2025-11-15 –, Node
Join us for an in-depth look at how Machine Learning (ML) models can be used to detect missing footway data in OSM.
Join us for an in-depth look at how Machine Learning (ML) models can be used to detect missing footway data in OSM. By finding missing marked crosswalks using ML, we can help point mappers to coverage gaps. We will discuss our technical approach as well as how we want to partner with local communities. We will also cover a unique approach to mapping these missing footways using the Rapid editor’s new Map Roulette integration.
Meta/Mapillary
I'm a passionate Geomatics Engineer, OpenStreetMap contributor and community builder. I love building maps and solving community problems by using my geospatial knowledge. I’m a strong believer that open data brings creativity, innovation and freedom to society. I evangelize open data initiatives and develop the OSM community growth strategies for Türkiye. Currently, I’m working as Project Manager at Meta’s Mapping team and based in London, United Kingdom.
Kurt Schellhase is a software engineer and machine learning expert at Meta. He is passionate about mapping transportation features such as roads, footways, and transit around the world. Based in Seattle (USA), Kurt is a frequent visitor to Europe and enjoys adventuring and “power walking” around the world.