Comparative Multi-Data and Multi-Method InSAR for Deformation Monitoring and Visualization: A Case Study of Baode, China

It remains unclear why deformation results obtained by applying different MT-InSAR methods to the same dataset, as well as those from different SAR datasets, exhibit discrepancies. Hence, this study selects Baode County, located in the Loess Plateau, as the study area to conduct a comparative analysis of multi-source SAR data and multiple MT-InSAR techniques for surface deformation monitoring. The datasets consist of concurrent Radarsat-2 and Sentinel-1 images acquired from October 2020 to June 2024. PS-InSAR, SBAS-InSAR, and IPTA-InSAR are adopted to compare their applicability across multiple dimensions, such as point coverage, deformation correlation, and mapping performance. Furthermore, based on IPTA-InSAR, the influences of spatiotemporal resolutions from different datasets on monitoring results are analyzed. The Sequential Turning Point Detection (STPD) method is incorporated to characterize the dynamic evolution of deformation and its correlation with precipitation. The results indicate that the three techniques exhibit favorable consistency and complementarity across diverse landform types. Nevertheless, SBAS-InSAR’s superiority in point density cannot be translated into an ability to represent continuous deformation fields. In contrast, IPTA-InSAR demonstrates better adaptability to complex surface conditions. Regarding data sources, Radarsat-2 achieves superior monitoring performance thanks to its high spatial resolution, yet its monitoring capacity is sensitive to variations in spatial resolution. Multi-looking not only reduces the maximum subsidence rate by approximately half but also increases elevation uncertainty by up to 24.8% and deformation-rate uncertainty by up to 42.1%. Sentinel-1, with its shorter revisit cycle, provides temporal sampling advantages that significantly enhance the ability to capture rapid subsidence signals. Through controlled-variable experiments, a dual-comparison analysis of multi-source SAR datasets and multiple MT-InSAR techniques enables the separation of discrepancies induced by algorithms from those originating in the datasets. The multifaceted experimental design provides a relatively comprehensive assessment of the influencing factors. The findings of this study can serve as references for InSAR data source combinations, technique selection, results presentation, and reliability assessment of deformation results in complex monitoring areas.