IGARSS 2026 || Washington, D.C. || 9

WE4.R9: Physics-Informed Machine Learning in Remote Sensing (4/4)

Wednesday, 12 August, 16:15 - 17:30

Location: Fairchild

Session Type: Oral

Session Co-Chairs: Davide De Santis, and Grigorios Tsagkatakis,

Track: Community Contributed Themes

Wed, 12 Aug, 16:15 - 16:30

WE4.R9.1: Drought-induced changes in groundwater-surface water exchange at Lake Mead area

Mohammad Khorrami, Susanna Werth, Sonia Zehsaz, Manoochehr Shirzaei, Virginia Tech

Wed, 12 Aug, 16:30 - 16:45

WE4.R9.2: KGML-SM: knowledge-guided machine learning with soil moisture for drought-aware corn yield prediction

Xiaoyu Wang, Yijia Xu, Jingyi Huang, University of Wisconsin-Madison; Zhengwei Yang, Yanbo Huang, USDA; Rajat Bindlish, NASA; Zhou Zhang, University of Wisconsin–Madison

Wed, 12 Aug, 16:45 - 17:00

WE4.R9.3: A TRANSFORMER-BASED DEEP LEARNING MODEL FOR PRECIPITATION RETRIEVALS USING ATMS OBSERVATIONS ABOARD THE NOAA/JPSS SATELLITES

Liping Wang, Haonan Chen, Colorado State University; Pingping Xie, Janice Bytheway, NOAA

Wed, 12 Aug, 17:00 - 17:15

WE4.R9.4: PHYSICS-INFORMED GEO-AI FOR QUANTIFYING IRRIGATION WITHDRAWALS: APPLICATION TO THE CENTRAL VALLEY

Esmaeel Adrah, Kent State University; Luca Brocca, National Research Council; Manzhu Yu, Penn State University; He Yin, Kent State University

Wed, 12 Aug, 17:15 - 17:30

WE4.R9.5: PHYSICS-AWARE AI SURROGATE FOR CFD RETROPLUME INVERSION: FAST CITY-SCALE CO2 EMISSION MAPPING FROM SPARSE IOT AND EO INPUTS

Rabeb Naassaoui, David Petit, Metaplanet; Tony Bush, Noise Consultants; Sei Cabrol, Alain Retière, Everimpact