Based on the SAR satellite images from 2015 to 2019, this paper proposes a novel wide-area InSAR time series analysis technology for high-precision and continuous monitoring of the surface deformation in the North China Plain. Firstly, standard interferometric processing is carried out on SAR images to obtain the interferogram. Then the parallelized StaMPS method is used to extract all PS pixels in the interferogram and obtain the deformation time series with full resolution. Next the atmospheric noise is estimated and removed using the joint atmospheric correction method, through combination of the atmospheric model correction and common scene stacking. After this processing flow, we successfully obtain a solution of large spatial scale, long-term span, full spatial resolution, and high precision deformation in the North China Plain, and detect the subsidence deformation pattern with a strong signal of up to 100 mm/a in central plain due to groundwater extraction. Compared with existing algorithms, the parallelized StaMPS method saves at least 60% of computing time through real-time distribution among multiple computing nodes. Besides, the joint atmospheric correction method can remove about 74.3% of the atmospheric noise, and its effectiveness is significantly higher than that of using the two correction methods alone. This wide-area InSAR time series analysis technique can effectively realize high-precision continuous monitoring of large-scale surface deformation. 

wide-area InSAR time series analysis technique, parallelized StaMPS method, joint atmospheric correction method, surface deformation, North China Plain