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Proceedings Paper

Change vector analysis method for inundation change detection using multi-temporal multi-polarized SAR images
Author(s): Guozhuang Shen; Huadong Guo; Jingjuan Liao
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Paper Abstract

With the all-weather and day-night imaging capability, synthetic aperture radar (SAR) plays an important role in inundation extent change detection. Inundation extent change detection using SAR will be easy as a result of the dark image tones yielded by specular reflection. Change vector analysis (CVA) method, an effective change detection method, is also a valuable inundation extent change detection method. In CVA method, change magnitude and change direction can be generated separately, which can be used to determine change areas and change types. CVA method also has the ability to process any number of spectral bands and to produce detailed change information. In this paper, CVA method was applied to inundation extent change detection using multi-temporal multi-polarization ENVISAT ASAR alternative polarization images acquired on 2004-08-29, 2004-12-12 and 2005-03-27. The test site is located in Poyang Lake wetland, where land surface had different inundation extent when images were acquired. Firstly these 3 phases of images were registered together. Then the change vectors were calculated using these images. After that change magnitude and direction cosine images were produced. At last the change areas and the corresponding change type were extracted separately using decision tree method. The result indicates that CVA method has potential utility in inundation extent change detection.

Paper Details

Date Published: 14 November 2007
PDF: 8 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679007 (14 November 2007); doi: 10.1117/12.739265
Show Author Affiliations
Guozhuang Shen, Institute of Remote Sensing Applications (China)
Graduate School of Chinese Academy of Sciences (China)
Huadong Guo, Institute of Remote Sensing Applications (China)
Jingjuan Liao, Institute of Remote Sensing Applications (China)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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