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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TU4.O-10.3

MACHINE LEARNING COMBINATION OF LEO AND GEO SATELLITES FOR DESIGN AND MONITORING OF OCEAN WIND ENERGY

Christophe Messager, Extreme Weather Expertsises, France; Tran-Vu La, Extreme Weather Expertises (EXWEXs), France; Rémi Sahl, Extreme Weather Expertsises, France
Session:
Remote Sensing in the Energy Industry: A Valuable Tool for Renewable Energy and Monitoring Environmental Footprints
Track:
Invited Sessions
Presentation Time:
Tue, 13 Jul, 15:10-15:25 (UTC)
Tue, 13 Jul, 17:10-17:25 Central Europe Summer Time (UTC +2)
Tue, 13 Jul, 23:10-23:25 China Standard Time (UTC +8)
Tue, 13 Jul, 11:10-11:25 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Helene Bideaud, Total and Emmanuel Pajot, EARSC
Session Manager:
Ragini Bal Mahesh
Presentation
Discussion
Resources
Session TU4.O-10
TU4.O-10.1: PRELIMINARY ASSESSMENT OF PROBABLE IMPACTS CAUSED BY THE LARGEST OIL SPILL IN BRAZIL HISTORY ON SELECTED MANGROVE STANDS USING SATELLITE IMAGING
Guillaume Lassalle, UNICAMP, Brazil; Dominique Dubucq, TOTAL S.A., France
TU4.O-10.3: MACHINE LEARNING COMBINATION OF LEO AND GEO SATELLITES FOR DESIGN AND MONITORING OF OCEAN WIND ENERGY
Christophe Messager, Extreme Weather Expertsises, France; Tran-Vu La, Extreme Weather Expertises (EXWEXs), France; Rémi Sahl, Extreme Weather Expertsises, France
TU4.O-10.4: THE IMPORTANCE OF MATCHING NEEDS TO SATELLITE SYSTEM CAPABILITY WHEN MONITORING METHANE EMISSIONS FROM SPACE
Jean-Francois Gauthier, GHGSat Incorporated, Canada
TU4.O-10.5: SAR SURFACE WIND ESTIMATION AND EXTRAPOLATION AT TURBINE HUB HEIGHT WITH MACHINE LEARNING FOR OFFSHORE WIND FARM SITING
Louis de Montera, Henrick Berger, Romain Husson, CLS, France; Pascal Appelghem, Atmosky, France; Laurent Guerlou, Mauricio Fragoso, CLS, France

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