Persistent Scatterer SAR Interferometry Research Articles

Analysis of Urbanization-Induced Land Subsidence in the City of Recife (Brazil) Using Persistent Scatterer SAR Interferometry

The article addresses anthropogenic and geological conditions related to the development of soil subsidence in the western zone of Recife (Brazil). Over the past 50 years, human activity has intensified in areas previously affected by soft soils (clay, silt, and sandstone) resulting in subsidence due to additional loads (landfills and constructions). The duration of the settlement process can be significantly influenced by the specific characteristics of the soil composition and geological conditions of the location. This work presents, for the first time, accurate InSAR time series maps that describe the spatial pattern and temporal evolution of the settlement, as well as the correlation with the geological profile, and validation with Global Navigation Satellite System (GNSS) data. Persistent Scatterer Interferometry (PS-InSAR) was employed in the analysis of Single Look Complex (SLC) images generated by 100 ascending COSMO-SkyMed (CSK) and 65 PAZ (32 ascending, and 33 descending) from the X-band, along with 135 descending Sentinel-1 (S1) acquisitions from the C-band. These data were acquired over the period from 2011 to 2023. The occurrence of subsidence was identified in several locations within the western region, with the most significant displacement rates observed in the northern, central, and southern areas. In the northern region, the displacement rates were estimated to be approximately −20 mm/year, with the Várzea and Caxangá neighborhoods exhibiting the highest rates. In the central region, the displacement rates were estimated to be approximately −15 mm/year, with the Engenho do Meio, Cordeiro, Torrões, and San Martin neighborhoods exhibiting the highest rates. Finally, in the southern region, the displacement rates were estimated to be up to −25 mm/year, with the Caçote, Ibura, and Ipsep neighborhoods exhibiting the highest rates. Additionally, east–west movements were observed, with velocities reaching up to −7 mm/year toward the west. These movements are related to the lowering of the land. The study highlights that anthropogenic effects in the western zone of Recife contribute to the region’s vulnerability to soil subsidence.

Flood subsidence susceptibility mapping using persistent scatterer SAR interferometry technique coupled with novel metaheuristic approaches from Jeddah, Saudi Arabia

Flood subsidence susceptibility mapping using persistent scatterer SAR interferometry technique coupled with novel metaheuristic approaches from Jeddah, Saudi Arabia

Estimating Land Subsidence and Gravimetric Anomaly Induced by Aquifer Overexploitation in the Chandigarh Tri-City Region, India by Coupling Remote Sensing with a Deep Learning Neural Network Model

This study utilizes surface displacement data from Persistent Scatterer SAR Interferometry (PSInSAR) of Sentinel-1 satellite and groundwater storage change data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to understand land subsidence in the Chandigarh tri-city region. The satellite datasets are used along with the groundwater level data obtained from wells over the study area. Since the GRACE data are available at a much coarser spatial resolution of 1o by 1o, challenges remain in correlating the dataset with PSInSAR displacement that has been multi-looked at 14 m by 14 m resolution. Therefore, multiple sources of data (i.e., the monthly average of GRACE data, groundwater storage change and monthly average PSInSAR displacement per pixel, and interpolated groundwater level data from wells for 2017 to 2022) have been deployed into a deep learning multi-layer perceptron (DLMLP) model to estimate the groundwater storage change at the urban level. This has an indirect downscaling method that is carried out successfully using the DLMLP model for the estimation of groundwater storage changes at the urban level, which is usually complicated by applying direct downscaling methods on the GRACE data. Thus, the DLMLP model developed here is a distinctive approach considered for estimating the changes in groundwater storage using PSInSAR displacement, groundwater data from wells, and GRACE data. The DLMLP model gives an R2-statistics value of 0.91 and 0.89 in the training and testing phases, respectively, and has a mean absolute error (MAE) of 1.23 and root mean square error (RMSE) of 0.87.

