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This article presents a new approach for the study of urban areas using polarimetric SAR (PolSAR) data. The PolSAR multidimensional information is analyzed using a linear time-frequency (TF) decomposition which permits to describe an urban area polarimetric behavior for different azimuth angles of observation and frequencies of illumination. A TF signal model, adapted to the case of urban areas is proposed and studied using two statistical descriptors related to the signal stationary aspect and coherence in the time-frequency domain. These indicators are shown to provide complementary information, adapted to the case of man made environments. A TF based classification is proposed and applied to fully polarimetric SAR data acquired by the ESAR sensor at L-band. Results demonstrate the efficiency of this method in terms of buildings location retrieval and response characterization.