InSAR Models Research Articles

Resolving Three-Dimensional Displacements Caused by Subsurface Fluid Activities From InSAR and Volumetric Strain Model: Adaptive Estimation of Model Parameters

Resolving Three-Dimensional Displacements Caused by Subsurface Fluid Activities From InSAR and Volumetric Strain Model: Adaptive Estimation of Model Parameters

Multi-Source SAR-Based Surface Deformation Monitoring and Groundwater Relationship Analysis in the Yellow River Delta, China

Land motions are significantly widespread in the Yellow River delta (YRD). There is, however, a lack of understanding of the delta-wide comprehensive deformation mode and its dynamic mechanism, especially triggered by groundwater extraction. This paper adopts an integrated analysis of multidisciplinary data of image geodesy, geophysics, geology and hydrogeology to provide insights into Earth surface displacement patterns and dynamics in the YRD. Delta-scale land motions were measured for the first time using L-band ALOS images processed using multi-temporal InSAR, illustrating multiple obvious surface sinking regions and a maximum annual subsidence velocity of up to 130 mm. Then, the InSAR-constrained distributed point source model with optimal kernel parameters, a smoothness factor of 10 and a model grid size of 300 m was established and confirmed to be rational, reliable and accurate for modeling analysis over the YRD. Remarkable horizontal surface displacements, moving towards and converging on a sinking center, were recovered by means of modeling and measured using InSAR, with a maximum rate of up to 60 mm per year, which can trigger significant disasters, such as ground fissures and building damage. In addition, the annual total water storage variation at the delta scale, the most meaningful outcome, can be calculated and reaches a total of approximately 12,010 × 103 m3 in Guangrao city, efficiently filling the gap of GRACE and in situ investigations for delta-wide aquifer monitoring. Finally, a comparative analysis of time series InSAR measurements, modeling outcomes, and fault and groundwater data was conducted, and the strong agreement demonstrates that faults control aquifer distribution and hence the spatial distribution of groundwater-withdrawal-related regional land subsidence. Moreover, the obvious asymmetric displacements, demonstrating a northeasterly displacement trend, further reveal that faults control aquifer distribution and Earth surface deformation. These findings are useful for understanding the land motion patterns and dynamics, helping to sustainably manage groundwater and control disasters in the YRD and elsewhere worldwide.

Integrating MODIS LST and Sentinel-1 InSAR to monitor frozen soil deformation in the Qumalai-Zhiduo area, Qinghai-Tibet Plateau

ABSTRACT Owing to continuous global warming, frozen soil degradation has become a universal phenomenon, leading to large-scale ground deformation that affects engineering construction and the fragile ecological balance. Geodetic observations, especially temporal InSAR, can quantify ground deformation. However, the accuracy of InSAR modelling in capturing the spatial–temporal variability of the freeze–thaw process depends on the spatial resolution of temperature measurements. This paper proposes a freeze–thaw amplitude model incorporating MODIS LST based on a single-master InSAR time-series deformation to calculate frozen soil deformation. We applied this model to the Qumalai-Zhiduo area of the Qinghai-Tibet Plateau and compared its results with those of the model using weather station temperature in terms of frozen soil deformation parameters, RSME, and characteristic targets. Our study found that the model incorporating MODIS LST performed better in areas far from weather stations, while both models produced similar results in areas of close proximity. Finally, we evaluated another commonly used method for calculating frozen soil deformation parameters and found that the method incorporating MODIS LST based on a single-master time-series deformation is more accurate and precise than the method based on a multi-master SBAS network.

Surface subsidence disasters over Xuzhou city, China 2014–2018 revealed by InSAR and Peck model

Surface subsidence disasters over Xuzhou city, China 2014–2018 revealed by InSAR and Peck model

Extensional Earthquakes in the Absence of Magma in Northern Afar: Insights From InSAR

AbstractIn magma‐rich rifts, normal faulting is commonly thought to be induced by dike intrusions. However, whether fault slip occurs purely tectonically is unclear. An earthquake sequence starting with a Mw 5.5 earthquake occurred in December 2022 in northern Afar, a continental rift near breakup. InSAR measurements show that seismicity was caused by normal faulting alone, without involvement of magma movements. Our best‐fit InSAR models show that conjugate faults ruptured during the seismic sequence with mainly normal dip‐slip and total deformation corresponding to a Mw 5.7 event, in agreement with local seismic recordings. Our models show that tectonic faulting accommodates 26 cm of extension corresponding to ∼30 years of plate spreading without any link to magma. Our observations point toward significant along‐rift variation in the proportion of extension from faulting, potentially caused by along‐rift variations in rate of extension and/or from a spatially and temporally segmented supply of magma.

