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TitleSeasonal Dynamics of the Amazon Floodplain through RADAR eyes: Lago Grande de Monte Alegre Case Study
 
AuthorCosta, M P; Novo, E M L; Ahern, F; Pietsch, R W
SourceInternational Symposium, Geomatics in the Era of RADARSAT (GER'97), Ottawa, Canada, May 25-30; 1997 p. 7
Year1997
Alt SeriesEarth Sciences Sector, Contribution Series 20042223
Documentbook
Lang.English
Mediapaper
SubjectsNature and Environment; Plants
AbstractThere is a lack of information on the seasonal dynamics of floodplain habitats in the Amazon regions of Brazil. This lack of information is due to the large size of the Amazon, persistent cloud cover and difficult access to do field campaigns. Radar data from RADARSAT will provide multitemporal data over these cloudy tropical regions which will result in increased information. As part of the ADRO program, this research investigates the preliminary results of assessing the synergism of multitemporal and multifrequency radar data for the Amazon. This assessment will allow for the understanding of seasonal floodplain dynamics in tropical environments. RADARSAT and JERS-1 images were acquired throughout 1996 for the Lago Grande test site in Brazil. Three periods of the hydrological cycles were imaged, these being high water, receding flood water and low water stages. The present evaluation is the preliminary results of the two first stages. Images for these stages were calibrated, orthorectified and filtered allowing for the integration of multitemporal and multifrequency data. These results show that the synergism of multitemporal and multifrequency (C and L- band) data provides the best combination of microwave information to discriminate among the floodplain habitats. C-band data is more sensitive to aquatic plants whereas L-band data is more effective in distinguishing between flooded forest, non-flooded forest, pasture, and aquatic plants. The combination of the two wavelengths increased the spectral separability of different classes, and allowed for monitoring of the seasonal floodplain dynamics.
GEOSCAN ID219025

 
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