PS干渉SAR解析によって推定された阪神エリアにおける活断層近傍の地表変動

干渉SAR時系列解析は年単位での地表変動傾向を明らかにするのに有効な手法である．本研究では，2018年に発生した大阪北部地震の震源付近の断層である有馬―高槻断層帯，及び六甲山活動セグメント近傍における地震前後を含む近年の地表変動傾向を明らかにするためにPS干渉SAR解析を用いることによって当地域における地表変動量を検出した．その結果，（i）六甲山活動セグメント近傍における沈降方向の地表変動，（ii）箕面GNSS観測点付近及び，有馬―高槻断層帯及び六甲山活動セグメントの間に位置するくさび型のエリアにおいて地表変動が地震後に隆起方向に変化し，その地表変動が地下水位の変動によるものであると示唆されること，（ⅲ）生駒断層と上町断層の間の広域において隆起と考えられる地表変動の要因が地下水位の変動による可能性，また（ⅳ）震源断層のすべりによる西向き方向の震央周辺の地表変動の可能性を示した．さらに，本研究のPS干渉SAR解析結果の妥当性がGNSSの結果及び先行研究との比較によって示された．断層周辺部における地表変動のメカニズムを解明するために，今後も継続的に同エリアにおける干渉SAR時系列解析を用いた地表変動の解析を行う必要がある．

Deformation monitoring of Surakachhar underground coal mines of Korba, India using SAR interferometry

Underground mines around the globe experience the deformation/subsidence due to the wornd practiced of the mining activity or by the geological failure. In this study deformation monitoring of Korba underground coal mines in Chhattisgarh, India was performed using the Synthetic aperture radar remote sensing. In this study, the Surakachhar 5/6 underground coal mining region of Korba area and its surrounding are considered for deformation/displacement monitoring. The displacement estimation was generated using Advanced Differential Interferometric Synthetic Aperture Radar (ADInSAR) technique: Persistent Scatterer SAR interferometry (PSInSAR) and Ground-based investigation for validation and impact assessment have also been performed. PSInSAR results, obtained by processing of 17 Sentinel-1A images (Feb-2015 to Feb-2017) showed that multiple areas above the underground mining have been deformed around 3 mm/year to −21 mm/year along the radar line of prospect. Deformed regions are mainly on the surface of active mining areas and settlements. Deformation mapping using PSInSAR with ground-based investigation provides an account learning of Surakachhar underground mining activities, consequences such as sag, pit and cracks in the area. This technique helps to predict the hazard-prone deformation/subsidence zone and to prevent serious damage due to roof failure in the near future.

Landslide deformation and temporal prediction of slope failure in Himalayan terrain using PSInSAR and Sentinel-1 data

Landslides in hilly terrains are frequent phenomenon due to various triggering factors such as heavy rainfall, flash flood, slope instability, tectonic disturbances etc., and result in loss of human lives and damage of infrastructure and property. The continuous monitoring of slope instability and temporal prediction of slope failure is of paramount importance for assessing landslide-triggering factors and mitigating landslide hazards. This research presented a comprehensive methodology for time-series displacement measurement of a landslide-affected area prior to its actual failure and temporal prediction of slope failure in a hilly terrain using persistent scatterer SAR interferometry (PSInSAR) technique and Sentinel-1 data in an open source computational environment. On 30 July 2021, a massive landslide witnessed in Sirmaur district of Himachal Pradesh, India near Barwas and brought down around 180 m stretch of national highway (NH) 707 connecting Paonta Sahib with Shillai-Hatkoti. We used 52 single look complex (SLC) images in ascending and 41 SLC images in descending orbit with VV polarization, acquired for a period of almost two years (2019–2021) for time-series displacement measurement along radar line of sight (LOS), horizontal and vertical directions. The pre-failure displacement-time series derived from ascending and descending data stacks was critically analyzed to identify the reliable and accelerating persistent scatterer (PS) locations for predicting temporal failure of slope material and to understand kinematics of the study area. We used inverse velocity (INV) and modified inverse velocity (T-INV) methods at three different accelerating and reliable PS locations for temporal prediction of slope failure. The results show that the mean LOS velocity ranges from −25.49 to + 31.35 mm/y in ascending data and from −20.97 to + 24.16 mm/y in descending data, and horizontal and vertical components of motion vector vary from −30.23 to + 18.99 mm/y and –23.16 to 25.79 mm/y respectively in the study area. Displacement time-series at selected measurement points (PSs) depict the initiation of slope instability from 31 July 2020 and 3 July 2020 using ascending and descending stacks respectively, which are almost one year before the actual failure. INV method predicted temporal windows of slope failure between 27 July 2021 to 1 August 2021 for ascending stack and 24 July 2021 to 29 July 2021 using descending stack, while those of T-INV method lye between 28 July 2021 to 1 August 2021 for ascending data and between 22 July 2021 to 30 July 2021 for descending data. The deformation-time series and predicted days of slope failure are in good agreement at different reliable PS locations. Results in this study show that the approach used for time failure may evolve as an effective tool for landslide early warning systems.