Quantitative Prediction for Deformation and Brine Extraction in Salt Solution Mining Based on Water-Solution Kinetic (WSK) InSAR Model

Quantitative Prediction for Deformation and Brine Extraction in Salt Solution Mining Based on Water-Solution Kinetic (WSK) InSAR Model

Building risk monitoring and prediction using integrated multi-temporal InSAR and numerical modeling techniques

• Large-scale ground subsidence was measured using an improved MTInSAR method. • Building risk level was assessed at the district scale using InSAR measurements. • The simulated subsidence due to underground construction agreed with InSAR data. • The integrated method achieves building risk monitoring and prediction. Frequent anthropogenic activities associated with rapid urbanization may cause ground subsidence and endanger the adjacent buildings. Interferometric synthetic aperture radar (InSAR) has generated dense measurement points for large-scale deformation monitoring and risk assessment. However, the applications of InSAR for building deformation and risk level prediction are still rare, especially under complex loading scenarios. In this study, we present an integrated method to monitor and predict building deformation and risk levels using multi-temporal InSAR and numerical modeling. Persistent and distributed scatterers were jointly detected to monitor deformation using TerraSAR-X, COSMO-SkyMed, and Sentinel-1 images over the Kowloon district of Hong Kong and the Futian district of Shenzhen. First, the building risk level was assessed at the district scale using ground subsidence and angular distortion to identify potentially damaged buildings. 10 out of 807 buildings in the Kowloon and 2 out of 145 buildings in the Futian were classified as medium risk. Back-analysis was used to retrieve the geological and hydrological conditions of buildings at the medium risk level. Then, time-series subsidence of the Lucky and BMW buildings during 2012 to 2016 and the Jingli building during 2010 to 2014 was simulated by numerical modeling, which agreed well with the InSAR measurements. By defining the groundwater level changes and upper loading, the predicted subsidence of the Lucky, BMW, and Jingli buildings reached 47.9, 62.8, and 39.9 mm by 2021, respectively, with a decelerated trend. Time-series results showed that the Lucky and BMW buildings were still at the negligible-to-medium risk level in 2021, and should be constantly inspected; the risk level of the Jingli building became negligible from 2020. This method can be transferred to other rapidly urbanized areas prone to ground subsidence for geohazard assessment and improve the understanding of the dynamic behaviors of anthropogenic activity-induced ground subsidence.

InSAR and numerical modelling for tailings dam monitoring – the Cadia failure case study

In this paper, ground deformation measurements from synthetic aperture radar interferometry (InSAR) and ground-based prism monitoring are compared to finite-element (FE) simulation results for a recent tailings dam collapse. The InSAR monitoring demonstrated the complex spatial and temporal variability of the tailings dam deformation that is not captured in traditional, point-based monitoring approaches. Potentially anomalous deformation behaviour could have been detected from InSAR 1 year preceding the dam failure. A two-dimensional coupled-consolidation analysis was used to predict the dam behaviour during construction stages. The FE modelling results were in broad agreement with the deformation measurement sources, both in terms of magnitude and trends preceding failure. The results, however, deviate significantly immediately before failure, following the construction of the buttresses. Moreover, the FE modelling is sensitive to parameter uncertainties, such as spatial variability of foundation soil properties. The FE results revealed that deformation in both the upstream and downstream parts of the dam are sensitive to changing foundation properties. However, this impact is potentially much more significant on the downstream compared to the upstream parts of the dam, which are dominated by the behaviour of the tailings. This study highlights the efficacy and complementarity of geotechnical and remote sensing techniques for the monitoring of tailings dams.

