e@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T120000 DTEND;TZID="+03:00":20260701T123000 DESCRIPTION:GeoSolutions has been involved in several projects\, ranging fr om local administrations to global institutions\, involving GeoNode deploy ments\, customizations and enhancements. A gallery of projects and use cas es will showcase the versatility and effectiveness of GeoNode\, both as a standalone application and as a service component\, for building secured g eodata catalogs and web mapping services\, dashboards and geostories. In p articular\, the recent advancements. Examples of GeoNode’s builtin capab ilities for extending and customizing its frontend application will also b e showcased. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:GeoNode: What is\, Use Cases & Custom Applications — Giovanni All egri\, Mattia Giupponi URL:https://talks.osgeo.org/foss4g-europe-2026/talk/JFHU7L/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-f5f0b8ce-6b09-5ea6-b0ac-d33744124137@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T120000 DTEND;TZID="+03:00":20260701T123000 DESCRIPTION:Digital Twins are becoming a standard requirement for urban pla nning and infrastructure\, but the software landscape is still dominated b y expensive\, proprietary systems. Over the last few years\, with support from a community crowdfunding campaign\, we have been working to make QGIS a viable alternative for building Open Source Digital Twins.\nThis talk will walk through the specific hurdle we faced and the solutions we implem ented to get QGIS 3D ready for production work. We will move beyond visual isation to show how QGIS now handles the heavy lifting required for real-w orld projects.\n\nWe will cover:\n - Handling Massive Data: We rewrote par ts of the rendering engine to support instanced rendering and dynamic chun king. This means you can now load millions of 3D objects\, like city-wide tree datasets or street furniture\, and navigate through massive point clo uds without the software lagging or crashing.\n - Making 3D Useful\, Not J ust Pretty: A Digital Twin is useless if you can't query it. We bridged th e gap between the 2D and 3D views\, adding tools to identify\, select\, an d inspect feature attributes directly in the 3D window.\n - Interoperabili ty: We added native support for 3D Tiles and ESRI Scene Layers (I3S)\, so users can stream in heavy 3D mesh data from existing sources without needi ng complex conversion workflows.\nWe will also demonstrate significant enh ancements to the cross-section tool\, improving its usability for analysin g complex 3D datasets. Join us to see how these updates have turned QGIS i nto a serious tool for 3D data management. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:QGIS for Digital Twins — Saber Razmjooei URL:https://talks.osgeo.org/foss4g-europe-2026/talk/E79HRQ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-c909c29e-15b2-57b9-a491-99a3eb6abdd2@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T120000 DTEND;TZID="+03:00":20260701T123000 DESCRIPTION:How dependent is your town on the electricity grid? How many bu ildings are supplied by rooftop solar panels? How much unused potential is there to leverage the power of the sun?\n\nWe built a deep learning model using FOSS4G and open remote sensing data for Germany. With this model\, you can detect which buildings have rooftop solar panels at a neighbourhoo d level. The input data is orthophotos and OpenStreetMap building footprin ts\, which we feed into a 4-channel image classification model.\n\nThe res ults of the model are visualised in the Rooftop Solar assessment tool of t he Climate Action Navigator (https://climate-action.heigit.org) from HeiGI T (https://heigit.org).\n\nIn this talk\, we will demonstrate our results through our assessment tool. We will also explain the design of our model and how we used OpenStreetMap tagging to significantly speed up the creati on of training data for our supervised learning approach. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Detecting Rooftop Solar Panels with Deep Learning\, using Open Remo te Sensing Data and OpenStreetMap — Gefei Kong URL:https://talks.osgeo.org/foss4g-europe-2026/talk/ENYAFG/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-12f37361-b776-5fe8-b42d-a6cfa61e1fc8@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T123000 DTEND;TZID="+03:00":20260701T130000 DESCRIPTION:Real-time rendered maps are surprisingly complex beasts.\n\nThi ngs you may take for granted\, such as placement of labels on the map\, ha ve been the subject of multiple PhDs and the cause of a large amount of de veloper blood\, sweat and tears.\n\nIn this talk we will take you on a rid e-along and show you the gnarliest challenges of real-time rendered maps\, as well as the secrets you will find hidden deep in the MapLibre source c ode used to tackle them. After this talk\, you will understand:\n\n- The r aison d'être of the MapLibre project. \n- How we manage to evolve this co mplex piece of software.\n- Why creating your own map toolkit is a bad ide a\, but why you should try anyway. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Secrets of real-time rendered maps feat. MapLibre Native — Bart L ouwers\, Stefan Karschti URL:https://talks.osgeo.org/foss4g-europe-2026/talk/JCJSVM/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-de1f69d2-cc23-5308-8553-237ab74b9a4e@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T123000 DTEND;TZID="+03:00":20260701T130000 DESCRIPTION:Many organizations still rely on the manual 'Pen and Paper' met hod for field surveying. This traditional approach is riddled with common problems: unreadable handwriting\, missing attributes\, photos taken that are disconnected from their actual locations\, and manual data entry back at the office which creates a bottleneck where errors thrive. Perhaps most frustrating is the 'data lag'\, the days or weeks it takes for informatio n to travel from the field to the person who needs to make a decision. In a world of instant information\, these delays are no longer necessary.\n\n During the talk\, we will present how Mergin Maps was used in real-life sc enarios enabling:\n\n- Seamless Collection: Prepare standardized forms wit h safety features like mandatory fields and drop-down menus to ensure that no data is left behind or incorrectly collected.\n- Integrated Georeferen ced Photos: With the mobile app\, you can take multiple pictures per data point. They are automatically georeferenced and part of your project right away. Forget about the headache of manual geo-tagging during evenings.\n- Instant Synchronization: Update your QGIS layers with a single button\, n o cables and no manual CSV imports required. Our synchronization allows fo r surveyors to work on the same project at the same time\, precise version ing of your data\, all the while keeping your office and field teams conne cted even when they are miles apart. Crucially\, while synchronization is handled online\, all data collection remains fully available offline for r emote locations.\n\nMergin Maps is an open-source platform that enables yo u to collect field data directly into your QGIS project. Being fully integ rated with QGIS means that all layers\, background maps\, symbology\, and custom forms are fully synchronized and shown in the mobile app exactly as they appear on your desktop. Mergin Maps is developed to be intuitive and as simple as possible. Your field team can focus on the tasks at hand wit hout needing to know that QGIS exists\, yet they will still be able to col lect high-quality\, professional data.\n\nIf you are currently struggling with messy spreadsheets\, lost paperwork\, or a clunky workflow that makes you want to avoid fieldwork altogether\, this talk might be for you. Join us to see that losing data does not have to be a standard. