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Today, Sentinel ‐ 1A data with terrain observation with progressive scanning (TOPS) imaging mode is increasingly used in earth observation aiming at consistent monitoring of surface change and its deformation. However, due to the limited accuracy of coarse co ‐registration, spectral aliasing along the azimuth direction enables the presence of phase jumping in overlapping area of neighboring bursts. Although geometrical co‐registration in conjunction with enhanced spectral diversity (ESD) is proven to be a feasible strategy to correct such error and has been widely used in some open source softwares (e.g. DORIS (Delft object‐oriented radar interferometric software), SNAP (sentinel applications platform), ISCE (InSAR scientific computing environment)), the performance of ESD is still not satisfactory and relies strongly on spatiotemporal decorrelation. Given that decorrelation is generally quantized by interferometric coherence, this paper presents and assesses a new methodology to improve the accuracy of ESD by fully exploring the high coherent targets. Specifically, this method focuses on mitigating the spatiotemporal decorrelation in fine coregistration procedures by: (1) Selecting stable targets with moderate and high coherence using accurate coherence estimation. (2) Maximizing coherence magnitude by optimal interferometric subset chosen from Dijkstra algorithm. We compare and test this method against current favorites based on single master image and network‐based enhanced spectral diversity (NESD), and the experimental results demonstrate the value of our method. It can make up for the shortage of NESD method. [ABSTRACT FROM AUTHOR]

Three-dimensional phase unwrapping is one of the key steps of time-series interferometric syn- thetic aperture radar (InSAR) technology. The unwrapping results directly affect the accuracy of time-series InSAR land subsidence monitoring. Aiming at the problem of the whole period unwrapping error caused by phase undersampling in areas with serious land subsidence and large change of terrain slope, a weighted least squares phase unwrapping algorithm based on frequency confidence is proposed, which replaces the weighted least squares phase unwrapping algorithm based on phase gradient in the time-dependent three-di- mensional phase. By improving the accuracy of phase slope change estimation, the accuracy and stability of spatio -temporal three-dimensional phase unwrapping can be improved. The land subsidence results of the typical area in Beijing are obtained by using the improved spatio-temporal three-dimensional phase unwrap- ping method. Compared with the classical spatio - temporal three - dimensional phase unwrapping method, the improved method can obtain higher accuracy of land subsidence monitoring results. Especially for the subsidence funnel region where the slope changes greatly and the decorrelation exists obviously, the subsid- ence monitoring accuracy has improved significantly. [ABSTRACT FROM AUTHOR]