Yield estimate for the January 2016 DPRK nuclear test based on InSAR and numerical modelling with mechanical heterogeneity

SUMMARY Interferometric Synthetic Aperture Radar (InSAR) provides a way of measuring ground deformation caused by underground nuclear testing via a satellite remote sensing platform. We present a finite-element model (FEM) of the nuclear test site in the Democratic People's Republic of Korea (DPRK, formerly North Korea) constrained by InSAR data. The model simulates elastic deformation caused by an underground explosion and includes high-resolution topography and mechanical heterogeneity. To the best of our knowledge, we are the first to investigate the effect of mechanical heterogeneity (a layered structure in our case) on deformation modelling at the DPRK test site. Sensitivity testing shows that inclusion of topography, mechanical layering and the combined effect results in 48.2, 22.6 and 91.5 per cent increase in the maximum predicted deformation, respectively. This suggests that previous models that do not account for these complexities may overestimate the nuclear yield and/or underestimate the depth of burial (DoB). We performed a parameter search to solve for the cavity size and DoB that best reproduce ground deformation observed in ALOS-2 InSAR data covering the DPRK's 4th nuclear test (DPRK4). Using these best-fit values with a cavity-yield scaling law, we estimate the yield of DPRK4 to be 10–20 kt at a DoB of 542–826 m. Our method provides an estimate that is independent from and complementary to traditional seismic methods, which is useful for a location that is data-limited.

Coseismic deformation and slip distribution of the 2017 Mw 6.3 Jinghe, Xinjiang, western China earthquake based on InSAR observations: a buried reverse event on previously unknown fault

SUMMARY The 2017 Mw 6.3 Jinghe earthquake occurred in the orogenic zone of the North Tianshan mountain range, Xinjiang, western China. No evident surface rupture was identified by field investigation conducted immediately after the earthquake. We investigate the coseismic and post-seismic deformation fields due to the Jinghe event using the C-band Sentinel-1 SAR imagery, and further analyse its causative fault. The Generic Atmospheric Correction Online Service for InSAR (GACOS) model is employed to remove the atmospheric phase delay of multiple InSAR deformation maps. Coseismic deformation fields are resolved by averaging the high quality deformation maps. A nonlinear inversion scheme is used to find the optimized fault geometry in a layered elastic crust. The results imply that the Jinghe earthquake is characterized by thrust faulting, with striking and dipping angles of ∼62° and ∼28°, respectively. Subsequently coseismic slip distribution is estimated using the steepest descent method program, constrained by the derived coseismic deformation fields. The inversion results show that the average slip is ∼0.08 m and the average rake angle is ∼98°. The maximum slip is ∼0.24 m, located at the depth of 12.9 km. The moment magnitude is estimated to be Mw 6.38. The fault geometry is generally consistent with the relocated aftershocks distribution. Both the InSAR-derived deformation field and the aftershock distribution indicate that the Jinghe earthquake is attributed to a previously unknown buried fault beneath the Yongji fold with a strike of 62°. No significant post-seismic deformation is identified in the zone of coseismic deformation. This study shows that the Jinghe earthquake is a typical inland thrust event in the North Tianshan area, which is affected by south to north compression due to the Indian-Eurasian collision.

InSAR Modeling and Deformation Prediction for Salt Solution Mining Using a Novel CT-PIM Function

Deformation prediction for a salt solution mining area is essential to mining environmental protection. The combination of Synthetic Aperture Radar Interferometry (InSAR) technique with Probability Integral Method (PIM) has proven to be powerful in predicting mining-induced subsidence. However, traditional mathematical empirical models (such as linear model or linear model combined with periodical function) are mostly used in InSAR approaches, ignoring the underground mining mechanisms, which may limit the accuracy of the retrieved deformations. Inaccurate InSAR deformations will transmit an unavoidable error to the estimated PIM parameters and the forward predicted subsidence, which may induce more significant errors. Besides, theoretical contradictory and non-consistency between InSAR deformation model and future prediction model is another limitation. This paper introduces the Coordinate-Time (CT) function into InSAR deformation modeling. A novel time-series InSAR model (namely, CT-PIM) is proposed as a substitute for traditional InSAR mathematical empirical models and directly applied for future dynamic prediction. The unknown CT-PIM parameters can be estimated directly via InSAR phase observations, which can avoid the error propagation from the InSAR-generated deformations. The new approach has been tested by both simulated and real data experiments over a salt mine in China. The root mean square error (RMSE) is determined as ±10.9 mm, with an improvement of 37.2% compared to traditional static PIM prediction method. The new approach provides a more robust tool for the forecasting of mining-induced hazards in salt solution mining areas, as well as a reference for ensuring the environment protection and safety management.

