TU2.R1.1
Updating Static Lake Inventories with Semi-Supervised Learning and Sentinel-2: A UK-Wide Demonstration
Shagun Garg, Wanli Ma, Sivasakthy Selvakumaran, Edoardo Borgomeo, University of Cambridge, United Kingdom
Session:
TU2.R1: Inland Waters IV Oral
Track:
Land Applications
Location:
TBD
Presentation Time:
Tue, 11 Aug, 11:00 - 11:15
Presentation
Discussion
Resources
No resources available.
Session TU2.R1
TU2.R1.1: Updating Static Lake Inventories with Semi-Supervised Learning and Sentinel-2: A UK-Wide Demonstration
Shagun Garg, Wanli Ma, Sivasakthy Selvakumaran, Edoardo Borgomeo, University of Cambridge, United Kingdom
TU2.R1.2: Scattering Physics Sets Hard Limits on Supervised Learning for SAR Flood Mapping
Bingyu Zhao, Xinyi Shen, Maopu Xu, University of Wisconsin-Milwaukee, United States; Albert Kettner, University of Colorado Boulder, United States; Guy Schumann, Paul Bates, University of Bristol, United Kingdom; Yuei-An Liou, National Central University, Taiwan; Emmanouil Anagnostou, University of Connecticut, United States
TU2.R1.3: BENCHMARKING SWOT DISCHARGE ESTIMATES AGAINST MODEL AND GAUGE DATA ACROSS SOUTH AMERICA
Laila Jover, University of Virginia, United States; Augusto Getirana, NASA, United States; Sydney Crisanti, John B Eylander, U.S. Army Corps of Engineers, United States; Collin Gleason, Heejin An, University of Massachusetts Amherst, United States; Ivan Hellwig, Mariana Sosa, Subsecretary of Water Resources, Argentina; Waldo Lavado, National Meteorological and Hydrological Service, Peru; William Santini, Jean-Michel Martinez, HYdro-geochemistry of the AMazonian Basin (HYBAM), France; Jorge Luis Sanchez Lozano, Aquaveo LLC, United States; Eduardo Dose, Entidad Binacional Yacyreta, Paraguay; Venkataraman (Venkat) Lakshmi, University of Virginia, United States
Contacts