Prof. Frédérique Seyler
at Institut de Recherche pour le Développement
SPIE Involvement:
Author | Instructor
Publications (2)

SPIE Journal Paper | October 5, 2018
JARS Vol. 12 Issue 04
KEYWORDS: Vegetation, Agriculture, Remote sensing, Satellites, Ecosystems, Statistical analysis, Geographic information systems, Earth observing sensors, Image segmentation, Environmental sensing

PROCEEDINGS ARTICLE | December 19, 2008
Proc. SPIE. 7150, Remote Sensing of Inland, Coastal, and Oceanic Waters
KEYWORDS: Radar, Satellites, Synthetic aperture radar, Floods, Hydrology, Carbon dioxide, L band, Microwave radiation, Atmospheric propagation, Radio propagation

Course Instructor
SC924: Remote Sensing Techniques and Developments for Watershed Monitoring in Tropical Countries
This course provides attendees with a working knowledge of Remote Sensing capabilities in high tropical island environments, including cloud covers, flattening, atmospheric correction, mixed and dense vegetation cover distinction, and water monitoring and managment. The course concentrates on optical and radar system performance optimization and analysis. The first section of the course concerns the ungauged basins and the global monitoring of water resources. Dynamics and water residence time combining radar altimetry and SAR images show the exchanges process of water between the floodplain and the river. Results will be presented and discussed. The second section will examine experiences and methodology of the use of radar imagery for forest management and grass biomass. It then covers an original approach for radiometric (atmospheric) and geometric (flatenning) correction effect, which will be examined in the context of a project dealing with erosion problems in New Zealand (J. Dymond work). Examples on change detection on forestry issues will also be presented. The final section of the course analyzes a study in the Solomon Islands area, where SOPAC set up water catchment monitoring GIS layers. The example to be shown will cover a study on overlay analysis in raster data environment (ERDAS).
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