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:How Mergin Maps connects QGIS and Field Data Collection in seconds without using Paper — Patrik Mizera URL:https://talks.osgeo.org/foss4g-europe-2026/talk/7ERAEU/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-9dec84d7-16d4-5712-8317-c7a70f53a516@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T123000 DTEND;TZID="+03:00":20260701T130000 DESCRIPTION:Terra Draw is an MIT licensed JavaScript library for drawing on web maps. It supports six different mapping libraries out the box\, inclu ding the popular open source libraries MapLibre\, Leaflet.js and OpenLayer s. The library has many builtin drawing modes for creating common geometri es that users need such as point\, linestring\, polygon and rectangle amon gst others. As well as the builtin modes\, Terra Draw supports the ability for users to create their own custom modes. Users can provide deep stylin g control for the features created in these modes to match their applicati ons design\, creating a seamless drawing experience for users.\n\nThis tal k will get those new to Terra Draw up to speed on the library and how it w ork\, and then go into some of the new features we have been working on ov er the last year. These include the widely requested undo/redo functionali ty\, improved opacity support for features\, click and drag drawing suppor t for several modes and support for multiple instances of the same modes w ith different configurations. We'll also look at some interesting real lif e use cases that we have observed in the last year\, showcasing our users to the wider FOSS4G community.\n\nLastly\, we'll give an update on the fut ure of Terra Draw and the expected direction of the project for the next y ear\, showing users what they can expect to see in the near future. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Terra Draw: What's new for 2026? — James Milner URL:https://talks.osgeo.org/foss4g-europe-2026/talk/SVK98A/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-5e11d429-b3e2-516b-bb72-faf2311d0b53@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T123000 DTEND;TZID="+03:00":20260701T130000 DESCRIPTION:The presentation describes processes and open-source tools empl oyed by the author and his team to build and consume digital models for ur ban environments. The results of these processes will be rendered in MapSt ore as 3D Tiles layers\, an OGC community standard designed for streaming and rendering massive 3D geospatial content. MapStore WebGIS framework sup port for 3D Tiles and glTF models through the Cesium mapping library has b een greatly enhanced to support a more powerful integration. The latest ve rsions of MapStore also include improvements and tools for exploring 3D da ta such as Map Views\, Styling\, 3D Measurements\, Annotations and more.\n \nAttendees will be presented with an overview of our work related to 3D d ata processing and visualization\, and a selected city will be used to exe mplify the processes. At the end of the presentation\, attendees will be a ble to use the presented processes\, tools and workflows to replicate them in different urban scenarios\, finally visualizing them with the 3D tools of the MapStore WebGIS application. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Explore open-source tools for creating digital urban models with Ma pStore — Lorenzo Natali\, Tobia Di Pisa\, Stefano Bovio URL:https://talks.osgeo.org/foss4g-europe-2026/talk/JXEHLZ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-a0d55b9a-0f5e-59de-ac3f-a73d12b57d54@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T123000 DTEND;TZID="+03:00":20260701T130000 DESCRIPTION:The Open Earth Monitor Cyberinfrastructure is an European proje ct (2022-2026) that has brought together Earth Sciences and computer scien tists that imagined and calculated a significant amount of \nworldwide and regional geospatial data products based on satellite data\, from agricult ure to forestry\, from air quality to flood monitoring. Behind the science and technical progress done to support these results\, it is essential to also expand their benefits beyond their traditional fields. Thus\, work w as done to assess to which extent the project’s results can assist in p roviding a clearer image of the risks to which the private European sector is exposed due to climate change.\nA special attention was given to the f inancial sector with an emphasis on the insurance branch\, given its signi ficant role in the stability of the economy\, through its intermediary ser vices to transfer and allocate financial capital. The team used the open source tool Climada to evaluate the potential of OEMC generated products i n the analysis of risk assessment of the European private sector. This tal k will present the results obtained. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Mapping the Unavoidable: Using open source and open data to better understand climate change impacts on the private sector — Codrina Ilie URL:https://talks.osgeo.org/foss4g-europe-2026/talk/GHPZKA/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-24ece046-f820-5ca6-98bf-b9342e9fe5d2@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T143000 DTEND;TZID="+03:00":20260701T150000 DESCRIPTION:The Mapbox Vector Tile specification has been around in the eco system for over 10 years\, becoming a formal standard in 2017. They took o ff due to their lightweight encoding that allows for fast and efficient se rving of map tiles. The use of vector tiles is now very common within the geospatial ecosystem with support in many FOSS4G tools for both production and consumption.\n\nThere are many approaches to serving out vector tiles to end users\, with some teams choosing to generate tiles upfront with a library like Tippecanoe and statically serve them\, whilst others are usin g a database like PostGIS and serving them dynamically\, potentially with tile servers like Martin or Tegola. Some teams will use a hybrid approach with more frequently updated data being served on the fly and data that is updated less frequently being served as static files.\n\nThere are trade offs that come with choosing between static or dynamic tile serving\, incl uding speed\, cost\, complexity\, flexibility and freshness of data. This talk we dig into these trade offs\, examining how and when each approach m akes sense and which options you can choose for each. Attendees can expect to come away with a nuanced understanding of these tradeoffs and insights into the tools that they could use when making this decision. We will als o finish off by touching on new developments in the vector tile ecosystem like the new MapLibre Tile specification\, and MVT support from DuckDB. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Vector Tiles: Static or Dynamic? — James Milner URL:https://talks.osgeo.org/foss4g-europe-2026/talk/8P3BMH/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-0f593bb3-3bdf-5844-bfff-0671e4a94172@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T143000 DTEND;TZID="+03:00":20260701T150000 DESCRIPTION:Precise localization in urban areas\, can be tricky despite hav ing accurate GPS devices. Urban canyons may lead to interrupted and reflec ted satellite signals making navigation unreliable und imprecise.\n\nThis presentation will present the outcome of the ongoing European Horizon Init iative [Egeniouss](https://www.egeniouss.eu/). In a consortium of more tha n 10 partners we have worked more than three years to get to the point whe re we can locate ourselves within 10 cm's in urban areas without adding an external GPS Device.\nThe project’s mission was to harness alternative data sources and develop a cloud service based on novel multi-sensor navig ation with a tightly integrated visual localisation component to overcome known GNSS issues and augment existing EGNSS services. Following\, this se rvice is made available through a dedicated API. To validate our approach\ , we defined three real-world use cases to test the reliability and accura cy of the service.\nWe’ll showcase one of these used cases and explain h ow Egeniouss has been integrated into QField via its innovative plugin fra mework.\n The presentation will cover the journey of egeniouss alongside Q Field and how both were constantly improved to finally serve the same grou ps of end-users. \nNew features which were specifically developed to final ly meet the needs of the end-users of the egeniouss service in the urban a reas\, will also be presented. