BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:America/Los_Angeles X-LIC-LOCATION:America/Los_Angeles BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:19700308T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:19701101T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260417T190156Z LOCATION:West Building\, Rooms 301-305 DTSTART;TZID=America/Los_Angeles:20250814T080000 DTEND;TZID=America/Los_Angeles:20250814T084500 UID:siggraph_SIGGRAPH 2025_sess594_ftalk_105@linklings.com SUMMARY:Talk: Earth Embeddings: Harnessing the Information in Earth Observ ation Data with Machine Learning DESCRIPTION:Esther Rolf (University of Colorado Boulder)\n\nMachine learni ng (ML) for Earth Observation (EO) data is revolutionizing the speed and s cope at which science and policy can operate — filling critical data gaps across fields such as ecology and development economics. In this talk, I w ill 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 embed dings designed to capture the unique characteristics of satellite imagery, to an emerging class of location encoders that serve as implicit neural r epresentations of EO data. After discussing the impact-driven goals and me thodological details of these models, I'll conclude by discussing my longe r term vision of building Earth embedding models to unlock new scales of s cience.\n\nInterest Area: Research & Education\n\nRecording: Livestreamed, Recorded\n\nKeyword: Artificial Intelligence/Machine Learning, Computer V ision, Digital Twins\n\nRegistration Category: Full Conference, Virtual Ac cess, Experience\n\n END:VEVENT END:VCALENDAR