The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Machine Learning-Powered Flood Intelligence: A Scalable Sentinel-1 SAR Pipeline for Near-Real-Time Inundation Mapping and Disaster Informatics (AGU25)

Machine Learning-Powered Flood Intelligence: A Scalable Sentinel-1 SAR Pipeline for Near-Real-Time Inundation Mapping and Disaster Informatics

Reda Amer, University of Missouri St Louis, St Louis, MO, United States
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