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Salt domes play a crucial role in hydrocarbon storage, underground construction, solution mining, and mineralization. Therefore, deformation monitoring is essential for analyzing the kinematics and impact of salt domes. This study aims to measure the temporal displacements of the Shah-Gheyb salt dome from 2016 to 2019 and from 2020 to 2022 using the New Small Baseline Subset (NSBAS) Interferometric Synthetic Aperture Radar (InSAR) technique and to predict future displacements through machine learning models. A total of 14 data layers, including topography, remote sensing, hydrology, and geology group were used in Machine Learning (ML). Random Forest Regression (RFR) and Support Vector Regression (SVR) models were employed to project displacements in both the East-West (E-W) and Up-Down (U-D) components through 29 scenarios.In the E-W direction, the salt dome exhibits a displacement rate of 39 mm/year, while in the U-D direction, it varies between −18 and +6 mm/year. ML predictions and SAR interferometry data processing results for the period 2020–2022 were validated using Root Mean Square Error (RMSE) and the correlation coefficient (R). The RFR model demonstrated the lowest RMSE of 1.9 mm for the E-W component, achieving a maximum R-value of 97.3 %. For the U-D component, the RMSE was 2.8 mm, with an R-value of 55.8 %. Evaluation of the predictive performance of the ML models and a comparison of InSAR and ML outcomes indicated that the RFR model predicted displacement along the E-W and U-D directions between 2020 and 2022 with greater accuracy than the SVR. Furthermore, comparing the displacement predicted by the RFR model using SAR interferometry along two perpendicular profiles confirmed the model's precision.

Over the last two decades, Semarang, located in the central region of Java island, Indonesia, has been undergoing significant land subsidence. Mainly attributed to reservoir compaction and fluid extraction, this subsidence has pronounced effects in coastal regions. However, the existing study on the details of subsidence and its application to accurately depict present circumstances has been insufficient. Utilizing the new small baseline subset technique and C-band SAR data from 2015 to 2022, this study delineates the spatial boundaries of land subsidence in Semarang and surrounding areas. Atmospheric effects were mitigated using the GACOS model during InSAR processing. The study reveals dominant vertical movements in Semarang’s north coastal area, characterized by rapid and extensive changes. In contrast, horizontal movement shows relatively small changes in number to the east of the study area. Time series analysis indicates maximum subsidence rate of 100–120 mm/year in the northern and eastern part of Semarang and Demak. Available data from GNSS stations ensures the reliability of these findings. The correlation coefficient of 0.86 indicated substantial association between groundwater and deformation. Approximately 20 % of Semarang’s land area is affected by land subsidence, which is notably more prevalent in alluvial soils and densely populated regions. In Demak, subsidence is primarily observed in agricultural regions, whereas in Kendal, the 50 mm/year subsidence rate represents a growing concern. This accelerating phenomenon poses substantial risks to the local environment and economic sectors. All authorities must harmonize regulations to force their roles, produce details spatial plan maps, and establish mitigation and adaptation infrastructure to handle the current crisis realistically.

The 110-kilometer-long Qom-Kashan railway is one of the busiest lines in Iran, passing through the Kashan plain. The majority of Iran's plains have subsided in recent years as a result of uncontrolled groundwater extraction, and the Kashan plain is no exception. In this study, ground surface displacement in the Kashan plain region and its impact on the railway were investigated using New Small Baseline Subset (NSBAS) in up-down and east–west directions using descending and ascending Sentinel-1 data collected between 2015 and 2021. Our results indicate that the Kashan plain is subsiding more than 90 mm/year. The study of the local areas around the railway which passes through the study area revealed that the rate of vertical velocity in some locations reaches –23 mm/year, while the rate of east–west velocity is insignificant and is approximately ±2 mm/year. Additionally, a method for analyzing the railway's stability based on longitudinal profiles along the railway is presented. Our findings suggest that more than 60% of the railway line is subject to variable amounts of subsidence. Additionally, a region of approximately one kilometer of the railway has been classified as a risk zone due to relatively fast local deformation. After examining the effect of various factors, it was determined that uncontrolled groundwater extraction in agricultural areas contributed to the subsidence in this area. Our results show that the presented stability control approach in this study is highly reliable for creating hazard profiles for linear structures, such as railways.