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:QField goes (e)geniouss — Berit Mohr URL:https://talks.osgeo.org/foss4g-europe-2026/talk/NSG7MA/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-8ac9c6f3-7482-5c7a-ac4c-a8905b269b7a@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T143000 DTEND;TZID="+03:00":20260701T150000 DESCRIPTION:Earth observation using remote sensing (or satellite data) come s with its own fair bit of challenges. From managing large amounts of data to dealing with projections\, inconsistencies with resolutions and more. \n\nWhile there's no silver bullet to solve all these problems\, we'll loo k at one possible of modelling your GIS data (not just satellite data) in a Discrete Global Gird System (DGGS). \n\nIn DGGS\, you divide the earth i nto multiple cells and store the data in each cell. There are few advantag es of using this approach \n- Single data structure for all your GIS (vect or or raster) \n - Rasters are represented as array of Cell ids with eac h cell having a value \n - Vectors are represented as Points => Cells\, Lines => Array of Cells\, Polygon => Array of Cells \n- A single base fram e with multiple layers of data built on top \n- Easy visualization and ana lysis \n- Easy storage and retrieval based on Cell IDs \n\nIt's not all ra inbow in the DGGS land\, you lose:\n- Existing tool set not built around D GGS \n- Distortions/Errors going from point data to cells \n\nBut still it 's an interesting way to look at data. We'll use \n- DuckDB as our databas e and query engine \n- Sample data from OSM \n- Sample data from Sentinel- 2 DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Storing your Satellite in a DGGS — json singh URL:https://talks.osgeo.org/foss4g-europe-2026/talk/UKW9M8/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-4ec4aa6c-e67b-5fa0-98f9-0bdeaa32c870@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T143000 DTEND;TZID="+03:00":20260701T150000 DESCRIPTION:We are a group of companies:\n1. "Geomatics Solutions"\, Ltd.\, created in 2002 by a group of specialists in the field of Geomatics. For 24 years\, the company has been well proven in production and in delivery of services related to the creation\, processing\, and use of geospatial d ata.\nhttps://geosol.com.ua/about_en.html\n2. Now managing the results of "Intelligence Systems GEO\, Ltd." (ISGeo). ISGeo created in 1996 by the gr oup of experts from the V.M. Glushkov Institute of Cybernetics and was the leading Ukrainian company in the sphere of geoinformation systems (GIS) a nd spatial database development. \nhttps://isgeo.com.ua/about\n\nOur compa nies have faced several crisis situations throughout their history. We'll share our experiences\, both successful ones and those where we lost a sig nificant portion of our developments and resulting data. We'll explain why and how we came to the OSGeo/FOSS4G ecosystem. Using our own examples\, w e'll highlight some of the challenges we encountered when working with pro prietary software. We'll demonstrate the benefits of using OSGeo tools and projects. We'll also discuss how the latest developments from the Open GI S community helped us make decisions and keep our stack up to date with th e help of annual FOSS4G conferences.\nWe have experienced the following di rections and their stages:\n1) Technological development:\na) Transition f rom paper maps to digital ones. The results of this work include CDs/DVDs\ , atlas books\, and map brochures. We primarily worked with proprietary so ftware.\nb) Transition from desktop applications to web-based alternatives . This resulted in static websites\, Tile-Servers\, and other server solut ions. Partial transition to an open-source stack. We began implementing pr oducts such as GeoServer and Leaflet. 2012–2015.\nc) Transition from sta tic Web 1.0 to dynamic Web 2.0 between 2010 and 2018. Adding interactivity and strong user engagement when using products. Also\, a complete shift i n the core stack in favor of open-source OSGeo products.\nd) Transition fr om an interactive web resource to the provision of services as a service s tarting in 2018.\n2) Global instability:\na) Covid-19. The transition to o nline. This facilitated the full use of server technologies. Products such as GeoServer and QGIS Server were very helpful. Period 2020–2022.\nb) G eopolitical instability. The situation in the country since 2014 and globa lly since 2022. Loss of access to servers\, transition to cloud environmen ts. Mobile workstations are being built. Licensing and access to licensed servers have become a pressing issue. Caching and desktop solutions are be ing used to address unstable internet access. QGIS\, GDAL/OGR\, and PROJ h ave proven effective. For data\, use GeoPackage\, GeoTIFF\, PostgreSQL+Pos tgis and SpatialLite.\nAt each stage\, we used different technology stacks . We began using proprietary software that positioned itself as stable\, s ecure\, and supported. We were among the first official partners/distribut ors of such global monopolistic companies of the time as Pitney Bowes MapI nfo Corporation\, Avenza Inc. (Canada)\, Infotech Europe (Great Britain)\, and PCI Geomatics Inc. (Canada).\nBut\, with the very first change\, we e xperienced difficulties in transferring already collected data to new stac k solutions. The main problem was the proprietary software. The result of this work—a multitude of written add-ons/modules/extensions\, a multitud e of resulting data—was all "captive" to the proprietary software monopo lies. We realized we didn't control the system and didn't own our own data . We were under the influence of mega-corporations. It was their speed of response to global trends and other global/local changes\, especially loca l ones. American companies\, which dominated our stacks\, didn't quite und erstand or respond appropriately to our local challenges.\nThe support sys tems turned out to be very slow and underperforming. Simple fixes for iden tified bugs took months\, which impacted product release schedules. This n egatively impacted the company's overall "respect." This also led to probl ems with understanding\, as the mentality\, culture\, and values "across t he ocean" differ greatly from those of Western and Central Europe.\nAfter 10-15 years of work\, we made a difficult\, but ultimately correct\, decis ion. We completely rethought our entire approach to running our IT busines s. We rewrote all our existing developments. We partially migrated what we could to a new technology stack. This stack became the OSGeo/FOSS4G produ ct suite. The main requirement was open-source code for the development pr oduct\, as well as open data formats. No binary formats that limit perform ance\, such as DLLs\, Flash\, and so on. The goal was to ensure that all m odules and plugins could be maintained independently even if support for c ertain software ceased. All data was now stored exclusively in open format s. This set of open formats\, those that can be opened using several open- source products\, was key when selecting the software.\nOpen source won't eliminate the problem of crisis situations or save us from something beyon d our control. However\, due to openness\, we have complete control over t he entire technology stack\, all the results of years of development. And this is key for an IT company.\nInitially\, when choosing\, we were faced with a huge abundance of frameworks and libraries. This was confusing. We needed to avoid getting bogged down in a multitude of different solutions. Finding truly high-quality software with a strong\, supportive community became a pressing issue. Initially\, we looked at stars\, forks\, the date s and frequency of commits and project versions\, and the number of contri butors on GitHub.\nBut due to the lack of funding\, donations became scarc e\, and even good solutions disappeared from the market. We had to find al ternatives or take on full support ourselves.\nUltimately\, we found a str ong community sponsored by OSGeo/FOSS4G products. We enjoyed stable sponso rship\, a huge community\, and frequent and highly informative FOSS4G conf erences. We learned a lot of best practices from these conferences.\nOSGeo /FOSS4G minimizes the risk of product discontinuation\, provides stable su pport\, and operates within a unified community. All OSGeo/FOSS4G products provide confidence and guarantee stability and long-term product support. