DocumentCode :
986954
Title :
Delineation of inundated area and vegetation along the Amazon floodplain with the SIR-C synthetic aperture radar
Author :
Hess, Laura L. ; Melack, John M. ; Filoso, Solange ; Wang, Yong
Author_Institution :
Inst. for Comput. Earth Syst. Sci., California Univ., Santa Barbara, CA, USA
Volume :
33
Issue :
4
fYear :
1995
fDate :
7/1/1995 12:00:00 AM
Firstpage :
896
Lastpage :
904
Abstract :
Floodplain inundation and vegetation along the Negro and Amazon rivers near Manaus, Brazil were accurately delineated using multi-frequency, polarimetric synthetic aperture radar (SAR) data from the April and October 1994 SIR-C missions. A decision-tree model was used to formulate rules for a supervised classification into five categories: water, clearing (pasture), aquatic macrophyte (floating meadow), nonflooded forest, and flooded forest. Classified images were produced and tested within three days of SIR-C data acquisition. Both C-band (5.7 cm) and L-band (24 cm) wavelengths were necessary to distinguish the cover types. HH polarization was most useful for distinguishing flooded from nonflooded vegetation (C-HH for macrophyte versus pasture, and L-HH for flooded versus nonflooded forest), and cross-polarized L-band data provided the best separation between woody and nonwoody vegetation. Between the April and October missions, the Amazon River level fell about 3.6 m and the portion of the study area covered by flooded forest decreased from 23% to 12%. This study demonstrates the ability of multifrequency SAR to quantify in near realtime the extent of inundation on forested floodplains, and its potential application for timely monitoring of flood events
Keywords :
forestry; geophysical signal processing; geophysical techniques; hydrological techniques; image classification; radar applications; radar imaging; radar polarimetry; remote sensing by radar; rivers; spaceborne radar; synthetic aperture radar; 24 cm; 5.7 cm; AD 1994; Amazon floodplain; Brazil; L-band UHF C-band microwave; Manaus; Negro; SIR; SIR-C; decision-tree model; flood flooding; geophysical measurement technique; hydrology; inundated; multifrequency SAR; radar polarimetry; river; spaceborne radar remote sensing; supervised image classification; synthetic aperture radar; tropical forest forestry; vegetation mapping; water level; Data acquisition; Floods; L-band; Monitoring; Polarimetric synthetic aperture radar; Polarization; Rivers; Synthetic aperture radar; Testing; Vegetation mapping;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/36.406675
Filename :
406675
Link To Document :
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