An InSAR and depth-integrated coupled model for potential landslide hazard assessment

An InSAR and depth-integrated coupled model for potential landslide hazard assessment

Time and path prediction of landslides using InSAR and flow model

Landslides originating from remote steep slopes render people living downhill vulnerable, unaware of the impending danger. Identifications of slow-moving mountain slopes are possible now due to time series measurement from space using microwave satellite data and the InSAR technique, which potentially can detect displacement at millimetre level. Availability of open-source Sentinel-1 data has revolutionised the study involving landslide kinematics and predicting the time of failure. However, identification of accelerating trend, demarcation of release area and prediction of flow path after failure initiation are still challenging. In this paper, we present a novel method for time and path prediction of landslides using two large landslides (Kikruma and Kotropi) located in the Himalayas in India. Sentinel-1 data stack was processed using the Persistent Scatterer and Small Baseline Subset interferometric techniques to analyse the trend of ground deformation leading to slope failures. The displacement time series of the measurement points, analysed using inverse velocity and modified inverse velocity methods, show that the instability had commenced almost a year or more with the final onset of acceleration triggered by heavy rainfall, couple of weeks prior to the actual failure. The acceleration image created from displacement time series data was clustered using image segmentation techniques to demarcate the release area of landslides. The flow simulation was done using the Voellmy friction model with a high-resolution DEM to predict the flow path. The analysis done for Kikruma and Kotropi landslide case studies with the proposed method provided a safe prediction of the time of landslide with ~90% accuracy of the flow path prediction. Results show that the method demonstrated in this study may evolve as an effective tool for landslide early warning in hilly areas.

Dry Snow Parameter Retrieval With Ground-Based Single-Pass Synthetic Aperture Radar Interferometry

In this article, we investigate the potential of using single-pass InSAR model-based approaches to retrieve dry snow parameters. Two InSAR scattering models of dry snow are considered: the dense-medium random volume over ground (RVoG) model and the simple variant of the full penetration (FP) model. A quasi-crystalline approximation (QCA)-based extinction analysis confirms the negligible extinction dependence of the InSAR observables at L/C/X-band for fresh dry snow. The FP models the low-frequency (L/C/X-band) InSAR phase as a single constraint of snow depth and density, which can be supplemented by an extra observation (e.g., InSAR coherence or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> depth/density). The single-pass InSAR models and inversion approaches were validated using X-band InSAR data collected from a tower-based three-frequency (X/Ku-low/Ku-high) fully polarimetric TomoSAR system, where a multi-frequency polarimetric InSAR analysis and ground-to-volume ratio-based snow condition analysis were conducted. We also analyzed the sensitivity and error propagation of the single-pass InSAR phase and coherence in measuring dry snow depth/density. It was found that the X-band HH-pol FP-modeled single-pass InSAR phase along with RVoG-modeled coherence or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> depth is capable of measuring snow water equivalent (SWE) with a 23–26 mm uncertainty (13–15%) and a 20–26 mm bias (12–15%) for dry snow SWE of 0.2 m, and with an optimal perpendicular baseline on the order of a tenth of the snow depth (0.8 m) at our test site. This single-pass InSAR approach with the FP model is potentially useful and thus needs further investigation for large-scale dry snow retrieval with a wide range of snow conditions using ground-based/airborne/spaceborne low-frequency (L/C/X-band) InSAR observations.

Measuring Subsidence Over Soft Clay Highways Using a Novel Time-Series InSAR Deformation Model With an Emphasis on Rheological Properties and Environmental Factors (NREM)

Long-term monitoring of highways in soft soil areas, especially during the postconstruction period, is of great significance to ensure transportation safety and the quality of highway construction. Multitemporal interferometric synthetic aperture radar (MTInSAR) provides an effective tool for soft clay highway monitoring. However, most time-series models used in MTInSAR modeling are empirical mathematical functions, which ignores the physical properties of the observed objects and may limit the accuracy of the retrieved deformation and the understanding of the underground settlement dynamics. We propose a novel InSAR time-series deformation model (namely, NREM) with an emphasis on the rheological mechanisms for soft soil highways and environmental factors (temperature, humidity, and precipitation) to improve the accuracy of the traditional InSAR model and assist in the analyzing the rheological properties of soft soil. The NREM is constructed based on a combination of the seasonal model and the Burgers model introduced from the field of rheology. The primary parameters (i.e., viscosity and elastic modulus) are introduced in the NREM and estimated with the generation of time-series surface deformation. In the real data experiments, two highways are selected as the test areas. The results show that the standard deviations (STDs) of the high-pass deformation, which can reflect the modeling accuracy, derived by the NREM are lower than those of the three traditional models, yielding an improvement of 45&#x0025; for the Lungui Highway (LH) and 50&#x0025; for the G1508 Highway (GH). The root mean square errors (RMSEs) for deformation results derived from NREM are estimated to be &#x00B1;5.1 mm compared with the leveling measurements, which outperforms the traditional models. The obtained rheological parameters can broaden the application of InSAR technology and provide a reference for highway engineering.

