InSAR Time Series Research Articles

Surface Displacements Monitoring in Cyprus via InSAR and Field Investigation: The Case Studies of Pyrgos-Parekklisia and Pedoulas Villages

The island of Cyprus is characterised by a complex geological environment as it overlies a boundary zone of three tectonic plates, leading to high seismicity and intensive tectonism. It consists highly of Neogene marls, exhibiting serious geotechnical problems due to their high content of clay minerals. Along with strong, destructive earthquakes, various geohazards have been identified in Cyprus, including landslides, swelling/shrinking phenomena and land subsidence etc. Pedoulas is a village in Cyprus experiencing ground deformation due to landslide phenomena. Conversely, Pyrgos and Parekklisia villages in Limassol, Cyprus are experiencing a long-term swelling/shrinking phenomenon. To further investigate this surface deformation, a time-series InSAR analysis of Sentinel-1 SLC images of ascending satellite passes was performed, with a parallelised version of PSI (Persistent Scatterers Interferometry), along with field investigation, for the time period of 2016 to 2021. Negative vertical displacements with maximum rates of −10 mm/y, were identified in Pedoulas village, while positive vertical displacements with a maximum rate of 10 mm/y, dominated in Pyrgos and Parekklisia villages. The analysis of precipitation data from 2017 to 2021, presented a correlation between annual fluctuations in precipitation in the affected areas and changes in the InSAR time-series deformation trends. In Pedoulas village, landslide movements sped up during spring and summer, when the infiltration of waste water in the ground intensified due to the increase in the tourist population. In Pyrgos-Parekklisia villages, higher positive deformation rates were identified in winter months, while during summer, when the formations dried out, uplifting phenomena stopped evolving. The integration of InSAR displacements with field investigation provided validation of the observed ground failures and added valuable insights into the driving mechanisms of the deformation phenomena. Finally, the assessment of the impact of the triggering factor in the evolution of the deformation phenomena, can serve as a valuable tool for risk mitigation.

Elucidating the complex interplay between natural and anthropogenic factors in the deformation of the Muyubao landslide through time-series InSAR analysis

In the Three Gorges Reservoir area, landslide disasters occur frequently, making scientific monitoring and risk prediction crucial for disaster prevention and mitigation. However, most previous studies have been constrained by analysis of singular influencing factors. In this study, we employed multi-temporal InSAR techniques coupled with multivariate geospatial statistical analysis to monitor and analyze the dynamic evolution of the Muyuba landslide in Zigui County, Hubei Province, China from 2016 to 2023. The findings indicate that the Muyuba landslide was predominantly characterized by continuous, gradual subsidence. Key factors inducing deformation included well-developed drainage networks, gentle slopes of 15–30°, and the orientation of rock strata. Deformation rates in residential areas and along roadways exceeded background levels, implicating anthropogenic activities in the heightened landslide risk. A significant correlation was observed between landslide deformation and reservoir water level fluctuations, as opposed to rainfall patterns, highlighting reservoir regulation disturbances as a critical landslide triggering factor.

Variations in Subsidence Patterns in the Gulf of Mexico Passive Margin From Airborne‐LiDAR Data and Time Series InSAR: Baton Rouge Case Study

AbstractThe Coast of Louisiana is affected by accelerating sea level rise compounded by land subsidence, leading to land loss. Vertical crustal motions in the region are caused by natural and anthropogenic processes that vary temporally and spatially across the Gulf of Mexico. We investigate the role of growth faulting contributions to subsidence in a case study of Baton Rouge, where two E‐W striking, down‐to‐the‐south normal faults, the Denham Springs and Baton Rouge faults, cut compacted Pleistocene strata, and where sediment compaction should be minimal. We used InSAR time series and LiDAR differencing data spanning 1999–2020 to quantify modern vertical and horizontal displacements. After calibration with GNSS data, both methods reveal similar spatial patterns in ground motion, with the faults delimiting areas with different absolute rates. On average the area north of the Baton Rouge fault is subsiding faster than the south, opposite to the long‐term sense of fault slip. LiDAR mean vertical rates range between −5 to −11 mm/y and −2.4 to −7 mm/y. InSAR time‐series mean rates in the LOS direction range between −10.9 to −13.6 mm/y and −8 to −10.6 mm/y, respectively, for the north and south areas. Subsidence in the northern area likely is controlled by groundwater level changes caused by pumping as indicated by groundwater extraction models. The southern area average is likely influenced by the injection of fluids. Our results suggest volumetric changes caused by fluid extraction and injection in regions separated by growth faults that are creeping to accommodate the spatial variations in subsidence.