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:How to survive in a rapidly changing world or how to protect your d ata from the "captivity" of proprietary software — Vasyl Yasko URL:https://talks.osgeo.org/foss4g-europe-2026/talk/ENLRK9/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-d04b1179-b040-5748-8ec8-566735f24d91@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T143000 DTEND;TZID="+03:00":20260701T150000 DESCRIPTION:This presentation will introduce the most important innovations from the GeoNetwork community and present the roadmap for 2026 and beyond . These include the ambitious GeoNetwork 5 initiative\, new features of th e modern GeoNetwork UI framework\, and what lies ahead for existing GeoNet work 4 instances. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:GeoNetwork\, for a connected Europe — Olivia Guyot URL:https://talks.osgeo.org/foss4g-europe-2026/talk/EXMNUS/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-d47c2434-9d6e-5824-8ebd-8f6a31ff9eda@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T150000 DTEND;TZID="+03:00":20260701T153000 DESCRIPTION:pygeoapi is an OGC API Reference Implementation. Implemented in Python\, pygeoapi supports numerous OGC APIs via a core agnostic API\, di fferent web frameworks (Flask\, Starlette\, Django) and a fully integrated OpenAPI capability. Lightweight\, easy to deploy and cloud-ready\, pygeoa pi's architecture facilitates publishing datasets and processes from multi ple sources. The project also provides an extensible plugin framework\, en abling developers to implement custom data adapters\, filters and processe s to meet their specific requirements and workflows. pygeoapi also support s the STAC specification in support of static data publishing.\n\npygeoapi has a significant install base around the world\, with numerous projects in academia\, government and industry deployments. The project is also an OGC API Reference Implementation\, lowering the barrier to publishing geos patial data for all users.\n\nThis presentation will provide an update on the current status\, latest developments in the project\, including new co re features and plugins. In addition\, the presentation will highlight key projects using pygeoapi for geospatial data discovery\, access and visual ization. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:pygeoapi project status — Tom Kralidis URL:https://talks.osgeo.org/foss4g-europe-2026/talk/BG9WH8/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-af233953-85bf-590f-99a3-5f49b1221653@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T150000 DTEND;TZID="+03:00":20260701T153000 DESCRIPTION:Hexagon based grids have gained particular attention in geospat ial applications with their use in discrete global gridding systems (DGGS) . A feature of many DGGS is the indexing of the grid cells at different re solutions to uniquely identify the cells. For hexagon based DGGS like H3 o r IGEO7 the underlying system for indexing is based on 2D generalized bala nced ternary (GBT).\n\nGBT was originally described in the 80s for use in image analysis because of the similarity between hexagon grids and biologi cal vision systems. Here we discuss how GBT encodes indexes and discuss th e basics of GBT arithmetic in 2D hexagon grids. We demonstrate how GBT ari thmetic can be employed for neighbour traversal and more broadly spatial a lgorithms on hexagonal girds. Finally\, we will look at the special cases that arise in the application of GBT to indexing in DGGS\, which are the c onsequences of necessary pentagons and non-GBT arranged base zones. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Indexing with Hexagons: GBT Explained — Javier Jimenez Shaw\, Wes ton Renoud URL:https://talks.osgeo.org/foss4g-europe-2026/talk/HFJQ9H/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-bc0165f4-0fd1-5e97-b960-7cb8e895ea99@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T150000 DTEND;TZID="+03:00":20260701T153000 DESCRIPTION:Open geospatial ecosystems increasingly depend on collaboration between open source communities\, universities\, and private companies. W hile these actors often share common goals\, building partnerships that la st beyond short term funding or sponsorship remains a practical challenge. \nThis talk explores sustainable collaboration models that balance opennes s with real world constraints such as institutional timelines\, commercial objectives\, and governance structures. Drawing on European examples\, it highlights what enables long term cooperation: clear roles\, shared gover nance\, open contribution pathways\, and mutual value creation across rese arch\, education\, and industry.\nThe session offers a practical perspecti ve on designing collaborations that strengthen the FOSS4G ecosystem withou t compromising independence or open principles.\nAudience level: Beginner to intermediate\nKey takeaway: Sustainable open–enterprise collaboration is built on trust\, clarity\, and shared long term value. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:When “Open” Meets “Enterprise”: Sustainable Collaboration B etween Communities\, Universities\, and Companies — Octavian Borcan URL:https://talks.osgeo.org/foss4g-europe-2026/talk/EYNXGT/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-9dfe48d0-32f9-5ec9-bb57-4ee2226e6c64@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T153000 DTEND;TZID="+03:00":20260701T160000 DESCRIPTION:The remote execution of processing workflows is a common task i n many spatial data infrastructures and projects. To increase interoperabi lity\, the OGC (Open Geospatial Consortium) published the [API Processes s tandard in 2021](https://ogcapi.ogc.org/processes/). Its RESTful design an d use of JavaScript Object Notation (JSON) encoding make it suitable for c loud environments. [Pygeoapi](https://pygeoapi.io/) is an open-source impl ementation of this standard.\n\nIn pygeoapi\, several plugins are availabl e and a manager component must be implemented to manage process jobs. A c ommon feature of the built-in managers is that the processing jobs are exe cuted directly within the pygeoapi Python environment. Hence\, a job with high resource demands influences the resource requirements and usage of th e pygeoapi instance itself. Recognizing the limitations of pygeoapi’s bu ilt-in job managers regarding isolation and resource handling\, we develop ed the [pygeoapi-K8s-manager](https://github.com/52North/pygeoapi_k8s-mana ger).\n\nResource sharing and non-existent job isolation are some of the d isadvantages of this architecture. Due to the resource-intensive nature an d need for scheduled execution of certain processes within our projects\, we had to run a “heavy” pygeoapi deployment in our cluster. We also n eeded to execute processes in diverse runtime environments outside of Pyth on\, e.g.\, using the CUDA Fortran model execution.\n\n We decided to deco uple the management and execution layers to address these demands. Having already deployed a pygeoapi instance in our K8s cluster\, it made sense t o take advantage of the cluster's processing capabilities. Our team used K 8s-CronJobs for process scheduling and K8s-Jobs for execution. The Kuberne tes API server handled the process management and pygeoapi provided an int erface. The resulting\, generic “pygeoapi-k8s-manager” was developed b ased on [EOX IT Services GmbH’s](https://eox.at) [“pygeoapi-kubernetes -papermill“](https://github.com/eoxhub-workspaces/pygeoapi-kubernetes-pa permill).\n\nBy decoupling management and execution\, we were able to defi ne complex process requirements such as using GPUs via Job properties. An autoscaler installed in the cluster applies these properties. This enable s on-demand provision of the requested resources.\n\nOur team implemented two processes: a HelloWorld-K8s process and a process to run generic image s. The first process demonstrates how to run a preconfigured image. The ge neric process enables image configuration via the pygeoapi configuration f ile.\n\nWe will present the current pygeoapi-K8s-manager implementation\, future development plans and illustrate its application through exemplary use cases\, such as data ingestion\, flood modelling and ship voyage optim ization workflows. Listeners will gain practical insights into how Kuberne tes and OGC API Processes can improve your geospatial data processing work flows\, e.g.