Research on wetland classification approaches based on Hyperion hyperspectral image

Xue Li; Weiguo Jiang

doi:10.1117/12.833912

30 October 2009 Research on wetland classification approaches based on Hyperion hyperspectral image

Xue Li, Weiguo Jiang

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74981O (2009) https://doi.org/10.1117/12.833912
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Land cover classification is essential for the monitoring, protecting and managing of wetlands. With Dongting Lake in Hunan province of China selected as the study area, a scene of hyperspectral image acquired by EO-1 Hyperion was used to evaluate the methods for land cover classification. After a series of preprocessing including bands removal, radiometric correction, strip removal and geometric registration, MNF transformation and band selection were adopted for dimension reducing. Then the image was classified into eight land cover types via MLC, SVM, SAM and MF classifier. Results reveal that higher classification accuracy would be obtained if data dimension reduction is done by MNF method. In addition, SVM performs best among the four classifiers, followed with MLC, while SAM and MF show worse performances.

Citation Download Citation

Xue Li and Weiguo Jiang "Research on wetland classification approaches based on Hyperion hyperspectral image", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981O (30 October 2009); https://doi.org/10.1117/12.833912

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