THE LATEST DTM USING INSAR FOR DYNAMICS DETECTION OF SEMANGKO FAULT-INDONESIA

The latest Digital Terrain Model (DTM) is seen as an upgradable DTM that is fitted to the latest combination of DTM master and its displacement. The latest DTM can be used to overcome the problem of static DTM weaknesses in displaying the latest topographic changes. DTM masters are obtained from InSAR and Digital Surface Model (DSM) ALOS PALSAR conversions. Meanwhile, the displacement is obtained from Sentinel-1 images, which can be updated every 6–12 days or at least every month. ALOS PALSAR data were the images acquired in 2008 and 2017, while Sentinel-1 data used were images acquired in 2018 and 2020. This study aims to reveal the importance of an upgradable DTM so called latest DTM which is combination of DTM master and its displacement in order to show the latest condition of study area. The case study is the dynamics analyze of the Semangko fault specifically in the Sianok and Sumani segments situated in Indonesia. The vertical accuracy assessment was done to evaluate the DSM to DTM conversion with a tolerance of 1.96σ. The result obtained is the latest DTM. It is derived from the integration of the DTM master with displacement. The latest DTM can be used to detect the dynamics of Semangko fault. The study area has vertical deformation at a value of –50 cm to 30 cm. The Semangko fault area is dominated by –25 to 5 cm deformation. In general, this region has decreased. The decline in this region ranges from 7.5 cm to 10 cm per year. The latest DTM vertical accuracy is 2.158 m (95% confidence level) with a scale of 1: 10,000 to 1: 20,000.

The March 2021 Tyrnavos, central Greece, doublet (Μw6.3 and Mw6.0): Aftershock relocation, faulting details, coseismic slip and deformation

On 3 March 2021, the Mw6.3 Tyrnavos earthquake shook much of the Thessalia region, leading to extensive damage in many small towns and villages in the activated area. The first main shock was followed in the next day, on 4th of March 2021, by an “equivalent” main shock with Mw6.0 in the adjacent fault segment. These are the largest earthquakes to strike the northeastern part of Thessalia since the M6.3, 1941 Larissa earthquake. The main shocks triggered extensive liquefaction mainly along the banks of the Titarisios tributary where alluvial flood deposits most probably amplified the ground motions. Our seismic monitoring efforts, with the use of recordings of the regional seismological network along with a dense local network that was installed three days after the seismic excitation initiation, led to the improved understanding the geometry and kinematics of the activated faults. The aftershocks form a north–northwest–trending, east–northeast–dipping, ~40 km long distribution, encompassing the two main ruptures along with minor activated structures, consistent with the rupture length estimated from analysis of regional waveform data and InSAR modeling. The first rupture was expanded bilaterally, the second main shock nucleated at its northern tip, where from this second rupture propagated unilaterally to the north–northwest. The focal mechanisms of the two main shocks support an almost pure normal faulting, similar to the aftershocks fault plane solution determined in this study. The strong ground motion of the March 3 main shock was computed with a stochastic simulation of finite fault model. Coseismic displacements that were detected using a dense GPS / GNSS network of five permanent stations located the Thessaly region, have shown an NNE–SSW extension as expected from the nature and location of the causative fault. Coulomb stress changes due to the coseismic slip of the first main shock, revealed that the hypocentral region of the second main shock was brought closer to failure by more than 10 bars.

