Geospatial Foundation Models Workshop - Hosted by CARTO and Barcelona Supercomputing Center
- Date
- 2026-02-04
- Location
- Barcelona, Catalunya, Spain
- Host
- Personal
About this event
Geospatial foundation models are moving fast from research into real-world workflows, and this workshop is designed to help you make sense of what that actually means in practice. Hosted by CARTO and the Barcelona Supercomputing Center, this in-person gathering in Barcelona brings together people who care about the future of spatial analysis, machine learning, and applied geospatial work. If you work with maps, remote sensing, spatial data science, or AI systems, this is a chance to get closer to the ideas, tools, and conversations shaping the field right now. Expect a focused environment where technical curiosity, practical questions, and peer exchange all have a place. About the Event This workshop centers on geospatial foundation models: large-scale AI models trained on broad spatial and earth observation data that can support tasks like understanding imagery, extracting patterns, and accelerating geospatial analysis. Rather than treating the topic as hype, the event creates space to explore what these models are, where they are useful, and what challenges still need to be solved. Because it is hosted by organizations deeply connected to geospatial technology and advanced computing, the event is likely to be especially relevant for people who want substance over generalities. The setting suggests a workshop designed around informed discussion, shared learning, and concrete examples, not just high-level talk. The format is best understood as a workshop first, meetup second. That means attendees can expect both structured content and room for conversation. You are not just showing up to sit through a sequence of disconnected presentations; you are stepping into a room with others who are actively thinking about how foundation models could change spatial workflows, products, and research. What to Expect You can expect a morning built around a mix of expert context, practical framing, and community exchange. While the exact session breakdown is not provided, the workshop title and hosts make it clear that the focus will be on the emerging intersection of geospatial data, machine learning, and large-scale computational approaches. Likely themes of discussion may include: What geospatial foundation models are and how they differ from narrower task-specific models How these models relate to remote sensing, mapping, spatial prediction, and earth observation workflows Where they may already be useful in applied settings Current limitations, open questions, and implementation challenges How infrastructure and compute shape what is possible in this space Beyond the formal content, expect one of the most valuable parts of the event to be the quality of the room. With tags including community, networking, meetup, and social, this is not only about absorbing information. It is also about meeting people who are experimenting, building, researching, or trying to evaluate this fast-moving area for their own work. That makes the event useful whether you are deeply technical or still mapping the landscape. You may come away with new vocabulary, better questions, sharper judgment about the field, and a clearer view of who is working on what. Why Attend This workshop offers something especially useful right now: a chance to understand a fast-evolving topic in a setting that is grounded in the geospatial domain. There is no shortage of broad AI discussion, but far fewer spaces that focus specifically on what foundation models mean for spatial data, mapping, earth observation, and geospatial decision-making. Attending can help you: Build a more practical understanding of an important new technical direction Connect research ideas to applied geospatial use cases Pressure-test your assumptions with others in the field Meet peers and practitioners who share your interests Identify where the biggest opportunities and unknowns are today For researchers, this may be a valuable way to situate your work within a broader ecosystem. For practitioners, it can help you distinguish what is actionable now from what is still exploratory. For teams evaluating future capabilities, it is a strong opportunity to listen closely, ask better questions, and return with a more informed perspective. There is also real value in simply being in person for this conversation. Topics like this benefit from nuance, back-and-forth, and informal discussion. The most useful insights often come not only from the main session, but from the conversations before, after, and between segments. Practical Details The workshop takes place in person in Barcelona, Spain on Wednesday, February 4 at 9:30 AM GMT+1. The in-person format matters here: it supports deeper discussion, easier networking, and a more collaborative learning environment than a purely virtual session. Because this is a workshop format, it is worth arriving prepared to engage. If you already work with geospatial data, machine learning, remote sensing, or spatial applications, think about the questions you most want answered. If you are newer to the topic, come ready to listen for frameworks, examples, and terminology that can help you build a stronger foundation. A few useful ways to prepare: Review your current understanding of foundation models and where they may intersect with your work Be ready to talk briefly about your background or area of interest Bring specific questions about applications, limitations, or tooling Leave space for networking before and after the core program If geospatial AI is on your radar and you want an informed, focused entry point into the conversation, this workshop is a strong place to be. It brings together the right topic, the right setting, and the kind of audience that can make the discussion genuinely worthwhile.
Who should attend
This is for people who want a sharper, more practical understanding of where geospatial foundation models are heading and how they may affect real work. - You work in **geospatial analysis, GIS, mapping, or spatial data science** and want to understand how foundation models could change your workflows. - You are involved in **remote sensing or earth observation** and are curious about how large-scale models may support interpretation, extraction, or analysis tasks. - You build or evaluate **AI and machine learning systems** and want domain-specific insight into spatial use cases, constraints, and opportunities. - You are a **researcher, engineer, or technical practitioner** looking to connect current developments in geospatial AI with broader questions around data, compute, and deployment. - You lead or support a team exploring **future geospatial capabilities** and need a clearer view of what is promising, what is still early, and what questions to ask next. - You value **in-person technical community** and want to meet others in Barcelona who are thinking seriously about the intersection of geospatial work and foundation models.