Utilizing Gaofen-3 InSAR time series to reveal land subsidence in Beijing (China)

ABSTRACT Various applications have been achieved by Gaofen-3 images, while the time series interferometric synthetic aperture radar (TS-InSAR) analysis was rare due to the issues with baseline instability. In this study, we revealed that the primary artefacts degrading the quality of Gaofen-3 interferograms are the long spatial baselines and inaccuracy of orbit information induced by the lack of consideration of satellite orbital tube manoeuvres. To address these challenges, we have proposed an enhanced interferometry processing method aimed at isolating the main artefacts from wrapped interferograms and enhancing the interferometry capabilities of Gaofen-3 images. It mainly includes tips on estimating precise baselines based on orbital information and fringe frequency in the wrapped interferogram and refining the residual phase further by a quadratic polynomial regression model. Subsequently, the TS-InSAR analysis is successfully implemented to acquire high-accuracy land subsidence in Beijing during 2020–2021 based on these refined interferograms. This case study demonstrates the achievement of the land subsidence analysis through TS-InSAR with Gaofen-3 images, highlighting that our proposed method could enhance the quality of Gaofen-3 interferograms.

Current active fault distribution and slip rate along the middle section of the Jiali-Chayu fault from Sentinel-1 InSAR observations (2017–2022)

The Jiali-Chayu fault, situated on the eastern side of the eastern Himalayan syntaxis, is the southeastern margin of the large strike-slip fault zone of the Jiali Fault. The study of the distribution and activity within this fault zone is imperative for a comprehensive understanding of the tectonic movement patterns in the southeastern Tibetan Plateau. Previous studies have established that the kinematic characteristic of the Jiali-Chayu fault diverges significantly from that of other segments within the Jiali fault. Nonetheless, the current tectonic characteristics, including the slip sense, slip rate, and geometric deformation of this fault, are still not well resolved, leading to divergent interpretations regarding its contemporary activity intensity. This paper introduced an optimized time-series InSAR method with phase compensation designed for regions characterized by low coherence and exhibiting slow deformation. Using Sentinel-1 SAR data from both ascending and descending orbits spanning the period between 2017 and 2022, we successfully derived deformation rates for the middle part of the Jiali-Chayu fault at a spatial resolution of 150 m. The slip and dip rates of active faults are determined by considering the fault movement rates from two different observation angles, in conjunction with strike angle and the assumed dip angle of the fault. The results show that the deformation rates of the three branches are very different, with F2-1 and F2-2 exhibiting notable activity, while other areas exhibit relatively weaker activity. The strike-slip rates for F2-1 and F2-2 faults range between 3.6 and 5.3 mm/a and 3.05 to 5.13 mm/a, respectively, while their respective dip-slip rates fall within the range of 1.1–2.7 mm/a and 2.99–5.02 mm/a. In accordance with the fault slip directions, we classify the F2-1 fault as a sinistral (left-lateral) strike-slip fault and the F2-2 fault as a dextral (right-lateral) strike-slip fault. This study addresses a gap in remote sensing methods for detecting active fault activity in this region, providing a systematic foundation for identifying weak activity characteristics within the fault zone.Graphical

Geodetic imaging and dynamic modeling of saline mudflat using time-series InSAR in Howz-e-Soltan Salt Lake, Qom, Iran

