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: California-wide High-Resolution Building Footprint Mapping Using Scalable Deep Learning (AGU25)

California-wide High-Resolution Building Footprint Mapping Using Scalable Deep Learning

Akash Awasthi1, Kyle Kristian Kabasares2, Hirofumi Hashimoto3, Khuong H Tran4, Pratima Khatri-Chhetri5, Scott Horner6, Wen Yip2, Ian G Brosnan7, Taejin Park8 and akash awasthi, (1)University of Houston, Houston, United States, (2)Bay Area Environmental Research Institute, Moffett Field, United States, (3)NASA Ames Research Center, Moffett Field, CA, United States, (4)South Dakota State University, Geospatial Sciences Center of Excellence (GSCE), Department of Geography & Geospatial Sciences, Brookings, SD, United States, (5)Bay Area Environmental Research Institute Moffett Field, Moffett Field, United States, (6)NASA Ames Research Center, Moffett Field, United States, (7)NASA Ames Research Center, Earth Science Division, Moffett Field, CA, United States, (8)NASA Ames Research Center/Bay Area Environmental Research Institute, Moffett Field, United States