The Amazon Floodplain through Radar Eyes: Lago Grande de Monte Alegre Case Study

There is a lack of information on the seasonal changes in the floodplain habitat 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 for field campaigns. Satellite radar sensors can provide multitemporal images...

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Bibliographic Details
Published in:Canadian journal of remote sensing 1998-12, Vol.24 (4), p.339-339
Main Authors: Costa, M.P. de F., Novo, E.M.L. de Moraes, Ahern, F., Mitsuo, F., Mantovani, J.E., Ballester, M.V., Pietsch, R.W.
Format: Article
Language:English
Subjects:
Brazil, Amazon
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Summary:There is a lack of information on the seasonal changes in the floodplain habitat 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 for field campaigns. Satellite radar sensors can provide multitemporal images over these cloudy tropical regions which can result in better mapping of the extent of the floodplain habitat. This research shows the synergism multi-frequency and multi-incidence angle radar data for studying the Amazon floodplain. RADARSAT and JERS-1 images were acquired on May 1996 for the Lago Grande test site in Brazil. The acquisitions coincide with the high water period of the hydrological cycle of the region of study. The images were calibrated, ortho-rectified and filtered allowing for the integration and classification of the data. The results show that the synergism of multi-frequency (C-and L- band) data provides a better combination of microwave information to discriminate among the floodplain habitat. C-band data is more sensitive to aquatic plants and water whereas L-band data is more effective in distinguishing between flooded forest and aquatic plants, and non-flooded forest and pasture. The combination of the two wavelengths increased the separability of the different classes.
ISSN:0703-8992
1712-7971
DOI:10.1080/07038992.1998.10874698