\, by reducing resource requirements. The talk will cover sust ainable resource management and explain the operation of pygeoapi in a clo ud-native environment. We aim to encourage wider adoption\, feedback\, and contributions to these ongoing developments through this conference. DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Optimizing resource usage of interoperable geospatial processing in frastructures with Kubernetes — Eike Hinderk Jürrens\, Martin Pontius URL:https://talks.osgeo.org/foss4g-europe-2026/talk/VWRHVX/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-7e771907-dd73-526e-a394-72db4e5478b2@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T153000 DTEND;TZID="+03:00":20260701T160000 DESCRIPTION:QGIS is one of the most widely used open-source desktop GIS pla tforms\, offering strong tools for geospatial data management\, editing\, and styling. Yet collaboration is still hard in everyday production workfl ows: teams need shared server-side storage\, reliable desktop synchronizat ion\, conflict-aware multi-user editing\, and a transparent history of cha nges.\n\nWe develop an open-source stack that enables smooth simultaneous editing from both QGIS and Web maps. NextGIS Web is a Web GIS server for s toring and publishing geospatial data with granular permissions and built- in version control for vector layers. It uses QGIS as a renderer\, providi ng near-complete support for QGIS symbology in web maps. NextGIS Connect i s a QGIS plugin that integrates QGIS with NextGIS Web: it supports publish ing QGIS projects as web maps\, opening web maps as QGIS projects\, editin g server data directly from QGIS\, and resolving conflicts interactively.\ n\nThe latest NextGIS Connect release adds end-to-end handling of feature attachments (photos\, documents\, and other files)\, managed consistently from both QGIS and the Web interface. Attachments are also covered by the same versioning mechanics as spatial and attribute edits.\n\nIn this talk\ , we will present the current state of the NextGIS Web / NextGIS Connect / QGIS ecosystem\, demonstrate workflows for seamless multi-user editing\, and show how teams can move from local QGIS projects to enterprise-level c ollaboration using open source software. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:QGIS Teamwork with NextGIS Web: Sync\, Conflict Resolution\, and Ve rsion Control — Eduard Kazakov URL:https://talks.osgeo.org/foss4g-europe-2026/talk/EVMMWW/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-bd97dee0-638a-5be4-b8ff-37f96d633b83@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T153000 DTEND;TZID="+03:00":20260701T160000 DESCRIPTION:Observing the earth is not so straightforward with many web map viewers. How about the poles? How can we easily change the current time\, and see which time span each layer has? And what about the day/night cycl e?\nIfremer and Camptocamp have worked together to come up with a new soft ware for this. We made the Sextant Viewer to be extremely easy to use\, bu t also to address data sources and use cases that other map viewer on the market do not do as much. The Sextant Viewer shows Cloud-Native data\, it switches effortlessly to globe mode using MapLibre\, and it will fit snugg ly inside any web site with its Web Component architecture. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:A look at our planet with the Sextant Viewer — Olivia Guyot URL:https://talks.osgeo.org/foss4g-europe-2026/talk/ZPD9KG/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-81ca32ac-6f21-5f83-a633-038ec9348a16@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T153000 DTEND;TZID="+03:00":20260701T160000 DESCRIPTION:Large Language Models are reshaping how we interact with data — but most implementations ignore geography entirely. At Camptocamp\, we 've spent the last two years embedding LLMs deep into open source geospati al workflows\, and this talk is a frank account of what works\, what doesn 't\, and where the field is heading.\n\n** GeoNetwork as a GeoAI laborator y\n\nGeoNetwork\, the OSGeo flagship metadata catalog\, is where much of o ur work has been grounded. We'll walk through the integration of semantic search — moving beyond keyword matching to meaning-based retrieval power ed by embedding models — and the development of a conversational assista nt that lets users query geographic datasets in plain language. We'll also share our ongoing work on exposing GeoNetwork capabilities through the Mo del Context Protocol (MCP)\, enabling LLM agents to interact directly with catalog APIs.\n\n*** Agentic geospatial: bleeding edge techniques\n\nBeyo nd search and chat\, we'll dive into what agentic AI looks like when appli ed to geospatial workflows: function calling to orchestrate GIS operations (buffer\, intersection\, spatial queries against OpenStreetMap)\, LLM-dri ven QGIS automation via MCP\, and the architectural patterns — RAG pipel ines\, intent extraction\, hybrid search — that make these systems relia ble enough to put in front of real users.\n\n** The French National Digita l Twin: an open source GeoAI at scale\n\nWe'll close with our role leading the LLM workstream of the French National Digital Twin project (France 20 30)\, a consortium bringing together IGN\, INRIA\, Cerema and others. This initiative is tackling GeoAI at territorial scale — and doing it entire ly in the open. We'll share early architectural decisions\, the challenges of grounding LLMs in authoritative geographic knowledge bases\, and why o pen source is not just a preference here but a sovereignty requirement.\n\ n** Key takeaways for the FOSS4G community\n\nAttendees will leave with a clear picture of the current state of open source GeoLLM tooling\, practic al patterns for integrating LLMs into OSGeo-stack applications\, and an ho nest assessment of the remaining challenges — from data quality to model size optimization — that the community needs to solve together. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:GeoLLM in the Wild: Open Source AI Meets Geospatial — Florent Gra vin URL:https://talks.osgeo.org/foss4g-europe-2026/talk/JM9A8T/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-23bd3f0e-5885-50c0-8e39-7aed4aa76967@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T153000 DTEND;TZID="+03:00":20260701T160000 DESCRIPTION:MapStore is a powerful open-source framework for building\, man aging and sharing web-based maps\, dashboards and geostories directly in t he browser. It supports a wide range of geospatial data and highly customi zable viewer applications.\n\nIn this talk\, GeoSquare Belgium presents a real-world implementation of MapStore for the Department of Mobility and P ublic Works (DMOW) of the Flemish Government. What started as a proof of c oncept\, has quickly evolved into a fully operational open-source WebGIS p latform supporting data-driven mobility policy in Flanders.\n\nThe platfor m integrates MapStore\, GeoServer\, GeoNetwork and PostgreSQL to power a g eoportal that hosts multiple thematic applications. These applications com bine interactive maps\, dashboards and geostories to support internal deci sion-making while simultaneously publishing selected data and insights to citizens through public web services and embedded web applications.\n\nTo illustrate the capabilities and flexibility of the platform\, several use cases will be highlighted\, such as bicycle infrastructure monitoring\, su pporting the deployment of intelligent traffic lights and using the custom developed photoviewer extension to view and navigate images on the map. \ n\nWe will also briefly touch on community contributions like OpenID integ ration\, dynamic filtering\, and translation updates.\n\nJoin us to discov er how MapStore’s flexible design enables organizations like DMOW to del iver both ready-to-use and customized user-friendly geospatial solutions. