Double Polarization SAR Image Classification based on Object-Oriented Technology
Xiuguo Liu, Yongsheng Li, Wei Gao, Lin Xiao
DOI: 10.4236/jgis.2010.22017   PDF   HTML     5,343 Downloads   9,568 Views   Citations


This paper proposed to use double polarization synthetic aperture radar (SAR) image to classify surface feature, based on DEM. It takes fully use of the polarization information and external information. This pa-per utilizes ENVISAT ASAR APP double-polarization data of Poyang lake area in Jiangxi Province. Com-pared with traditional pixel-based classification, this paper fully uses object features (color, shape, hierarchy) and accessorial DEM information. The classification accuracy improves from the original 73.7% to 91.84%. The result shows that object-oriented classification technology is suitable for double polarization SAR’s high precision classification.

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X. Liu, Y. Li, W. Gao and L. Xiao, "Double Polarization SAR Image Classification based on Object-Oriented Technology," Journal of Geographic Information System, Vol. 2 No. 2, 2010, pp. 113-119. doi: 10.4236/jgis.2010.22017.

Conflicts of Interest

The authors declare no conflicts of interest.


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