A comparative case study of MTInSAR approaches for deformation monitoring of the cultural landscape of the Shanhaiguan section of the Great Wall

The Great Wall of China is one of the largest architectural heritage sites globally, and its sustainability is a significant concern. However, its large extent and diverse characteristics are challenges for deformation monitoring. In this study, the Shanhaiguan section of the Great Wall was investigated in a case study to ascertain the damage and potential hazards of the architectural site. Two standard multi-temporal synthetic aperture radar interferometry (MTInSAR) technologies, including persistent scatterer SAR interferometry (PSInSAR) and small baseline subset (SBAS) SAR interferometry, were used for deformation monitoring using high-resolution TerraSAR-X data acquired in 2015–2017. The results of the two MTInSAR approaches reveal the health condition of the Great Wall. The Shanhaiguan section was stable, but local instabilities caused by rock falls were detected in some mountainous areas. In addition, the applicability of PSInSAR and SBAS was evaluated. The performance analysis of the two approaches indicated that a more reliable and adaptable MTInSAR technique needs to be developed for monitoring the Great Wall. This study demonstrates the potential of MTInSAR technology with high-resolution data for the health diagnosis of heritage sites with a linear structure, such as the Great Wall.

Monitoring of Power Towers’ Movement Using Persistent Scatterer SAR Interferometry in South West of Tehran

The Tehran basin has been increasingly affected by subsidence during the last few decades due to groundwater withdrawal. Hence, the study of the strength of the power towers (PTs) of transmission lines, as vital structures, is an important subject. In this paper, the persistent scatterer interferometry (PSI) method was applied on data stacks from two satellites (i.e., X-band COSMO-SkyMed (CSK) and C-band Sentinel-1A (S-1A)) obtained between 2014 and 2016 to investigate the deformation and the exact amount of displacement in each PT of the area of interest. Based on the results, during the same time interval (between October 2014 and February 2016), the vertical velocities calculated using CSK and S-1A were about −86 and −79 mm/y, respectively. Although the CSK data analysis resulted in a better displacement interpretation of PTs, due to its high resolution and shorter wavelength, the S-1 data analysis also demonstrated sufficient persistent scatterer (PS) points. The research proves that most of the PTs along a transmission line are affected by high land subsidence, which puts them in a serious jeopardy. They must be constantly monitored to ensure their safety and accurate operation. The results are in complete agreement with information of the existing global positioning system (GPS) station in our study area and also the observations of two piezometric wells with declining trends in the groundwater reservoir, which has the greatest effect on the subsidence rate in this area. The analysis revealed that the strength of PTs is at a high risk.

