Keywords
forestry, geophysical techniques, geophysics computing, image recognition, remote sensing by radar
Abstract
The Seasat-A scatterometer (SASS) was designed to measure the near-surface wind field over the ocean by inferring the wind from measurements of the surface radar backscatter. While backscatter measurements were also made over land, they have been primarily used for the calibration of the instrument. This has been due in part to the low resolution of the scatterometer measurements (nominally 50 km). In a separate paper the present authors introduced a new method for generating enhanced resolution radar measurements of the Earth's surface using spaceborne scatterometry. In the present paper, the method is used with SASS data to study vegetation classification over the extended Amazon basin using the resulting medium-scale radar images. The remarkable correlation between the Ku-band radar images and vegetation formations is explored, and the results of several successful experiments to classify the general vegetation classes using the image data are presented. The results demonstrate the utility of medium-scale radar imagery in the study of tropical vegetation and permit utilization of both historic and contemporary scatterometer data for studies of global change. Because the scatterometer provides frequent, wide-area coverage at a variety of incidence angles, it can supplement higher resolution instruments which often have narrow swaths with limited coverage and incidence angle diversity.
Original Publication Citation
Long, D. G., and P. J. Hardin. "Vegetation Studies of the Amazon Basin using Enhanced Resolution Seasat Scatterometer Data." Geoscience and Remote Sensing, IEEE Transactions on 32.2 (1994): 449-6
BYU ScholarsArchive Citation
Long, David G.; Hardin, Perry J.; and Whiting, Peter T., "Vegetation studies of the Amazon basin using enhanced resolution Seasat scatterometer data" (1994). Faculty Publications. 702.
https://scholarsarchive.byu.edu/facpub/702
Document Type
Peer-Reviewed Article
Publication Date
1994-03-01
Permanent URL
http://hdl.lib.byu.edu/1877/1134
Publisher
IEEE
Language
English
College
Ira A. Fulton College of Engineering and Technology
Department
Electrical and Computer Engineering
Copyright Status
© 1994 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Copyright Use Information
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