IEEE GRSS
First Slide
2026 IEEE International Geoscience and Remote Sensing Symposium
9 - 14 August 2026 • Washington, D.C.
TUP1.PM: Soil Moisture: Ground to Space
Tuesday, 11 August, 09:45 - 11:00
Location: Poster Area M
Session Type: Poster
Track: Community Contributed Themes
Poster Area M

TUP1.PM.1: High resolution soil moisture based drought assessment: insights from the 2021 Southern La Plata River Basin drought
Bin Fang, Venkataraman Lakshmi, Laila Jover, Sebastian Marshall, University of Virginia, United States
Poster Area M

TUP1.PM.2: Physics-Informed Adaptive Transformer for High Resolution Soil Moisture Retrieval from Sentinel-1 Time Series
Jiaming Lyu, Yun Zhang, Zhiguo Liang, Yankun Huang, Xiuqing Wang, Harbin Institute of Technology, China
Poster Area M

TUP1.PM.3: HIGH-RESOLUTION SOIL MOISTURE FROM ORBITAL VSWIR IMAGING SPECTROSCOPY
Nayma Binte Nur, David R. Thompson, Philip G. Brodrick, Michael Turmon, Nimrod Carmon, Robert O. Green, Jet Propulsion Laboratory, California Institute of Technology, United States; Charles M. Bachmann, Rochester Institute of Technology, United States; Abigail M. Keebler, California Institute of Technology, United States
Poster Area M

TUP1.PM.4: Bayesian Soil Moisture Retrieval Using High-Resolution SAR
Lena Azimi, Weihang Li, Laura Bowling, Melba Crawford, James Garrison, Jinha Jung, Purude University, United States
Poster Area M

TUP1.PM.5: The use of active microwave remote sensing to produce high-resolution soil moisture at watershed scales
Jongmin Park, Korea National University of Transportation, Korea (South); Kiyoung Kim, Korea Institute of Hydrological Survey, Korea (South)
Poster Area M

TUP1.PM.6: MULTI-FREQUENCY INVERSION OF CANOPY AND SOIL MOISTURE VIA CUMULATIVE INSAR CLOSURE PHASE
Yuan-Kai Liu, Elizabeth Wig, Howard Zebker, Stanford University, United States
Poster Area M

TUP1.PM.7: Complementary Use of Surface Soil Moisture and Temperature for Subsurface Soil Moisture Retrieval
Emad Mashayekh, Leila Farhadi, The George Washington University, United States
Poster Area M

TUP1.PM.8: Physics-Regularized Deep Learning for Accurate Soil Moisture Estimation from Multi-Source Remote Sensing data
Noureddine JARRAY, RIADI Laboratory, National School of Computer Science, Manouba, Tunisia, Tunisia; Lilia Bennaceur FARAH, IPEIEM - Institut Préparatoire aux Études d'Ingénieurs El Manar Tunis, Tunisia, Tunisia; Raja Inoubli, RIADI Laboratory, Manouba School Of Engineering (MSE), University of Mannouba, 2010, Tunisia, Tunisia; Imed Riadh FARAH, Manouba School Of Engineering (MSE), University of Mannouba, 2010, Tunisia, Tunisia