Due to the physicochemical properties of salt swelling and collapsibility, the potential geological hazards threaten the large-scale infrastructure and residential areas in the saline-soil region. Geodetic imaging and dynamic monitoring of the spatiotemporal evolution process of saline soil are vital to detect the potential geological hazards in a vast area. Therefore, this paper presents a coupled deformation model synthesizing environmental factors and trigonometric function model for estimating the time-series InSAR deformation and interpreting the dynamic evolutionary mechanism of the saline mudflat. To demonstrate the advantages of the proposed model, the sulphate saline mudflat is selected as the study area, which is traversed by the Tehran-Isfahan high-speed railway in Howz-e-Soltan Salt Lake, Qom, Iran. Moreover, 259 interconnecting interferograms were selected for the time-series InSAR estimation, composed of 87 Sentinel-1A images obtained from October 2014 through December 2018. Then, the time-series deformations, including the annual deformation velocity and the accumulated deformation, are extracted by the original estimation, polynomial, trigonometric and environmental models. The comparison results show that the environmental model's RMSEs (root-mean-square errors) are smaller than others. It should be noted that the linear deformation, periodic oscillation, and deformation derived from the environmental factors (i.e., precipitation and temperature) are extracted by the environmental model. Furthermore, the dynamic evolutionary mechanism of the saline mudflat is interpreted according to the physicochemical properties of sulphate/carbonate saline soil. The results derived from the environmental model suggested that the saline-soil deformation is directly related with the environmental changes: rapid collapsibility occurs when the precipitation increases from September to the next May, while uplift due to the salt swelling in the dry and rainless season from May to September every year. Our findings provide an opportunity to detect, prevent and control the potential geological hazards in saline mudflats.

A Parallel Sequential SBAS Processing Framework Based on Hadoop Distributed Computing

With the rapid development of microwave remote sensing and SAR satellite systems, the use of InSAR techniques has been greatly encouraged due to the abundance of SAR data with unprecedented temporal and spatial coverage. Small Baseline Subset (SBAS) is a promising time-series InSAR method for applications involving deformation monitoring of the Earth’s crust, and the sequential SBAS method is an extension of SBAS that allows long-term and large-scale surface displacements to be obtained with continuously auto-updating measurement results. As the Chinese LuTan-1 SAR system has begun acquiring massive SAR image data, the need for an efficient and lightweight InSAR processing platform has become urgent in various research fields. However, traditional sequential algorithms are incapable of meeting the huge challenges of low efficiency and frequent human interaction in large-scale InSAR data processing. Therefore, this study proposes a distributed parallel sequential SBAS (P2SBAS) processing chain based on Hadoop by effectively parallelizing and improving the current sequential SBAS method. P2SBAS mainly consists of two components: (1) a distributed SAR data storage platform based on HDFS, which supports efficient inter-node data transfer and continuous online data acquisition, and (2) several parallel InSAR processing algorithms based on the MapReduce model, including image registration, filtering, phase unwrapping, sequential SBAS processing, and so on. By leveraging the capabilities associated with the distributed nature of the Hadoop platform, these algorithms are able to efficiently utilize the segmentation strategy and perform careful boundary processing. These parallelized InSAR algorithm modules can achieve their goals on different nodes in the Hadoop distributed environment, thereby maximizing computing resources and improving the overall performance while comprehensively considering performance and precision. In addition, P2SBAS provides better computing and storage capabilities for small- and medium-sized teams compared to popular InSAR processing approaches based on cloud computing or supercomputing platforms, and it can be easily deployed on clusters thanks to the integration of various existing computing components. Finally, to demonstrate and evaluate the efficiency and accuracy of P2SBAS, we conducted comparative experiments on a set of 32 TerraSAR images of Beijing, China. The results demonstrate that P2SBAS can fully utilize various computing nodes to improve InSAR processing and can be applied well in large-scale LuTan-1 InSAR applications in the future.

Long-Term SAR Data Analysis for Subsidence Monitoring and Correlation Study at Beijing Capital Airport

