IN FOCUS: MLSpAnFOSS 2026 Explores Machine Learning and Spatial Analysis

Next month (Feb 18–20), the historic city of Krakow, Poland will welcome MLSpAnFOSS 2026– the Machine Learning and Spatial Analysis with Free Open Source Software Conference. The inaugural GRSS event brings together researchers, developers, practitioners, and educators dedicated to advancing machine learning and spatial analysis using freely available software and data. Over three days, attendees will explore cutting-edge topics at the intersection of artificial intelligence, machine learning, and spatial analysis, showcasing how open-source tools are transforming research and practice across domains such as environmental monitoring, natural resource management, remote sensing, and urban analytics.

Focus on Machine Learning and AI

The MLSpAnFOSS conference succeeded the SpAnFOSS 2019 conference, which focused solely on spatial analysis using free software. This time, the conference is being organized for the entire local region and will focus on machine learning, including artificial intelligence. 

“We are all committed to advancing accessible, open-software-based geospatial science and coordinating professional involvement,” says Dr. Paweł Netzel, Chair of the IEEE GRSS Poland Chapter, and conference organizer. “By bringing together attendees and experts from across the region, we encourage collaboration and support the expansion of ideas and applications in specialized analysis. Participants will see presentations on applications of advanced environmental analysis using freely accessible software, and they will become familiar with new approaches based on open-source tools during hands-on workshops.” he adds.

Chapter Synergy Enabled Conference Development 

A compelling dimension of MLSpAnFOSS 2026 lies in the synergy among the three IEEE Geoscience and Remote Sensing Society (GRSS) Chapters (Poland, Austria, and Germany), supported by the University of Agriculture in Krakow and the Open Source Geospatial (OSGeo) community, which have combined resources and expertise to bring this conference to fruition. Their partnership underscores how chapters can work collectively to shape discourse on open science, create inclusive scholarly platforms, and cultivate networks that empower researchers at all career stages.

“As the newly created Poland chapter, we invited the newly created Austria chapter and the well-established Germany chapter to participate,” Dr. Netzel explains. “Additionally, we invited colleagues from the Czech Republic. The guiding principle behind this collaboration is to bring our communities together. The goal is to create a forum for collaboration between geographically close yet separate communities,” he adds. 

“Coordinating across chapters also allowed us to pool complementary expertise, broaden the scientific scope, and create a conference that is both technically rigorous and genuinely inclusive,” explains Dr. Shaily, Gandhi Senior Postdoctoral Researcher at the Geosocial Artificial Intelligence Research Group, Interdisciplinary Transformation University Austria, and Chair of the IEEE GRSS Austria Chapter. The program also reflects the growing role of urban data science, where machine learning, raster-based spatial analysis, and open-source geospatial tools are applied to analyze complex urban environments using remote sensing and spatial datasets.

Robust Technical Program 

MLSpAnFOSS 2026 aims to foster a vibrant and inclusive forum where participants can both share their latest work and learn new methods directly applicable to real-world spatial challenges. A core emphasis of the conference is the accessibility of analytical methods. MLSpAnFOSS highlights frameworks, libraries, and workflows that are open-source, freely distributable, and modifiable. This ethos supports broader participation from researchers, students, and professionals who may otherwise face barriers due to licensing costs or restrictive software ecosystems. 

The conference will span multiple session types: plenary talks, technical sessions, poster presentations, and hands-on workshops designed to teach participants essential techniques in a workshop setting. In addition to keynote and plenary sessions that set thematic directions and showcase high-impact research, there will be deep-dive oral presentations that spotlight recent advances in algorithms and applications. Poster sessions offer a more informal venue for one-on-one discussion and networking with peers. 

“Hot machine learning topics and spatial processing techniques will be discussed at the conference, such as GDAL, Quantum computation, land type classification, and GNSS,” says Dr. Qian Song, IEEE GRSS Germany Chapter Chair. “We have worked hard to develop an itinerary which will be interesting to a broad audience,” she adds.

Attendees can take part in a diverse set of hands-on, applied workshops spanning modern data science and geospatial technologies. The program includes an introduction to Federated Learning, guiding participants from traditional single deep learning models toward collaborative, privacy-preserving model federations. A practical Raster Calculator workshop explores how a single geospatial tool can support many analytical tasks through real-world examples. Participants can also engage in Quantum Computing for Remote Sensing, gaining conceptual and applied insight into how emerging quantum methods may transform Earth observation data processing. Finally, an Introduction to GDAL (Geospatial Data Abstraction Library) workshop familiarizes attendees with one of the most powerful and widely used libraries for spatial data management and analysis, emphasizing its versatility across geospatial workflows. 

“We’ve developed a robust technical program that combines strong theoretical foundations with hands-on, open-source workflows,” says Dr. Gandhi. “Attendees can expect practical exposure to machine learning and spatial analysis methods they can directly apply to real-world challenges, while also engaging with a community committed to transparency, accessibility, and collaboration,” she adds. 

Events Support Collaboration and Networking 

Beyond the technical program, MLSpAnFOSS 2026 facilitates a range of networking opportunities including social events, informal meet-ups, and community meals to encourage attendees to strengthen professional relationships and explore future collaborations. For many in the field, these interactions are as valuable as formal sessions, often leading to multi-institutional research efforts, open-source project contributions, or joint proposals for funding. The conference also provides a gateway for students and emerging professionals to connect with potential mentors and collaborators, expanding both their academic horizons and career prospects. GRSS is particularly interested in engaging young scientists at this event by promoting regional chapters and encouraging informal communication to build a strong network of contacts.

Registration is open…we hope to see you in Krakow!

MLSpAnFOSS 2026 not only showcases technological innovation but also champions a collaborative model of research that holds promise for the future of science. Conference attendees in Kraków will be within easy reach of the city’s beautifully preserved medieval Old Town, including the UNESCO-listed Main Market Square, Wawel Royal Castle, and historic churches and museums. Registration will remain open until February 15. 

“I’d like to encourage participation by anyone interested in exploring how open, community-led approaches to machine learning and spatial analysis can accelerate discovery, broaden participation, and translate computational advances into tools that serve society at large,” says Dr. Netzel. For more information and to register, visit mlspanfoss.org.