Presentation
Talk: Earth Embeddings: Harnessing the Information in Earth Observation Data with Machine Learning
DescriptionMachine learning (ML) for Earth Observation (EO) data is revolutionizing the speed and scope at which science and policy can operate — filling critical data gaps across fields such as ecology and development economics. In this talk, I will outline a class of ML for EO models that distill global satellite data into compact, multi-purpose representations of the Earth. I’ll trace the recent evolution of these “Earth embedding” models, from early image embeddings designed to capture the unique characteristics of satellite imagery, to an emerging class of location encoders that serve as implicit neural representations of EO data. After discussing the impact-driven goals and methodological details of these models, I'll conclude by discussing my longer term vision of building Earth embedding models to unlock new scales of science.
Event Type
Frontiers
TimeThursday, 14 August 20258:00am - 8:45am PDT
LocationWest Building, Rooms 301-305
Research & Education
Livestreamed
Recorded
Artificial Intelligence/Machine Learning
Computer Vision
Digital Twins
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