Land subsidence, resulting from natural or human activities, is a global environmental geological disaster. The Interferometric Synthetic Aperture Radar (InSAR) time-series analysis technique offers high spatial and continuous temporal resolution, providing data and a foundation for investigating regional land subsidence and its evolution mechanism. Beijing Capital International Airport (BCIA) has experienced uneven land subsidence since 1935, together with severe fissures significantly affecting its normal operations. In this study, the time-series InSAR method was successfully applied to monitor the gradual increase in uneven local subsidence and ground fissures activity at BCIA from June 2003 to March 2023. Initially, ENVISAT-ASAR, Cosmo-SkyMed, and Sentinel-1 data were processed by time-series InSAR techniques to generate deformation rate maps and time series for the airport area. Subsequently, a comparison was made between the displacement time series from InSAR and ground leveling measurements to assess the accuracy of InSAR-derived measurements. Through a comprehensive analysis of the distribution characteristics of land subsidence at the airport, a long-standing ground fault was located within the airport was identified. A preliminary discussion on the development status of this ground fissure was carried out based on the visual interpretation of optical images. Lastly, the inducing factors and evolutionary conditions of land subsidence were discussed. This case demonstrates the applicability of InSAR technology in identifying and monitoring geological processes such as land subsidence and ground fissure activities. It provides a scientific approach to exploring and studying the causes and formation mechanisms of land subsidence and ground fissures in the Beijing Capital Airport area.

Unveiling the driving factors of urban land subsidence in Beijing, China

Land subsidence, an insidious and gradual geological phenomenon, presents a latent threat to future urban development and socio-economic progress. Beijing City, renowned for its high population density, has encountered significant challenges associated with land subsidence. In this study, we leverage time-series interferometric synthetic aperture radar (time-series InSAR) method to analyze the spatio-temporal patterns of land subsidence in Beijing. Furthermore, we quantify the contributions of natural and anthropogenic factors to land subsidence. Our findings reveal that land subsidence primarily occurs in the plain area of Beijing, exhibiting an average rate of −5.6 mm/year (Positive values indicate uplift, while negative values indicate subsidence.). Notably, several large-scale subsidence centers are identified, with the maximum subsidence rate reaching an alarming −232.7 mm/year. The assessments indicate that geological factors, specifically fault activity, account for 33 % of the observed land subsidence, while human activities contribute to the remaining 67 %, with groundwater overexploitation playing a prominent role. The insights gained from this study provide a foundation for understanding the causative factors behind urban land subsidence and can aid in the formulation of effective intervention policies targeting this critical issue.

Slow slip event displacement on 2018 offshore Boso Peninsula detected by Sentinel-1 InSAR time-series analysis with numerical weather model assistance

SUMMARY The south-eastern offshore of the Boso Peninsula in Japan periodically experiences short-term slow slip events (SSEs) every few years. On 2018 June, an SSE occurred with the maximum surface horizontal displacement reaching up to 4.7 cm by according to the operational global navigation satellite system (GNSS) network. This study performed a time-series analysis of interferometric synthetic aperture radar (InSAR) with Sentinel-1 SAR images to investigate detailed spatial pattern of surface displacements caused by the SSE. With the assistance of an atmospheric delay correction with a regional numerical weather model output, the InSAR time-series analysis successfully captured displacement signals in three paths, whose maximum amplitudes in line-of-sight directions were 1.46, 1.86 and −0.80 cm. A checkerboard test revealed that the resolution of the slip inversion was higher when InSAR was used than that using GNSS, especially in and around the inland. The slip inversion with the actual displacement data derived from the InSAR time-series analysis was performed with the L-curve optimization, showing that the estimated slip area was concentrated offshore south-eastward from the Boso Peninsula with the maximum slip of 5 cm and the estimated moment magnitude of 6.4. As similar to previous SSEs in the Boso Peninsula, a seismic swarm simultaneously occurred in the downdip area adjacent to the estimated slip with the SSE occurrence, suggesting a different friction characteristics between them. This study demonstrates usefulnesses of the InSAR observation for capturing detailed spatial characteristics of small-displacement events like SSEs and of the hybrid use of the externally derived delay correction with the time-series analysis to improve the displacement detection accuracy.

