DocumentCode :
298025
Title :
A multi-temporal classifier for SIR-C/X-SAR imagery
Author :
Bergen, Kathleen M. ; Pierce, Leland E. ; Dobson, M. Craig ; Ulaby, Fawwaz T.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Volume :
3
fYear :
1996
fDate :
27-31 May 1996
Firstpage :
1568
Abstract :
Biophysical systems in temperate regions undergo distinct changes in each annual cycle. For forested ecosystems this includes moisture and phenological changes. The dual-flight program (April and October) for the SIR-C/X-SAR instrument aboard the Shuttle Endeavor was designed expressly to acquire imagery at different stages of such cycles. This provides new opportunities in terrain classification where phenology and moisture changes may be used as additional information. Given multi-season SIR-C/X-SAR imagery, there are three possible approaches to classifier development: (1) ignore the multiseason availability and develop independent classifications for each scene using n features, (2) develop one classification for a set of x scenes using n features, with x times the number of samples per feature, and (3) develop a true multi-temporal classification where N of features equals n (number of features) times x (number of scenes). Each of these are applied and results for the first two of six selected scenes show the true multi-temporal and the October scene alone to have the highest accuracies (94% and 95% respectively) at a level II classification
Keywords :
forestry; geophysical signal processing; hydrological techniques; image classification; moisture; radar imaging; remote sensing by radar; soil; spaceborne radar; synthetic aperture radar; SIR-C/X-SAR imagery; biophysical systems; classifier development; dual-flight program; forested ecosystems; level II classification; moisture; multi-temporal classification; multi-temporal classifier; multiseason availability; phenological changes; temperate regions; terrain classification; Biomass; Ecosystems; Filtering; Instruments; Laboratories; Layout; Moisture; Springs; Testing; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International
Conference_Location :
Lincoln, NE
Print_ISBN :
0-7803-3068-4
Type :
conf
DOI :
10.1109/IGARSS.1996.516733
Filename :
516733
Link To Document :
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