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: Integrating Multi-Angle SIF and Multi-Source Vegetation Indices in a Physically-Guided Deep Learning Framework for Soybean Yield Estimation (AGU25)

Integrating Multi-Angle SIF and Multi-Source Vegetation Indices in a Physically-Guided Deep Learning Framework for Soybean Yield Estimation

Yongyuan Gao1, Ke Li2, Dalei Hao3, Yachang He2 and Yelu Zeng2, (1)CAU China Agricultural University, College of Land Science and Technology, Beijing, China, (2)China Agricultural University, Beijing, China, (3)Pacific Northwest National Laboratory, Atmospheric, Climate, & Earth Sciences Division, Richland, United States