TUP.P22.1: COULD L-BAND SOIL MOISTURE PRODUCTS CAPTURE THE SOIL MOISTURE CLIMATOLOGY VARIATIONS IN TROPICAL RAINFORESTS?
Hongliang Ma, State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, China; Jiangyuan Zeng, Aerospace Information Research Institute, Chinese Academy of Sciences, China; Nengcheng Chen, Xiang Zhang, National Engineering Research Center of Geographic Information System, China University of Geosciences (Wuhan), China; Xiaojun Li, Jean-Pierre Wigneron, INRAE, UMR1391 ISPA, Université de Bordeaux, France
TUP.P22.2: An Assessment of SMAP soil moisture retrieval algorithm for the Amazon rainforest region
Kyeungwoo Cho, Georgia Institute of Technology, United States; Robinson Negron-Juarez, Lawrence Berkeley National Laboratory, United States; Andreas Colliander, Jet Propulsion Laboratory, California Institute of Technology, United States; Eric Cosio, Norma Salinas, Pontifical Catholic University of Peru, Peru; Alessandro de Araujo, Brazilian Agricultural Research Corporation (EMBRAPA), Brazil; Jingfeng Wang, Georgia Institute of Technology, United States
TUP.P22.3: SUBSURFACE SOIL MOISTURE OBSERVATION USING SOFTWARE-DEFINED RADAR MOUNTED ON A UAV AND COMPARISON WITH NUMERICAL EM SIMULATIONS
Asem Melebari, Piril Nergis, Mahta Moghaddam, University of Southern California, United States
TUP.P22.6: VALIDATION OF SATELLITE SOIL MOISTURE PRODUCTS IN CHINA USING GROUND-BASED OBSERVATIONS
Yawei Xu, Hui Lu, Tsinghua University, China; Aihui Wang, Panpan Yao, Chinese Academy of Sciences, China
TUP.P22.7: A SOIL MOISTURE DOWNSCALING RESIDUAL DENSE NETWORK CONSIDERING SPATIOTEMPORAL RELATIONSHIP
Yingtao Wei, Liupeng Lin, Jie Li, Qiangqiang Yuan, Wuhan University, China
TUP.P22.8: SPATIOTEMPORAL PATTERNS AND INFLUENCING FACTORS OF SOIL MOISTURE AT A GLOBAL SCALE
Chenchen Peng, Jiangyuan Zeng, Aerospace Information Research Institute, China; Kun-Shan Chen, Guilin University of Technology, China; Hongliang Ma, INRAE, Avignon Universite, France; Haiyun Bi, Institute of Geology, China
TUP.P22.9: MACHINE LEARNING BASED HIGH RESOLUTION SOIL MOISTURE (ML-HRSM) FOR IDENTIFYING PREVENTED PLANTING FIELDS
zhengwei Yang, Patrick Willis, USDA/NASS, United States; Jingyi Huang, Zhou Zhang, University of Wisconsin - Madison, United States
TUP.P22.10: MULTI-SOURCE REMOTE SENSING OF SOIL MOISTURE PROFILES – A CASE STUDY OVER MONTICELLO, UTAH
Jinyang Du, John Kimball, University of Montana, United States; Christopher Jarchow, RSI EnTech, LLC, United States; Deborah Steckley, U.S. Department of Energy Office of Legacy Management, United States
