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Time-series interferometric synthetic aperture radar (InSAR) methods estimate the spatiotemporal evolution of deformation over large areas by incorporating information from multiple SAR interferograms. Persistent scatterer (PS) and small baseline (SB) methods, which identify areas where the surface is least affected by geometric and temporal decorrelation, represent two families of time-series InSAR techniques to study successfully a wide spectrum of ground deformation phenomena worldwide. However, little is known comparatively about the performance of PS and SB techniques applied to the same region. Here, we compare quantitatively and cross validate the time-series InSAR results generated using two representative algorithms-the maximum likelihood PS method and the small baseline subset algorithm-in selected test sites, over the San Francisco Bay Area imaged by European Remote Sensing (ERS) sensors during 1995-2000. We present line of sight (LOS) velocities and deformation time series using both techniques and show that the root mean squared differences of the estimated mean velocities and deformation from each method are about 1 mm/year and 5 mm, respectively. These values are within expected noise levels and a characteristic of the pixel selection parameters for both the time-series techniques. We validate our deformation estimates against creep measurements from alignment arrays along the Hayward Fault and show that our estimates agree to within 0.5 mm/year LOS velocity and 1.5 mm LOS displacement.