With the launch of the Sentinel-1 satellites, it becomes easy to obtain long time-series dual-pol (i.e., VV and VH channels) SAR images over most areas of the world. By combining the information from both VV and VH channels, the polarimetric persistent scatterer interferometry (PolPSI) techniques is supposed to achieve better ground deformation monitoring results than conventional PSI techniques (using only VV channel) with Sentinel-1 data. According to the quality metric used for polarimetric optimizations, the most commonly used PolPSI techniques can be categorized into three main categories. They are PolPSI-ADI (amplitude dispersion index as the phase quality metric), PolPSI-COH (coherence as the phase quality metric), and PolPSI-AOS (taking adaptive optimization strategies). Different categories of PolPSI techniques are suitable for different study areas and with different performances. However, the study that simultaneously applies all the three types of PolPSI techniques on Sentinel-1 PolSAR images is rare. Moreover, there has been little discussion about different characteristics of the three types of PolPSI techniques and how to use them with Sentinel-1 data. To this end, in this study, three data sets in China have been used to evaluate the three types of PolPSI techniques’ performances. Based on results obtained, the different characteristics of PolPSI techniques have been discussed. The results show that all three PolPSI techniques can improve the phase quality of interferograms. Thus, more qualified pixels can be used for ground deformation estimation by PolPSI methods with respect to the PSI technique. Specifically, this pixel density improvement is 50%, 12%, and 348% for the PolPSI-ADI, PolPSI-COH, and POlPSI-AOS, respectively. PolPSI-ADI is the most efficient method, and it is the first choice for the area with abundant deterministic scatterers (e.g., urban areas). Benefitting from its adaptive optimization strategy, PolPSI-AOS has the best performances at the price of highest computation cost, which is suitable for rural area applications. On the other hand, limited by the medium resolution of Sentinel-1 PolSAR images, PolPSI-COH’s improvement with respect to conventional PSI is relatively insignificant.

Underground coal fire is a global geological disaster that causes the loss of resources as well as environmental pollution. Xinjiang, China, is one of the regions suffering from serious underground coal fires. The accurate monitoring of underground coal fires is critical for management and extinguishment, and many remote sensing-based approaches have been developed for monitoring over large areas. Among them, the multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques have been recently employed for underground coal fires-related ground deformation monitoring. However, MT-InSAR involves a relatively high computational cost, especially when the monitoring area is large. We propose to use a more cost-efficient Stacking-InSAR technique to monitor ground deformation over underground coal fire areas in this study. Considering the effects of atmosphere on Stacking-InSAR, an ERA5 data-based estimation model is employed to mitigate the atmospheric phase of interferograms before stacking. Thus, an adaptive ERA5-Corrected Stacking-InSAR method is proposed in this study, and it is tested over the Fukang coal fire area in Xinjiang, China. Based on original and corrected interferograms, four groups of ground deformation results were obtained, and the possible coal fire areas were identified. In this paper, the ERA5 atmospheric delay products based on the estimation model along the LOS direction (D-LOS) effectively mitigate the atmospheric phase. The accuracy of ground deformation monitoring over a coal fire area has been improved by the proposed method choosing interferograms adaptively for stacking. The proposed Adaptive ERA5-Corrected Stacking-InSAR method can be used for efficient ground deformation monitoring over large coal fire areas.

With time-series PolSAR images, polarimetric persistent scatterer interferometry (PolPSI) algorithms can obtain optimized interferograms with overall better phase quality than any single-pol channel for ground deformation monitoring. Moreover, the open access of Sentinel-1 PolSAR data makes it possible for applications of PolPSI over large regions worldwide. However, the optimum scattering mechanism usually has to be searched in a high dimension solution space by PolPSI techniques from each pixel. This is with very high or even unacceptable computational costs if satisfactory results are expected. To this end, an efficient and effective PolPSI algorithm named as TP-ESM is proposed with Sentinel-1 data in this study, which optimizes pixels' interferograms by a weighted sum of their corresponding VV and VH channel interferograms. The effectiveness of TP-ESM is tested together with two other PolPSI techniques (i.e., TP-MSM and ESPO) over Beijing with 46 Sentinel-1 PolSAR images. The results show that TP-ESM can obtain similar optimized interferometric phases with ESPO over high quality pixels, and the ground deformation monitoring pixel density improvement achieved by TP-ESM and ESPO w.r.t. conventional PSI approach (with VV data) is 35% and 43%, respectively. On the other hand, the TP-MSM approach is found not applicable to Sentinel-1 data. Considering the negligible computational cost of TP-ESM w.r.t. ESPO, it presents a quite good performance on both interferograms' optimizations and ground deformation monitoring. Moreover, the proposed TP-ESM outperforms ESPO on DS pxiels' optimization, and it is anticipated to have promising performances on other PolSAR images acquired by other sensors.