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Supporting Mobility and Infrastructure Decisions in Flanders with M apStore — Yanko Godaert URL:https://talks.osgeo.org/foss4g-europe-2026/talk/B8UFHS/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-bfe5aac0-e13a-56fc-9a65-d5e3832387e9@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T163000 DTEND;TZID="+03:00":20260701T173000 DESCRIPTION:Stay tuned! More info coming very soon! DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Surprise Keynote — Marian Neagul URL:https://talks.osgeo.org/foss4g-europe-2026/talk/9WZGDC/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-0dc7b2a8-1000-5ac2-80b6-d076e4397ce1@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260701T173000 DTEND;TZID="+03:00":20260701T180000 DESCRIPTION:Thank you for coming to FOSS4G Europe 2026! \nWe hope you had a great time in Timișoara\, meet old friends\, made new ones and learned a lot about this wonderful open source in geospatial! DTSTAMP:20260602T160506Z LOCATION:Auditorium SUMMARY:Closing plenary — Marian Neagul URL:https://talks.osgeo.org/foss4g-europe-2026/talk/RCQB9M/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-06ff843a-0b71-53dd-84ea-c90c4bb60cea@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T090000 DTEND;TZID="+03:00":20260702T130000 DESCRIPTION:This workshop will cover the basics of setting up a GeoServer 3 instance and adding vector and raster data to it\, and applying styles to the data to produce a completed web map. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:An Introduction to GeoServer3 — Jody Garnett\, Ian Turton URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/T9KQXC/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-869e7a66-bcf1-575c-898a-4e6a6d782bc0@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T090000 DTEND;TZID="+03:00":20260702T130000 DESCRIPTION:This workshop will provide an introduction to performing common GIS/geospatial tasks using Python geospatial tools such as OWSLib\, Shape ly\, Fiona/Rasterio\, and common geospatial libraries like GDAL\, PROJ\, p ycsw\, as well as other tools from the geopython toolchain. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Doing Geospatial in Python — Tom Kralidis\, Paul van Genuchten\, Angelos Tzotsos\, Just van den Broecke\, Seth Girvin URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/DVUYY9/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-9782ac52-3979-583c-ac1c-182e092bf548@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T090000 DTEND;TZID="+03:00":20260702T130000 DESCRIPTION:This interactive session will introduce you to eoAPI - a powerf ul cloud-native framework that simplifies access to Earth Observation data . By the end of this workshop\, you'll understand how to use eoAPI to cata log\, discover\, visualize\, and analyze geospatial data efficiently.\n\nW orkshop Objectives:\n* Explore how eoAPI can fit into your geospatial work flows\n* Learn about STAC (SpatioTemporal Asset Catalog) and its role in E arth observation\n* Explore the key components of eoAPI and how they work together\n* Gain hands-on experience working with metadata\, raster\, and vector services DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:eoAPI with STAC for Earth Data at scale — Felix Delattre URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/HYXDDR/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-fde839ba-7867-5e01-ad99-028d4bf60058@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T090000 DTEND;TZID="+03:00":20260702T130000 DESCRIPTION:With the most recent upgrade to QField 4.0\, it is suddenly pos sible to cloudify any project from QField from any smart device. \nIn this workshop the participant will start in QField\, not QGIS\, collect data i n the field and only then synchronize it with the desktop. \n\nParticipant s will learn how to:\n\n- create and edit their own QGIS project\n- optima lly configure attribute forms\n- cloudify their projects to QFieldCloud\n- manage teams in QFieldCloud\n- capture data using a mobile device and syn chronize it back to the cloud. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:How to cloudify your QField project - from your phone — Berit Mohr URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/Q9MDRC/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-8e24448a-b495-5f90-a885-0ebb189f02d3@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T090000 DTEND;TZID="+03:00":20260702T130000 DESCRIPTION:Environmental monitoring infrastructures are increasingly requi red to support high-frequency sensor data\, heterogeneous observation type s\, and real-time analytics\, while ensuring interoperability\, scalabilit y\, and long-term sustainability. In this context\, open standards and ope n-source technologies play a central role in enabling data sharing across institutions\, disciplines\, and national boundaries. This workshop introd uces istSOS4\, an open-source implementation of the OGC SensorThings API\, designed for the management\, publication\, and analysis of spatio-tempor al sensor observations. The workshop targets practitioners and researchers involved in environmental monitoring\, smart cities\, hydrology\, climate studies\, and geospatial data infrastructures who wish to design interope rable sensor data platforms aligned with FAIR data principles. \n\nPartici pants will gain both conceptual and practical knowledge on how to structur e sensor metadata\, ingest observations\, and expose time-series data thro ugh standardized web APIs. The workshop starts by framing the challenges o f modern sensor networks: increasing data volumes\, diverse sensor typolog ies\, the need for near real-time access\, and the integration of observat ions with downstream analytics\, dashboards\, and decision-support systems .\n\nA core focus will be the SensorThings API data model\, including key entities such as Things\, Locations\, Sensors\, ObservedProperties\, Datas treams\, and Observations. Particular attention will be given to\nmodeling complex environmental monitoring setups\, including multi- parameter stat ions\, mobile sensors\, and long-term monitoring networks. The workshop wi ll demonstrate how istSOS4 extends and operationalizes\nthis model in real -world deployments\, supporting versioning\, quality control\, and efficie nt time-series handling. Through hands-on sessions\, participants will int eract directly with an istSOS4 instance to:\n* Register sensors and mon itoring stations\,\n* Ingest observations via RESTful endpoints\,\n* Query time-series data using spatial\, temporal\, and attribute filters\, \n * Visualize and export observations for further analysis.\nThe worksho p will also cover architectural aspects\, including database backends\, pe rformance considerations for high-frequency data\, and integration pattern s with visualization tools\, data analytics pipelines\, and early-warning systems. Real use cases from environmental monitoring projects (e.g.\, hyd rometeorological networks\, water quality monitoring\, and climate adaptat ion initiatives) will be used to illustrate best practices and common pitf alls.\nBy the end of the workshop\, participants will have a clear underst anding of how to design and deploy a SensorThings-based infrastructure usi ng istSOS4\, enabling interoperable and standards-compliant access to sens or observations. DTSTAMP:20260602T160506Z LOCATION:Info lab 1 SUMMARY:From Sensors to Services: Building Interoperable Environmental Data Platforms with istSOS4 and the OGC SensorThings API — Massimiliano Cann ata\, Daniele Strigaro\, alessandro centazzo\, Claudio Primerano URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/9FMGKJ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-998d526b-47a1-5e0d-ad61-5fea016d400a@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T090000 DTEND;TZID="+03:00":20260702T110000 DESCRIPTION:The workshop describes processes and tools used by the author a nd his team to build and consume digital models for urban environments. Pa rticipants will gain exclusive insights into the development of digital mo dels in 3D Tiles format to consume them within MapStore WebGIS framework DTSTAMP:20260602T160506Z LOCATION:info lab 2 SUMMARY:Building and Consuming Urban Digital Models with Open-Source Tools — Stefano Bovio URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/8V7VAF/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-08dce483-6efa-5f3e-a9ab-0b052fc178b9@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T111000 DTEND;TZID="+03:00":20260702T131000 DESCRIPTION:This workshop will provide an introduction to building your own Extension\, a plugin component that allows adding custom functionality to the map viewer\, based on the MapStore Open Source framework. MapStore is an highly modular Open Source WebGIS framework to create\, manage and sec urely share maps and geospatial applications. DTSTAMP:20260602T160506Z LOCATION:info lab 2 SUMMARY:MapStore\, Development of an Extension — Stefano Bovio URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/SRSTLP/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-c6dbddbb-2239-5372-92a0-5782409f38eb@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T140000 DTEND;TZID="+03:00":20260702T180000 DESCRIPTION:This workshop introduces OGC APIs\, their story\, objectives an d structure\, with practical examples from the GeoServer. Join this worksh op to get an update on the APIs\, to learn the current implementation prog ress as well as some GeoServer unique features. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:OGC APIs\, an introduction with GeoServer — Andrea Aime URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/9AXLUS/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-72fa9442-e278-5e94-8bc4-442df48f8166@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T140000 DTEND;TZID="+03:00":20260702T180000 DESCRIPTION:pygeoapi is an OGC Reference Implementation supporting numerous OGC API specifications. This workshop will cover publishing geospatial da ta to the Web using pygeoapi in support of the suite of OGC API standards. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:Diving into pygeoapi Workshop — Tom Kralidis\, Paul van Genuchten \, Angelos Tzotsos\, Just van den Broecke\, Joana Simoes URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/8TVTWR/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-339b4b96-4f39-54b9-8220-3e60f80125ba@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T140000 DTEND;TZID="+03:00":20260702T180000 DESCRIPTION:MapServer is an Open Source platform for publishing spatial dat a and interactive mapping applications to the web. Learn how to set up and use one of the fastest map engines in the world! DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Getting Started with MapServer — Even Rouault\, Seth Girvin URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/LLKSRF/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-ae634f78-b905-5678-8bf9-ed74f18c9aa2@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T140000 DTEND;TZID="+03:00":20260702T180000 DESCRIPTION:This workshop provides a hands-on guide to the complete field d ata collection workflow using QGIS and Mergin Maps.\nParticipants will lea rn how to:\nConfigure QGIS Projects: Set up background maps\, smart forms\ , and tracking tools for offline use.\nCollect Data Collaboratively: Deplo y projects to mobile devices and capture data as a team\, managing synchro nization and version control.\nPublish Results: Seamlessly share finished projects as interactive web maps for non-GIS stakeholders. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:From QGIS to the Field and Back with Mergin Maps — Gabriel Bolbot ină URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/UXJAPM/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-7331043f-cc0e-5875-9f92-9860b9ba787f@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T140000 DTEND;TZID="+03:00":20260702T180000 DESCRIPTION:Spatial datasets originate in field measurements\, yet the tran sformation from sensor reading to interoperable geospatial resource is oft en hidden in GIS workflows. This workshop makes that “first mile” tang ible by guiding participants as they build and program their own hardware kit. The kit uses a microcontroller\, GNSS module\, and environmental sens or of choice. Measurements are transmitted to a provided Dockerized Python (FastAPI) and PostgreSQL backend\, where they are exposed as GeoJSON Feat ures. Emphasizing architectural clarity over complexity\, the session demo nstrates how structured JSON\, REST APIs\, and relational storage underpin scalable geospatial services\, while outlining PostGIS and OGC API as nat ural extension paths within an open standards ecosystem. DTSTAMP:20260602T160506Z LOCATION:Info lab 1 SUMMARY:From Sensor to GeoJSON: Building an Open Source IoT Geo-Pipeline — Joram van der Vlist URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/RBAVH9/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-1b71650c-bba5-5eee-b055-c7717b118aa0@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260702T140000 DTEND;TZID="+03:00":20260702T180000 DESCRIPTION:EOEPCA+ provides an out-of-the-box solution for an EO Exploitat ion Platform that integrates open source components interfacing through op en standards. Developed under an ESA project led by Telespazio\, the EOEPC A Building Blocks cover the full scope of an exploitation platform\, from data discovery and access\, through processing and analytics to user works pace management.\n\nThis hands-on workshop introduces the core platform co mponents comprising the EOEPCA solution\, providing an end-to-end experien ce that deploys and demonstrates its capabilities within Kubernetes.\n\nTh e workshop is perfect for beginners who have no prior EOEPCA knowledge and only basic Kubernetes familiarity\, but also welcomes those who have alre ady experimented with EOEPCA Building Blocks. Anyone interested in integra ting the EOEPCA components into their Exploitation Platform\, or reusing t hem for Ground Segment\, EO Data Discovery\, Processing\, should join the session.\n\nParticipants will work through guided\, browser-based tutorial s hosted on our online platform. Each tutorial runs against a live Kuberne tes environment provisioned in the cloud\, no local software installation is required\, just a laptop and a GitHub account. \nThe tutorials describe each step in context and provide the necessary commands to deploy\, confi gure and utilise the platform components. \n\nOur team will be on hand thr oughout to guide\, troubleshoot and discuss how these components can be ad apted for different deployment scenarios. Everything used in this workshop is fully open source and the tutorial source code is publicly available o n GitHub. DTSTAMP:20260602T160506Z LOCATION:info lab 2 SUMMARY:EOEPCA+ Exploitation Platform: Hands on Deployment and Usage — Ri chard Conway\, James Hinton URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/K98UDC/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-eaf5ade7-4f68-54ca-a5a4-8dfe93bcfba8@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T090000 DTEND;TZID="+03:00":20260703T130000 DESCRIPTION:Learn how to build and serve vector tiles with GeoServer\, and how GeoServer can be well suited to mixed serving use cases (raster + vect or)\, dynamic data\, as well as handling different views based on the curr ent user security clearance. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Vector tiles with GeoServer — Andrea Aime URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/YZXSRW/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-f1b4512f-9758-584d-bec4-8f9cde2e6c86@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T090000 DTEND;TZID="+03:00":20260703T130000 DESCRIPTION:Presented under the efforts of the EOPF Sentinel Zarr Explorer project\, participants will learn how to leverage a modern\, cloud-native tech stack to interact with multidimensional data on object storage. We wi ll go through the various tools that support the development of visualizat ions of the GeoZarr format. Using Copernicus Sentinel data\, we will look into building maps and dashboards using eodash\, OpenLayers\, and TiTiler. Write interactive narratives and stories using EOxStorytelling\, and visu alize maps in notebooks using Jupyter EOxElements. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:EOPF Zarr Explorer Workshop: Web Visualization Techniques and Resou rces for the GeoZarr Specification — Ahmed Behairi URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/ZLZECM/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-bbabb1f9-5880-5da1-85cb-6cd048ef32c6@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T090000 DTEND;TZID="+03:00":20260703T130000 DESCRIPTION:GeoNetwork opensource is a fully featured catalog service and t he most popular catalog in Europe. This workshop provides hands-on experie nce setting up GeoNetwork\, using INSPIRE requirements as a guideline to e xplore configuration. