IGARSS 2025 || Brisbane, Australia || 3

TUP1.PT.1: HIGH SPATIO-TEMPORAL RESOLUTION SOIL MOISTURE NOWCASTING AT MULTIPLE DEPTHS WITH DATA-DRIVEN APPROACHES

Yuxi Zhang, Niranjan Manikku Acharige, Sebastian Haan, Jie Wang, Xinglong Zou, Thomas Bishop, The University of Sydney, Australia

TUP1.PT.2: COMPARATIVE ANALYSIS OF MACHINE LEARNING ALGORITHMS AND PHYSICAL MODELS FOR SOIL MOISTURE RETRIEVAL USING UNMANNED AERIAL VEHICLES

Yawei Xu, Hui Lu, Tsinghua University, China; Jeffrey Walker, Nan Ye, Monash University, Australia; Jiaxin Tian, Junkun Liang, Tsinghua University, China

TUP1.PT.3: RESEARCH ON COLLABORATIVE RETRIEVAL OF SOIL MOISTURE UTILIZING MICROWAVE REMOTE SENSING BASED ON BP NEURAL NETWORK

Chaoyang Bian, University of Electronic Science and Technology of China, China; Qiaofeng Zhang, Inner Mongolia Normal University, China; Jian Wang, Chinese Academy of Sciences, China; Hao Guan, Tongtong Lu, Fang Huang, University of Electronic Science and Technology of China, China

TUP1.PT.4: Footprint Soil Moisture Estimated From Cosmic-Ray Neutron Sensing Observation Using Long Short-Term Memory (LSTM) Method

Dazhi Li, Shanxi Normal University, China; Zebin Zhao, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, China; Jiaqi Sun, Shanxi Normal University, China

TUP1.PT.5: Preparing for Reanalysis: Generating spatially and temporally continuous AMSR-E/2 soil moisture time series by ConvLSTM2D

Visakh Sivaprasad, Mehdi Rahmati, Forschungszentrum Jülich, Germany; Anne Springer, University of Bonn, Germany; Harry Vereecken, Carsten Montzka, Forschungszentrum Jülich, Germany

TUP1.PT.6: AI-Based Detection of Water Content in GPR Radargrams: Transfer Learning Based Adaptation

Omar Shouman, Shaimaa Hassanein, Qatar University, Qatar; Essam Heggy, University of Southern California, United States; Tamer Khattab, Qatar University, Qatar

TUP1.PT.7: RESEARCH ON SOIL MOISTURE INVERSION METHODS BASED ON REMOTE SENSING DATA

Li Jiaqi, Ji ZhenYuan, Zhang Yun, Huang YanKun, Harbin Institute of Technology, China; Do Yong, Li YaoHua, China Mobile Chengdu Institute of Research and Development, China

TUP1.PT.8: ROOT-ZONE SOIL MOISTURE ESTIMATION USING HIGH RESOLUTION L-BAND DATA AND MACHINE LEARNING TECHNIQUES

Mostafa Rahimi Jamnani, Jeffrey P. Walker, Xiaoling Wu, Monash University, Australia; In-Young Yeo, The University of Newcastle, Australia; Noor Ul Ain Ayaz, Meng Cao, Monash University, Australia

TUP1.PT.9: A NEW SOIL MOISTURE DOWNSCALING METHOD CONSIDERING SURFACE HETEROGENEITY

Panshan Wang, Jiangyuan Zeng, Aerospace Information Research Institute, Chinese Academy of Sciences, China; Xiangjin Meng, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, China; Hongliang Ma, Department of Biology, Terrestrial Ecology and Center of Volatile Interactions, University of Copenhagen, China; Chunlin Zhang, Aerospace Information Research Institute, Chinese Academy of Sciences, China; Haiyun Bi, Institute of Geology, China Earthquake Administration, China

TUP1.PT.10: MULTI-SCALE TRANSFER LEARNING FOR HIGH-RESOLUTION SOIL MOISTURE RETRIEVAL IN DATA-SCARCE REGIONS

Liujun Zhu, Qi Cai, Xiaoji Shen, Hohai University, China; Jeffrey Walker, Monash University, Australia

TUP1.PT.11: SURFACE SOIL MOISTURE RETRIEVAL BASED ON MICROWAVE REMOTE SENSING COUPLING PHYSICAL AND MACHINE LEARNING MODELS

Zhenghao Li, School of Geodesy and Geomatics, Wuhan University, China; Qiangqiang Yuan, Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University, China

TUP1.PT.12: IMPACT OF OBJECTIVE FUNCTION SELECTION ON THE ACCURACY OF SOIL MOISTURE RETRIEVAL USING UAVSAR IMAGERY

Shilpa Koyyan, Dongryeol Ryu, Andrew W. Western, The University of Melbourne, Australia; D. Nagesh Kumar, Indian Institute of Science, India