IEEE GRSS
First Slide
2026 IEEE International Geoscience and Remote Sensing Symposium
9 - 14 August 2026 • Washington, D.C.
TUP1.PJ: Soils: Soils and Soil Moisture
Poster
Tue, 11 Aug, 09:45 - 11:00
Location: TBD
Session Type: Poster
Track: Land Applications
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TUP1.PJ.3: HIGH-RESOLUTION SURFACE SOIL MOISTURE MAPPING USING RANDOM FOREST AND SENTINEL-1 SAR WITH ENVIRONMENTAL DATA
Su-Bin Ha, Ye-Young Kim, Gwang-Woo Oh, Pukyong National University, Korea (South); Moung-Jin Lee, Korea Environment Institute, Korea (South); Seung-Kuk Lee, Pukyong National University, Korea (South)

TUP1.PJ.5: ANALYZING THE PRIMARY DRIVERS OF SOIL SPECTRAL VARIANCE IN TIME SERIES
Paul Karlshoefer, Uta Heiden, German Aerospace Center, Germany

TUP1.PJ.6: DIVERGENT DRIVERS OF UNCERTAINTY IN MAPPING CHINA’S SOIL ORGANIC CARBON AND A ROBUST FUSION STRATEGY
Xunjie Ma, Xiaojing Liu, Rongrong Ge, Jiayi He, Sichuan Agricultural University, China

TUP1.PJ.7: Understanding Multifrequency SAR Sensitivities to Soil Moisture Dynamics and Crop Growth from NISAR and Sentinel-1 Missions in North-Central Florida
Michelle Prieto-Sanchez, Laura Almendra, Jasmeet Judge, Mawiyah Abdelkarim, University of Florida, United States; Alejandro Monsivais Huertero, Instituto Politecnico Nacional, Mexico; Sarah Daly, Washington University in St. Louis, United States

TUP1.PJ.8: Integrating Temporal and Spatial Strengths: Advancing High-Resolution Global Soil Moisture Gap-Filling through POBI and NSTI Synergy
ZIYUE ZHU, University of Virginia, United States; John Eylander, Sydney Crisanti, U.S. Army Corps of Engineers, United States; Venkataraman Lakshmi, University of Virginia, United States

TUP1.PJ.9: A DEEP LEARNING FRAMEWORK FOR FARM-SCALE SOIL MOISTURE RETRIEVALS: A CASE STUDY FOR A DATA-SCARCE REGION
Hamza Rafique, Abubakr Muhammad, Lahore University of Management Sciences (LUMS), Pakistan

TUP1.PJ.10: QUASI-DAILY 30 M SOIL MOISTURE RETRIEVAL FROM SENTINEL-1 AND HARMONIZED LANDSAT AND SENTINEL-2 TIME SERIES USING A TRANSFORMER MODEL
Junjie Li, Hankui Zhang, South Dakota State University, United States

TUP1.PJ.11: ROOT ZONE SOIL MOISTURE MAPPING USING MACHINE LEARNING WITH L- AND P-BAND PASSIVE MICROWAVE OBSERVATIONS
Luisa Fernanda White Murillo, Monash University, Australia; Jifu Yin, University of Maryland, United States; Jeffrey Walker, Monash University, Australia; Xiwu Zhan, NOAA NESDIS Center for Satellite Applications and Research, United States; Jicheng Liu, Yan Zhou, University of Maryland, United States

TUP1.PJ.12: A SOIL MOISTURE-ASSISTED MOSAICKING ALGORITHM FOR GENERATING LARGE-AREA LUTAN-1 SAR MOSAICS
Jian Wang, Lei Zhao, Yaxiong Fan, Erxue Chen, 1. Institute of Forest Resource Information Techniques, Chinese Academy of Forestry; 2. State Key Laboratory of Efficient Production of Forest Resources, Key Laboratory of Forestry Remote Sensing and Information System of NFGA., China