IEEE GRSS
First Slide
2026 IEEE International Geoscience and Remote Sensing Symposium
9 - 14 August 2026 • Washington, D.C.
FRP1.PJ: Earth System Science and Applications Based on a Decade of NASA Soil Moisture Active Passive (SMAP) Satellite Mission Science Data Products
Poster
Fri, 14 Aug, 09:45 - 11:00
Location: TBD
Session Type: Poster
Track: Community Contributed Themes
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FRP1.PJ.2: A Semi-Synthetic Deep Learning-Based RFI Detection Approach for SMAP Satellite
Ahmed Manavi Alam, North Carolina State University, United States; Mehmet Kurum, University of Georgia, United States; Ali Gurbuz, North Carolina State University, United States

FRP1.PJ.3: ASSESSING LAND SURFACE ROUGHNESS EFFECTS ON SMAP RADAR OBSERVABLES USING 1-M LIDAR-DERIVED DIGITAL ELEVATION MODELS
Tianlin Wang, Simon Yueh, Xiaolan Xu, Jet Propulsion Laboratory, United States

FRP1.PJ.5: EFFECT OF ALBEDO, COST FUNCTION, AND BIOMASS ASSUMPTIONS ON SMAP VEGETATION MOISTURE RETRIEVAL PERFORMANCE
Jinyang Du, Alexandra Konings, Stanford University, United States

FRP1.PJ.6: SMAP RELIABLY DETECTS THE SIGN OF LAND COVER CHANGE IMPACT ON SOIL MOISTURE
Runze Zhang, University of Idaho, United States; Xiaolan Xu, NASA Jet Propulsion Laboratory, United States; Meng Zhao, University of Idaho, United States

FRP1.PJ.7: LIDA-3: A Remote Sensing Data Assimilation Framework for Mapping Coupled Water-Energy-Carbon Cycles
Leila Farhadi, Asif Mahmood, The George Washington University, United States

FRP1.PJ.8: A JOINT RETRIEVAL OF SOIL MOISTURE AND VEGETATION PARAMETERS FROM SOIL MOISTURE ACTIVE PASSIVE
Jaese Lee, Gwangju Institute of Science and Technology, Korea (South); Simon Yueh, Jet Propulsion Laboratory, California Institute of Technology, United States; Dara Entekhabi, Massachusetts Institute of Technology, United States; Andreas Colliander, Finnish Meteorological Institute, Finland; Jungho Im, Ulsan National Institute of Science and Technology, Korea (South); Chang-Hwan Park, Ajou University, Korea (South); Hyunglok Kim, Gwangju Institute of Science and Technology, Korea (South)

FRP1.PJ.9: RECONSTRUCTION AND PREDICTION OF MISSING RADIOMETRIC PARAMETERS FOR MICROWAVE SATELLITE SYSTEMS WITH METEOROLOGICAL AI FOUNDATION MODELS
Donggeon Lee, Seulgi Kim, Subin Kim, Hyunglok Kim, Gwangju Institute of Science and Technology, Korea (South)

FRP1.PJ.10: Utilizing SMAP and explainable machine learning to detect nonlinear interrelationships among river flood attributes and drivers across inland U.S. watersheds
Piyush Dahal, Abhinanda Roy, Ebrahim Ahmadisharaf, Florida State University, United States; Ehsan Jalilvand, Sujay Kumar, National Aeronautics and Space Administration, United States; Narendra Das, Michigan State University, United States

FRP1.PJ.11: THE L-BAND VEGETATION OPTICAL DEPTH IN THE U.S. CORN BELT TRANSITIONS FROM REPRESENTING SOIL SURFACE ROUGHNESS TO THE VEGETATION WATER COLUMN
Brian Hornbuckle, Matt Kavanaugh, Iowa State University, United States