Combining Satellite InSAR, Slope Units and Finite Element Modeling for Stability Analysis in Mining Waste Disposal Areas

Slope failures pose a substantial threat to mining activity due to their destructive potential and high probability of occurrence on steep slopes close to limit equilibrium conditions, which are often found both in open pits and in waste and tailing disposal facilities. The development of slope monitoring and modeling programs usually entails the exploitation of in situ and remote sensing data, together with the application of numerical modeling, and it plays an important role in the definition of prevention and mitigation measures aimed at minimizing the impact of slope failures in mining areas. In this paper, a new methodology is presented; one that combines satellite radar interferometry and 2D finite element modeling for slope stability analysis at a regional scale, and applied within slope unit polygons. Although the literature includes many studies applying radar interferometry and modeling for slope stability analysis, the addition of slope units as input data for radar interferometry and modeling purposes has, to our knowledge, not previously been reported. A former mining area in southeast Spain was studied, and the method proved useful for detecting and characterizing a large number of unstable slopes. Out of the 1959 slope units used for the spatial analysis of the radar interferometry data, 43 were unstable, with varying values of safety factor and landslide size. Out of the 43 active slope units, 21 exhibited line of sight velocities greater than the maximum error obtained through validation analysis (2.5 cm/year). Finally, this work discusses the possibility of using the results of the proposed approach to devise a proxy for landslide hazard. The proposed methodology can help to provide non-expert final users with intelligible, clear, and easily comparable information to analyze slope instabilities in different settings, and not limited to mining areas.

Coupling InSAR and numerical modeling for characterizing landslide movements under complex loads in urbanized hillslopes

Landslides, as a representative geohazard in fault zones, threaten the safety of buildings and infrastructure. Landslide movements are often subject to multiple loads in urbanized hillslopes from both natural and human activity. Synthetic aperture radar interferometry (InSAR) has been used to measure landslide movements. Used independently, InSAR can measure only surface deformation, and the points are sparse. Numerical modeling can simulate the full-scale movements, but it requires a prior knowledge of soil properties that are often not available in practice. To address these limitations, we proposed to couple InSAR and numerical modeling for characterizing landslide movements under multiple loads. We used 60 ascending and 56 descending Sentinel-1 images to measure surface movements in urbanized Daguan County Town. Of 31 landslides in the inventory map, 24 were successfully identified. The InSAR results assisted in determining the optimal soil properties through back-analysis. We used geological, geotechnical, and meteorological data to set three boundary conditions, that is, body loads, precipitation-induced hydraulic conditions, and construction-induced forces. Landslide mobility was demonstrated more distinctly using the coupled analysis. The numerical results revealed that body loads dominated the cumulative downslope movements by squeezing water and air from voids, and precipitation caused seasonal movements with the direction perpendicular to the slope surface. Construction works caused permanent changes (accelerating and decelerating) in time-series trends. Coupling InSAR and numerical modeling can facilitate analysis of the effects of complex loads and potentially predict future deformation. The method developed can be extended to study other urbanized landslide areas for early warning and risk mitigation.

Surface Deformation Retrieving Over Soft Clay Based on an Improved Time Series InSAR Model: A Case Study of Dongting Lake Area, China

The infrastructures built on soft clay in the Dongting Lake area are more prone to settlement and instability due to its significant rheological properties. It is of great importance to conduct a long-term surface deformation monitoring over this area. The most commonly used Synthetic Aperture Radar Interferometry (InSAR) deformation models are based on combinations of one or several pure empirical mathematical functions without considering the physical and mechanical characteristics of the observed objects. In this work, we propose an improved deformation model based on the functional relationship between strain and time in the Maxwell rheological model. The rheological parameters of elastic modulus and viscosity are introduced into a traditional empirical seasonal model. The improved model is applied for the investigation of the spatial-temporal surface evolution over the Dongting Lake area with the Small Baseline Subset InSAR (SBAS-InSAR) technology and TerraSAR-X satellite imagery. With the proposed model, the rheological parameters and the time series deformation are estimated, with the maximum accumulated subsidence estimated as 38 mm. Through the analysis of the generated results, we find that the lower the viscosity and elastic modulus are, the higher the deformation is. Temporally, the overall deformation follows a generally subsiding trend with a seasonal recovery of 5 mm from October 2012 to November 2012 and 12 mm from January 2013 to February 2013. To compensate for the deficiency of the unavailability of external geodetic measurements over this area, three different accuracy indexes (residual phase, temporal coherence, and high-pass deformation) are utilized to evaluate the modeling accuracy. The results of the improved model are also compared to three traditional models (seasonal model, cubic polynomial model, and linear model). The comparison shows that the improved model is highly recommended in this area because of its better accuracy.