About the Workshop
The rapid growth of geospatial data from remote sensing, IoT, and connected systems challenges traditional Geographic Information Systems (GIS) to deliver scalable, efficient, and reliable services. AI offers new opportunities to generate synthetic geospatial data, integrate heterogeneous sources, automate spatial reasoning, and enable real-time decision-making. Emerging approaches, including large language models (LLMs), geospatial foundation models, graph neural networks (GNNs), and AI agents, are opening new possibilities for intelligent GIS and environmental digital twins. However, these advances also raise challenges related to data quality, uncertainty, transparency, privacy, fairness, and regulatory compliance.
GIS-AI 2026 brings together researchers and practitioners to advance scalable, high-performance, and trustworthy GIS through AI, innovative architectures, data management, and edge computing. The workshop welcomes original research, novel methodologies, system designs, and practical applications addressing geospatial data generation, integration, intelligent analysis, real-time processing, and responsible AI.
Topics of Interest
We invite original contributions on, but not limited to, the following topics:
- AI-Driven GIS and Geospatial AI
- Large Language Models (LLMs), Generative AI, and Agentic AI for GIS
- Geospatial Foundation Models, Vision–Language Models, and Multimodal Geospatial AI
- Graph Neural Networks (GNNs), Graph-Based Learning, and Spatial Reasoning
- Knowledge Graphs (KGs), Neuro-Symbolic AI, and Semantic Geospatial Integration
- Geospatial and Environmental Digital Twins
- Synthetic Geospatial Data Generation, Augmentation, and Simulation
- Multi-Source Data Fusion, Data Quality, Anomaly Detection, and Uncertainty Management
- Spatiotemporal Prediction, Forecasting, Change Detection, and Spatial Generalization
- Real-Time Geospatial Analytics, Stream Processing, and Edge–Cloud Computing
- Scalable GIS Architectures, Geospatial Databases, and Distributed Data Management
- Geospatial Data Spaces, FAIR Data, Interoperability, and Semantic Standards
- IoT, Sensor Networks, Robotics, and Cyber-Physical Systems for GIS
- AI-Based Risk Assessment, Disaster Management, Environmental Monitoring, and Climate Resilience
- Smart Cities, Urban and Rural Planning, Biodiversity, and Ecosystem Monitoring
- AI-Driven Scientific Modelling, Scenario Generation, and Spatial Decision Support
- Geospatial AI Evaluation, Benchmarking, Explainability, and Reproducibility
- Trustworthy and Responsible AI, Privacy, Security, Fairness, and Regulatory Compliance
- Open-Source GIS, Geospatial MLOps, and Reproducible AI Workflows
Submission and Publication
We invite full research papers of up to 15 pages, prepared using the Springer format.
- Submission platform: Microsoft CMT – MEDES 2026
- Review process: At least three peer reviewers per paper.
- Evaluation criteria: Relevance, originality, technical soundness, significance, and presentation quality.
- Presentation requirement: At least one author of each accepted paper must attend MEDES 2026 and present the work.
Accepted papers will be presented at GIS-AI 2026 and included in the MEDES 2026 proceedings, planned for publication in Springer’s Communications in Computer and Information Science (CCIS) series, subject to the publisher’s requirements.
Important Dates
- Paper submission deadline: 20 October 2026
- Acceptance notification: 26 October 2026
- Camera-ready deadline: 1 November 2026
Journal Publication Opportunities
Selected papers presented at the conference may be invited to submit extended versions for consideration in special issues associated with the main conference:
Journal submissions will undergo the respective journals’ editorial and peer-review processes. An invitation does not guarantee acceptance.
Workshop Organizers
- Shareeful Islam, Anglia Ruskin University, UK
- Maryam Imani, Anglia Ruskin University, UK
- Akram Hakiri, University of Pau and Pays de l’Adour, France
- Marc Frincu, West University of Timișoara, Romania
Publication Ethics
All submissions must comply with established standards of research integrity. Plagiarism and inappropriate reuse of previously published material, including self-plagiarism, are not acceptable. Authors are encouraged to consult Miguel Roig’s guide to avoiding plagiarism.
Join us at GIS-AI 2026 to advance the next generation of scalable, intelligent, and trustworthy geospatial systems.
