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Proceedings Paper

The application of H-alpha-Wishart on land cover classification and analysis
Author(s): Ran Yang; Jie Yang; QianQing Qin
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Paper Abstract

The authors introduce unsupervised Wishart classification technique for fully polarimetric SAR data based on H-alpha decomposition of POLSAR images, and applied this technique to AIRSAR data of Flevoland, Netherlands. By applying the Cloude H-alpha decomposition to the original L-band image, we segment the image to 9 classes. While take this as the initial input, Wishart classification is followed. The most valuable in this paper is the section of application analysis. We found H-alpha classification has lower classification accuracy than Wishart iteration which use coherence matrix, but why? By analyzing the classification results for each type of land cover, this paper concluded the reason is that parameters of entry and alpha angle lose the original polarimetric information. While coherence matrix does not lose the original polarimetric information, we suggest that directly use coherence matrixes could derive much higher classification accuracy. There is also another found. Middle entropy scattering such as low vegetation often does not a single target while high or low entropy scattering, such as the deep forest and water, the coverage relatively much denser, often has single component; thus, the classification accuracy of high of low entropy land cover will be much higher than middle entropy scattering.

Paper Details

Date Published: 29 December 2008
PDF: 8 pages
Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854N (29 December 2008);
Show Author Affiliations
Ran Yang, Wuhan Univ. (China)
Jie Yang, Wuhan Univ. (China)
QianQing Qin, Wuhan Univ. (China)

Published in SPIE Proceedings Vol. 7285:
International Conference on Earth Observation Data Processing and Analysis (ICEODPA)
Deren Li; Jianya Gong; Huayi Wu, Editor(s)

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