TU2.R7.2

TRANSFER LEARNING FOR GLOBAL SOIL MOISTURE RETRIEVAL FROM SENTINEL-1 WITH LIMITED GROUND SAMPLES

Liujun Zhu, Junjie Dai, Hohai University, China; Jeffrey Walker, Monash University, China
Session:
TU2.R7: Active Remote Sensing of Soil Moisture Oral
Track:
Land Applications
Location:
Room G
Presentation Time:
Tue, 18 Jul, 10:27 - 10:39 Pacific Time (UTC -7)
Session Co-Chairs:
Jasmeet Judge, University of Florida and Thomas Jagdhuber, German Aerospace Center
Session Manager:
Shubham Awasthi
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Session TU2.R7
TU2.R7.1: STANDALONE SAR SOIL MOISTURE RETRIEVAL USING RADAR VEGETATION INDICES
Shilpa K., D. Nagesh Kumar, Indian Institute of Science, Bangalore, India; Dongryeol Ryu, The University of Melbourne, Australia
TU2.R7.2: TRANSFER LEARNING FOR GLOBAL SOIL MOISTURE RETRIEVAL FROM SENTINEL-1 WITH LIMITED GROUND SAMPLES
Liujun Zhu, Junjie Dai, Hohai University, China; Jeffrey Walker, Monash University, China
TU2.R7.3: ESTIMATING SOIL MOISTURE BY SENTINEL-1, SENTINEL-2 AND PRISMA DATA: ASSESSMENT OF RESULTS AND COMPARISON WITH IN-SITU MEASUREMENTS
Giovanni Nico, Consiglio Nazionale delle Ricerche (CNR), Italy; Olimpia Masci, DIAN S.r.l., Italy; Nuno Cirne Mira, Academia Militar, Portugal; João Catalão, Pedro Mateus, Universidade de Lisboa, Portugal
TU2.R7.4: EXTENDED ALPHA APPROXIMATION METHOD FOR THE RETRIEVAL OF SOIL MOISTURE UNDER DYNAMIC VEGETATION BY MULTI-INCIDENCE ANGLE SENTINEL-1
David Mengen, Research Centre Julich, Germany; Anna Balenzano, National Research Council of Italy (CNR), Italy; Thomas Jagdhuber, German Aerospace Center (DLR), Germany; Francesco Mattia, National Research Council of Italy (CNR), Italy; Harry Vereecken, Carsten Montzka, Research Centre Julich, Germany
TU2.R7.5: THE NISAR TIME-SERIES RATIO SOIL MOISTURE RETRIEVAL ALGORITHM
Jeonghwan Park, NASA GSFC/GST, United States; Rajat Bindlish, NASA GSFC, United States; Dustin Horton, Mohammad Al-Khaldi, Joel Johnson, The Ohio State University, United States
Resources
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