TU1.R1.4
EVALUATING MACHINE LEARNING-BASED RIVER ICE DETECTION USING SENTINEL-3 SLSTR DATA
Baya Cherif, Marouane Temimi, Stevens Insitute of Technology, United States
Session:
TU1.R1: Inland Waters III Oral
Track:
Land Applications
Location:
Morgan
Presentation Time:
Tuesday, 11 August, 09:15 - 09:30
Session Co-Chairs:
Baya Cherif, Stevens Insitute of Technology and Son Nghiem, Jet Propulsion Laboratory, California Institute of Technoly
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Session TU1.R1
TU1.R1.1: A NEW SENTINEL-2 SPECTRAL INDEX FOR MAPPING HYDRILLA VERTICILLATA IN SHALLOW FRESHWATER LAKES IN FLORIDA, USA
Ayesha Malligai M., Amr Abd-Elrahman, University of Florida, United States; James K. Leary, South Florida Water Management District, United States
TU1.R1.2: INTEGRATING SWOT AND SENTINEL-1 DATA: A MULTI-STEP PROCESS FOR MONITORING LAKES AND RESERVOIRS
Romain Cargnello, Santiago Pena Luque, Nicolas Gasnier, Centre National d'Etudes Spatiales, France
TU1.R1.3: SMAP Satellite Microwave Radiometry to Monitor River Flow and Lake Level in the Lower Mekong Basin
Anna Podkowa, Warsaw University of Technology, Poland; Son V. Nghiem, NASA Jet Propulsion Laboratory, United States; Zsofia Kugler, Budapest University of Technology and Economics, Hungary; G. Robert Brakenridge, University of Colorado, United States
TU1.R1.4: EVALUATING MACHINE LEARNING-BASED RIVER ICE DETECTION USING SENTINEL-3 SLSTR DATA
Baya Cherif, Marouane Temimi, Stevens Insitute of Technology, United States
Resources
No resources available.