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: Application and Challenges of a Machine Learning-Based Zero-Order Basin Extraction Method for Preventive Maintenance Against Large-Scale Disasters During Havey Rainfall: A Case Study the 2024 Noto Peninsula Heavy Rain (AGU25)

Application and Challenges of a Machine Learning-Based Zero-Order Basin Extraction Method for Preventive Maintenance Against Large-Scale Disasters During Havey Rainfall: A Case Study the 2024 Noto Peninsula Heavy Rain

Mitsuru Yabe1, Shunsuke Hamada2, Dai Nobuoka2, Natsumi Itoya3 and Yasunori Katsume1, (1)OYO Corporation, Disaster Prevention and Infrastructure Business Division, Saitama, Japan, (2)OYO Corporation, DX Promotion Headquarters, Tokyo, Japan, (3)OYO Corporation, Disaster Risk Reduction Business Division, Saitama, Japan