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In this paper, we performed a classification of the degree of imperviousness in Miyun urban areas of China's Beijing region based on object-oriented method with SPOT multi-spectral data. The approach mainly involved establishing an image object hierarchy consisting of three levels of different scale. With the integration of different object features and semantic information from different image object levels, we performed a final class-related classification in the middle level using the above super-scale and sub-scale information. After the classification completed, a thematic map of showing the degree of imperviousness in urban areas has been created. It showed that the object-oriented remote sensing image analysis method is an effective, simple and rapid way to estimate and map the degree of urban impervious surface.