Three-dimensional surface deformation from multi-track InSAR and oil reservoir characterization: A case study in the Liaohe Oilfield, northeast China

Oil productions can result in pore pressure drop in the reservoir, generating an increase in effective stress and leading to reservoir compaction. The compaction in the subsurface reservoir translates to the earth's surface, which is manifested as a loss of elevation (land subsidence), causing damages to oil production facilities and surface infrastructures. The Liaohe oilfield, located in Liaohe River Delta (LRD), northeast of China, is one of the most significant subsidence areas in China as a direct consequence of oil extraction from the reservoir. Previous studies carried out in this area assumed the oil production-induced displacement retrieved from Interferometric Synthetic Aperture Radar (InSAR) corresponds only to vertical deformation. In this work, for the first time, we proposed a method to retrieve the full three-dimensional (3D) displacement field over the oilfield. We retrieved the vertical and east-west displacement components by combining the multiple-geometry InSAR line-of-sight (LOS) observations and retrieved the north-south component based on the assumption of a physical relationship between the horizontal and vertical displacement. Two ascending and two descending datasets from Sentinel-1 satellite covering the area were processed by an InSAR time series analysis over the 2017 to 2021 period, providing consistent displacement rate maps and displacement time series in the LOS direction. Spatial local-scale land subsidence was found in several producing fields over the deltaic region, including Shuguang, Huanxiling, and Jinzhou oilfields. The 3D displacement decomposition was then conducted in Shuguang oilfield. The derived 3D displacement field exhibit a circular subsidence bowl with a maximum subsiding rate reaching 212 mm/year, accompanied by a centripetal pattern of horizontal displacements with maximum rates up to 50–60 mm/year moving towards the subsidence center. The retrieved 3D displacements are in good agreement with predictions from the geomechanical modeling by assuming a disk-shaped reservoir subject to a uniform reduction in pore fluid pressure. Finally, we show the importance of knowing both the vertical and horizontal displacement in characterizing the lateral boundary of the subsurface reservoir.

Analyzing gully erosion and deposition patterns in loess tableland: Insights from small baseline subset interferometric synthetic aperture radar (SBAS InSAR)

The fragile Loess Plateau of China suffers substantial gully erosion. It is imperative to elucidate gully erosion patterns for implementing effective erosion control strategies. However, high spatiotemporal resolution quantification of gully dynamics remains limited across the Loess Plateau landscape. We utilized the small baseline subset interferometric synthetic aperture radar (SBAS InSAR) technique to investigate the phenomenon of gully erosion and deposition on the Dongzhiyuan tableland, which sits within the vast expanse of the Loess Plateau in China, over the period spanning 2020–2022. The tableland edges subsided while gully bottoms uplifted due to sedimentation. Low elevations underwent active deformation. Slope, aspect, and curvature modulated uplift and subsidence patterns by affecting runoff and sediment transport. Gentle downstream slopes displayed enhanced sedimentation. Southern gullies showed pronounced uplift compared to northern gullies. Heavy rainfall triggered extensive erosion followed by rapid uplift, reflecting an adaptive oscillation between erosion and deposition. Basin hydrology correlated with spatial patterns of deformation. Vegetation cover above 60 % of the maximum substantially increased InSAR error. Our study reveals intricate spatiotemporal behaviors of erosion and deposition in loess gullies using time-series InSAR. The findings provide new insights into gully geomorphology and evolution, and our study quantifies gully erosion and deposition patterns at high spatiotemporal resolution, enabling identification of the most vulnerable areas and prioritization of conservation efforts.

Land subsidence analysis along high-speed railway based on EEMD-Prophet method

Environmental changes and ground subsidence along railway lines are serious concerns during high-speed railway operations. It is worth noting that AutoRegressive Integrated Moving Average (ARMA), Long Short-Term Memory (LSTM), and other prediction methods may present limitations when applied to predict InSAR time series results. To address this issue, this study proposes a prediction method that decomposes the nonlinear settlement time series of feature points obtained through InSAR technology using Ensemble Empirical Mode Decomposition (EEMD). Subsequently, multiple Intrinsic Mode Functions (IMFs) are generated, and each IMF is individually predicted using the Prophet forecasting model. Finally, we employ an equal-weight superimposition method to combine the results, resulting in the prediction of the InSAR settlement time series. The predicted values of each component are subsequently weighted equally and combined to derive the final prediction outcome. This paper selects InSAR monitoring data along a high-speed railway in inland China and uses the proposed method and ARMA and Prophet models to carry out comparative experiments. The experimental results show that compared with the ARMA and Prophet models, the method in this paper improves the root mean square error by 58.01% and 32.3%, and increases the mean absolute error by 62.69% and 33.78%, respectively. The predicted settlement values generated by our method exhibit better agreement with the actual InSAR monitoring values.