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Introduction to GeoNetwork — Jody Garnett\, Jeroen Ticheler URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/RATMDZ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-dcc48d29-833c-5ed3-b637-cf59e37a8db4@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T090000 DTEND;TZID="+03:00":20260703T130000 DESCRIPTION:This workshop will teach you how to work with point cloud data in QGIS. You will learn how to visualize point clouds in both 2D and 3D\, style them to highlight important features\, and process and edit them to extract meaningful information. DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:Working with Point Cloud Data in QGIS — Kurt Menke URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/E9LK8S/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-3029a840-a5c8-540e-bd61-1ba692fec609@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T090000 DTEND;TZID="+03:00":20260703T130000 DESCRIPTION:In this workshop\, we will explore the diverse range of tools a vailable in QGIS for conducting comprehensive hydrological analysis. Parti cipants will gain hands-on experience with tools from GRASS\, SAGA\, White boxTools\, and PCRaster processing provider plugins\, as well as other spe cialized plugins designed for hydrological studies.\n\nOur interactive ses sion will cover practical exercises on deriving streams and catchments\, a nd calculating essential morphometric parameters such as drainage density\ , concentration time\, and hypsometric curves. By the end of the workshop\ , attendees will have a solid understanding of how to leverage QGIS for hy drological analysis\, enabling them to apply these techniques to their own projects and research. DTSTAMP:20260602T160506Z LOCATION:Info lab 1 SUMMARY:Hydrological Analysis in QGIS — Hans van der Kwast URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/MGWBBV/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-7eaec624-2a11-505e-810c-27834bb5731a@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T090000 DTEND;TZID="+03:00":20260703T110000 DESCRIPTION:A developer tutorial for the JS/WebGL Gleo library\, with a tec hnical focus on how to create custom WebGL cartographic symbols. DTSTAMP:20260602T160506Z LOCATION:info lab 2 SUMMARY:Animating spatio-temporal vector data with Gleo (WebGL) — Iván S ánchez Ortega URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/ZLPMRY/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-87bfa2f8-c91f-5a60-aec8-33a1141a75b0@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T111000 DTEND;TZID="+03:00":20260703T131000 DESCRIPTION:PostgreSQL is a powerful\, open source object-relational databa se system. It can be extended with PostGIS which allows you to store and h andle geospatial data in the database.\nThis combination is very powerful and provides many possibilities.\n\nEverything is possible in the databse with some magic lines of SQL. This workshop will help you with the first s teps.\n\nMany processes that you did before with you Desktop GIS (f.e. int ersection\, union\, buffer) can be easily done via SQL using PostGIS funct ions. DTSTAMP:20260602T160506Z LOCATION:info lab 2 SUMMARY:Learn how to manage your geospatial data with PostgreSQL/PostGIS — Astrid Emde URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/J9RBVQ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-c5ba9fb0-dcf9-5c6a-b3a7-837d655523b5@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T140000 DTEND;TZID="+03:00":20260703T180000 DESCRIPTION:Create a tile server with the base map and some custom data. Bu ild a web site with both the base map and custom data using MapLibre GL+Ma rtin+PG+Planetiler+osm2pgsql+... Learn tools needed to have your own map s erver. DTSTAMP:20260602T160506Z LOCATION:A11 SUMMARY:Custom tile servers with MapLibre/Martin/Planetiler - base and over lays Workshop — Yuri Astrakhan\, Bart Louwers URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/9EYUKT/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-bf26aa35-d449-5eab-99b8-fc11f283a861@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T140000 DTEND;TZID="+03:00":20260703T180000 DESCRIPTION:GDAL 3.11 introduced a new command line interface (CLI)\, simpl y called "gdal"\, supplementing the traditional well-known GDAL utilities (gdal_translate\, ogr2ogr\, etc.)\, to provide users with a more uniform\, predictable and user-friendly experience.\nThis workshop will give the op portunity to participants to get a hands-one experience to discover the ca pabilities of the new CLI through a series of exercices\, including how to leverage them from Python. DTSTAMP:20260602T160506Z LOCATION:A12 SUMMARY:GDAL new command line interface: introduction and advanced topics — Even Rouault\, Seth Girvin URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/PR7HNK/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-290bbd49-8c5a-5b4b-8323-c1b12b53e7a8@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T140000 DTEND;TZID="+03:00":20260703T180000 DESCRIPTION:GeoNode is an open source web platform for the development of i nteroperable spatial data infrastructures.\nThe workshop will provide an i ntroduction to GeoNode starting with an overview of its functionalities fo r managing\, data\, users and documents covering also more advanced concep ts. DTSTAMP:20260602T160506Z LOCATION:A13 SUMMARY:Introduction to GeoNode — Mattia Giupponi URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/HAWYBQ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-b144ee2d-f9fa-5afc-b35a-8e279d6d9213@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T140000 DTEND;TZID="+03:00":20260703T180000 DESCRIPTION:iTowns is an open-source\, community-driven web framework desig ned for geospatial\ndata visualization\, navigation and interaction. It pr ovides seamless 3D\nrendering in a single\, integrated package. Sponsored by the french National\nMap agency (IGN) and Ciril Group\, iTowns benefits from institutional\nand industry support to ensure long-term development and innovation.\nTechnique\n\nBuilt with extensibility and interoperabilit y in mind\, iTowns out-of-the-box\nsupports commonly-used OGC's open forma ts and protocols. This includes:\n- fetching imagery and elevation data fr om WMS\, WMTS and TMS servers\n- streaming large 3D datasets: 3D Tiles\, p ointclouds\; ...\n- importing various vectors formats: vector tiles\, geoJ SON\, GPX\, ...\n- and those requested by the community! DTSTAMP:20260602T160506Z LOCATION:A02 SUMMARY:iTowns\, a JavaScript 3D data visualization framework : from the fi rst steps to the creation of a complex 3D geographic web service — laven ant URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/EXUYUS/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-d618a0c5-5ca1-580d-95b9-4c9d870b08af@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T140000 DTEND;TZID="+03:00":20260703T180000 DESCRIPTION:This workshop will introduce the GeoTools and JTS Java librarie s to developers who are looking to create portable scripts for cleaning\, transforming and analyzing spatial data. GeoTools is a powerful geospatia l library that allows you to read and write a wide range of vector and ras ter data formats. It wraps the JTS library to make features out of geometr y objects from the JTS library by adding attributes\, it also provides OGC compliant styling of those features and rasters (as seen in the GeoServer web maps server). DTSTAMP:20260602T160506Z LOCATION:Info lab 1 SUMMARY:Writing spatial data utilities with GeoTools and JTS — Ian Turton URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/GSREMZ/ END:VEVENT BEGIN:VEVENT UID:pretalx-fe2026-ec34c4b4-a335-51ee-a891-3316f0a6d3ce@2026.europe.foss4g. org DTSTART;TZID="+03:00":20260703T140000 DTEND;TZID="+03:00":20260703T160000 DESCRIPTION:Mapbender is a great open source solutions for creating intuiti ve and high-performance WebGIS applications. Mapbender offers a set of too ls that you can combine.\nThis software solution enables users to quickly and easily publish applications online without having to write a single li ne of code. DTSTAMP:20260602T160506Z LOCATION:info lab 2 SUMMARY:Create great Web Applications with Mapbender — Astrid Emde URL:https://talks.osgeo.org/foss4g-europe-2026-workshops/talk/NZ7U8B/ END:VEVENT END:VCALENDAR