Artificial Intelligence in Geoinformatics Domain Working Group


The Artificial Intelligence in Geoinformatics Domain Working Group (GeoAI DWG) explores how AI can improve maps and location-based services involving robots, the Internet of Things, and digital replicas of real-world objects. This group focuses on several key areas like healthcare, energy, autonomous vehicles, and city planning. It provides a public space for discussions about AI in geography, identifies standardization opportunities, and tackles interoperability challenges.

Sign-up for the GeoAI DWG mailing list to stay informed about the current and upcoming activities of this group.

Project Scope

The GeoAI DWG provides a public discussion forum the connects scientists, engineers, entrepreneurs, and leaders from academia, industry, and government. Group members document technology and policy issues concerning AI applications that utilize geospatial data, identify interoperability challenges and opportunities, and guide the adoption of OGC Standards.


AI in geoinformatics is more than just machine learning; it includes technologies like the Internet of Things, big data, cloud computing, and robotics to make machines more human-like in their understanding and actions. AI is key in improving mapping software, making machines smarter in decision-making, and better analyzing geographic data for uses such as studying environmental health and developing self-driving cars. However, ethical issues, lack of data, shortage of skilled workers, and the need for clearer and more compatible systems are barriers to using AI more widely. Addressing these issues by developing clear, ethically sound AI supported by trained professionals and strong policies is crucial for building trust and taking full advantage of AI in geography.


The GeoAI DWG will focus on activities such as collecting and analyzing AI applications and use cases within the geospatial community, identifying key requirements for OGC standards, designing interoperability experiments, and providing best practices for geospatial data management.

Training-DML SWG

This Standards Working Group (SWG) is chartered to develop the UML model and encodings for geospatial Machine Learning training data. The SWG released a conceptual model and is now working on creating encoding models based on GeoJASON and XML. This SWG is led by Wuhan University and Laboratoire d’Informatique de Grenoble and is only open to OGC Members.

Access the SWG

GeoAI Speaker Series

Discover groundbreaking research and applications at the intersection of Artificial Intelligence (AI) and geospatial technology with the OGC GeoAI Speaker Series. Each online session features a 30-minute presentation from a GeoAI thought leader, followed by a moderated question and answer period. These conversations will help the GeoAI community overcome challenges and identify new opportunities to build the future of location technology for the good of society. The GeoAI speaker series is open to both OGC Members and the general public.

Session 2 – June 17, 2024

The second session will feature a presentation from Dr. Michael Goodchild, Emeritus Professor of Geography at the University of California, Santa Barbara. The title of his talk is “Ethics in GeoAI” and will cover topics including uncertainty and privacy, fitness for use, ethics and user interfaces, and spatial heterogeneity.

Dr. Goodchild’s talk will be held during the GeoAI DWG session at the Montreal Member Meeting. Please see the GeoAI Speaker Series event page for more information.

Session 1 – May 15, 2024

The first session features Dr. Vipin Kumar, Regents Professor and Chair of the Department of Computer Science and Engineering at the University of Minnesota. His presentation is entitled “Knowledge-Guided Machine Learning: A New Framework for Accelerating Scientific Discovery and Addressing Global Environmental Challenges”.



AI/ML, Geospatial, GIS, Remote Sensing

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