Matthew Hanson
Matthew Hanson is a Senior Applied Scientist at LGND, where he works on AI, geospatial data infrastructure, and semantic search for Earth observation. He has more than 30 years of experience in remote sensing, cloud-native geospatial systems, and open geospatial technologies, with previous roles at Element 84 and Development Seed.
Matt is a member of the STAC Steering Committee and has been an active contributor to the open geospatial community through work on STAC, STAC Workflows, CEOS-ARD, cloud-native geospatial architectures, and open-source software. He is a frequent speaker at FOSS4G and other international geospatial conferences, where he enjoys sharing practical lessons from building large-scale Earth observation systems.
His current interests include foundation models for remote sensing, vector embeddings, semantic search, AI-assisted geospatial workflows, and the future of open geospatial standards.
Sessions
STAC outgrew the 101. Catalogs, APIs, extensions, cloud-native formats, AI workflows — there are many ways in. This live Choose Your Own Adventure lets the room pick the path. You steer; STAC's core concepts come along for the ride.
Your STAC search returned 2 million scenes. Don't paginate, visualize. STAC aggregations turn a catalog into a coverage map: where, when, and how cloudy, before you load a single pixel. A new open-source tool shows how.
Everyone says "geo embeddings," but they mean three different things: models, representations, and systems. And "open" means five different things. A practical field guide to Clay, TESSERA, vector databases, and what's actually free to use.