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: Learning with less: label-efficient land cover classification at very high spatial resolution using semantic stratification and self-supervised deep learning (AGU25)

Learning with less: label-efficient land cover classification at very high spatial resolution using semantic stratification and self-supervised deep learning

Dakota Hester1, Vitor Martins1, Lucas Borges Ferreira2 and Thainara Lima1, (1)Mississippi State University, Department of Agricultural and Biological Engineering, Mississippi State, MS, United States, (2)Mississippi State University, North Mississippi Research and Extension Center, Tupelo, MS, United States