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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/32248

Title: Analysis of a shallow water environment by multispectral satellite images using a subpixel classification algorithm
Authors: Kao H. M.;H. Ren;C. S. Lee
Contributors: NTOU:Institute of Applied Geosciences
Keywords: remote sensing;classification;mixture;subpixel;bathymetry
Date: 2008
Issue Date: 2012-06-15T07:43:42Z
Publisher: Applied remote sensing
Abstract: Optical satellite images observed in shallow water represent a mixture of information concerning bottom type, water quality, and water depth. In this study, we extracted such information by estimating the abundance using the mixed pixel classification technique. The method is based on the Orthogonal Subspace Projection algorithm which can first eliminate unwanted information, and then match for the information in which we are interested in. Our results indicated that using the subpixel classification approach, information correlated with water depth can be extracted from optical multi-spectral images. To further test this approach, we used satellite images of Itu-Aba Island in the southern part of the South China Sea as a test image and compared with truth depth data from echo sounder sonar system for verification. The results were promising and showed that the information extracted from the satellite image corresponding to bathymetry was highly correlated to the true water depth.
Relation: 2(1)
URI: http://ntour.ntou.edu.tw/handle/987654321/32248
Appears in Collections:[應用地球科學研究所] 演講及研討會

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