Double Polarization SAR Image Classification based on Object-Oriented Technology

Abstract

This paper proposed to use double polarization synthetic aperture radar (SAR) image to classify surface fea-ture, based on DEM. It takes fully use of the polarization information and external information. This paper utilizes ENVISAT ASAR APP double-polarization data of Poyang lake area in Jiangxi Province. Compared 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.