DocumentCode
1158590
Title
Knowledge-based classification of polarimetric SAR images
Author
Pierce, Leland E. ; Ulaby, Fawwaz T. ; Sarabandi, Kamal ; Dobson, M. Craig
Author_Institution
Radiation Lab., Michigan Univ., Ann Arbor, MI, USA
Volume
32
Issue
5
fYear
1994
fDate
9/1/1994 12:00:00 AM
Firstpage
1081
Lastpage
1086
Abstract
In preparation for the flight of the Shuttle Imaging Radar-C (SIR-C) on board the Space Shuttle in the spring of 1994, a level-1 automatic classifier was developed on the basis of polarimetric SAR images acquired by the JPL AirSAR system. The classifier uses L- and C-Band polarimetric SAR measurements of the imaged scene to classify individual pixels into one of four categories: tall vegetation (trees), short vegetation, urban, or bare surface, with the last category encompassing water surfaces, bare soil surfaces, and concrete or asphalt-covered surfaces. The classifier design uses knowledge of the nature of radar backscattering from surfaces and volumes to construct appropriate discriminators in a sequential format. The classifier, which was developed using training areas in a test site in Northern Michigan, was tested against independent test areas in the same test site and in another site imaged three months earlier. Among all cases and all categories, the classification accuracy ranged between 91% and 100%
Keywords
geophysical techniques; geophysics computing; image recognition; knowledge based systems; remote sensing by radar; synthetic aperture radar; 1.25 GHz; 5.3 GHz; C-Band; L-band UHF SHF; SAR imaging; SIR-C; Shuttle Imaging Radar-C; Space Shuttle; computer method; discriminator; expert system; geophysical measurement technique; knowledge based image classification; land surface; level-1 automatic classifier; polarimetric SAR image; radar backscattering; radar remote sensing; synthetic aperture radar; terrain mapping; trees; urban; vegetation; Classification tree analysis; Concrete; Layout; Pixel; Radar imaging; Soil measurements; Space shuttles; Springs; Testing; Vegetation mapping;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/36.312896
Filename
312896
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