Deformation monitoring and analysis of liujiaxia reservoir landslide based on time-series InSAR and wavelet transform

The periodic storage and release of water in reservoirs have the potential to accelerate deformation or trigger ancient landslides. Interferometric synthetic aperture radar (InSAR) technology, renowned for its wide coverage and high precision, has emerged as an effective technique for the identification and monitoring of landslides. This study utilized spaceborne InSAR technology to identify and interpret landslides in the Liujiangxia reservoir area in China, leading to the detection of a total of 20 landslides. Moreover, among these 20 landslides, the landslide with substantial deformation (LJX02) was chosen, and the wavelet quantitative analysis technique was employed to investigate the correlation and time lag between various elevation positions of this landslide, the reservoir water level, and rainfall. The study successfully demonstrated that the deformation of the landslide lagged behind the reservoir water level by 152.10-182.50 days (from low to high elevation) and was delayed by 45.60-68.44 days compared to rainfall (from high to low elevation).

Temporal and Spatial Analysis of Ground Deformation of Beijing Daxing International Airport before and after Operation Using Time Series InSAR

Temporal and Spatial Analysis of Ground Deformation of Beijing Daxing International Airport before and after Operation Using Time Series InSAR

Aliasing in InSAR 2-D Phase Unwrapping and Time Series

Aliasing in InSAR 2-D Phase Unwrapping and Time Series

Automated Reference Points Selection for InSAR Time Series Analysis on Segmented Wetlands

Automated Reference Points Selection for InSAR Time Series Analysis on Segmented Wetlands

Using InSAR Time Series to Estimate Ground Displacement Resulting From 7.3Mw 12 November 2017, Earthquake, Near the Iraq-Iran Border

Using InSAR Time Series to Estimate Ground Displacement Resulting From 7.3Mw 12 November 2017, Earthquake, Near the Iraq-Iran Border

InSAR time series analysis of natural and anthropogenic coastal plain subsidence: A case of Hangjiahu plain

The early excessive groundwater exploitation caused extensive land subsidence in the Hangjiahu Plain (HJHP), threatening geological stability and infrastructure. Government restrictions on groundwater exploitation led to considerable changes in surface subsidence. To explore the distribution and causes of surface deformation after restrictions on groundwater exploitation, we used 46 Sentinel-1A TOPS images to detect the spatiotemporal distribution of surface deformation in the HJHP area from January 2019 to October 2022 by SBAS-InSAR technique and verified it with leveling results. Results indicated the following: (1) The uneven surface subsidence in the HJHP was relatively apparent, with the localized subsidence concentrated in a few areas. During InSAR monitoring, the maximum subsidence velocity reached −21.0 mm/yr. The most severe subsidence area was in the Shengze town industrial park, with remarkable subsidence bowls and a maximum subsidence of −85.8 mm. (2) Results were verified by comparing the InSAR results with leveling, and the results were in good agreement, indicating the reliability of the InSAR results. (3) Comprehensive analysis of the spatial distribution characteristics of surface subsidence, geological data and rainfall changes revealed that fault activity and rainfall changes had varying degrees of effect on surface subsidence in the HJHP area. (4) The comparison with land use data indicated that the built area was the dominant mechanism of surface subsidence in the study area. In addition, the effect of industrial activities on the surface cannot be ignored. The study results provide scientific data support for emergency disaster prevention work in the HJHP.

Strategies for improving and correcting unwrapped interferograms implemented in LiCSBAS

This brief article gathers several improvements to the LiCSBAS, an open-source python-based InSAR time series tool developed by the COMET UK group, focusing on improving quality of unwrapped interferograms that are the input to the time series inversion, therefore their quality is crucial. We add functionality of full re-unwrapping of the original wrapped interferograms using a procedure controlled by several key parameters. We then check the residuals of phase loop closure residuals and either nullify pixels in interferograms that probably contain unwrapping error, or attempt to correct the errors within connected components or pixel-wise using some basic assumptions, such as the minimal residue of the unwrapped data from a preliminary model estimate (whole time series velocity) is correct. All these approaches find their importance in different case studies and will be part of the next version of LiCSBAS.