A fuzzy identification method for persistent scatterers in PSInSAR technology

Persistent Scatterer SAR Interferometry (PSInSAR) is known as one of the most effective technique for monitoring and analyzing ground deformation. It is a key step that how to identify Persistent Scatterers (PS) effectively and automatically from time-series SAR images. In the past research, one pixel will be classified to "PS" set or "no-PS" set clearly by one or more threshold rules for PS features. However, it is easy to fall into the 'either this or that' logical paradox in some cases because the covered objects in study area usually possess ambiguous boundary for interested characteristics. In this paper, a fuzzy PS concept is present and a fuzzy identification method is designed based on fuzzy set theory by taking the fuzzy characteristics of the pixels into account. Two groups of real data tests indicate that the new method can not only recognize more effective and reliable PS, but also can obtain the better quality results of selected PS, which can be used to evaluate the result of deformation and further improve the PSInSAR technology.

Deformation Monitoring and Analysis of the Geological Environment of Pudong International Airport with Persistent Scatterer SAR Interferometry

Many coastal cities have undertaken reclamation projects to satisfy the land demands of rapid urbanization. However, the foundations of reclaimed land are susceptible to settlement and can have undesirable environmental impacts that could adversely affect these dense, populated areas. In the case of international airports built on reclaimed areas especially, regional-scale deformation must be monitored to ensure operational security for public safety. Persistent Scatterer SAR Interferometry (PSI) technology has proven to be an effective tool to detect ground deformation in urban areas. However, it is still a challenge to apply PSI to effectively monitor settlement at airports built on newly developed coastal reclamation areas because of the scarcity of identifiable targets. Moreover, additional issues arise as the complicated deformation patterns associated with the underlying geological conditions make it difficult to interpret InSAR-derived results. In this study, a time-series analysis of a high-resolution TerraSAR-X satellite image stack acquired from September 2011 to October 2012 was performed by employing a modified PSI technique to retrieve the mean deformation velocity and time series of surface deformation at Pudong International Airport. Qualitative evaluation of spatial distribution and temporal evolution of deformation was conducted by joint analyses of deformation measurements and local geological data. Detailed analysis of various driving forces for deformation patterns confirmed that the results of deformation monitoring obtained by PSI are reliable and consistent with that of local geological surveys. Since the factors responsible for the subsidence within the airport are still at play, ongoing and routine deformation monitoring is warranted.

A study on measuring surface deformation of the L’Aquila region using the StaMPS technique

ABSTRACTThis research compares two time-series interferometric synthetic aperture radar (InSAR) methods, namely persistent scatterer SAR interferometry (PS-InSAR) and small baseline subset (SBAS) to retrieve the deformation signal from pixels with different scattering characteristics. These approaches are used to estimate the surface deformation in the L’Aquila region in Central Italy where an earthquake of magnitude Mw 6.3 occurred on 6 April 2009. Fourteen Environmental Satellite (ENVISAT) C-band Advanced Synthetic Aperture Radar (ASAR) images, covering the pre-seismic, co-seismic, and post-seismic period, are used for the study. Both the approaches effectively extract measurement pixels and show a similar deformation pattern in which the north-west and south-east regions with respect to the earthquake epicentre show movement in opposite directions. The analysis has revealed that the PS-InSAR method extracted more number of measurement points (21,103 pixels) as compared to the SBAS method (4886 pixels). A comparison of velocity estimates shows that out of 833 common pixels in both the methods, about 62% (517 pixels) have the mean velocity difference below 3 mm year−1 and nearly 66% pixels have difference below 5 mm year−1. It is concluded that StaMPS-based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean line of sight (LOS) velocity as compared to SBAS method.

PS干渉SAR解析を用いた関東平野北部の地盤沈下域の推定

PS干渉SAR解析を用いた関東平野北部の地盤沈下域の推定

Heterogeneous surface displacement pattern at the Hatchobaru geothermal field inferred from SAR interferometry time-series

We estimated surface displacements using persistent scatterer SAR interferometry (PS-InSAR) around the Hatchobaru geothermal field, Japan, from 18 ALOS/PALSAR images acquired from July 2007 to December 2010. Generally, geothermal fields, covered with natural targets such as rocky terrain and vegetation, have been one of the difficult targets for PS-InSAR analysis. However, we applied space adaptive filtering to increase the number of pixels for measuring surface displacement. The results of our analysis demonstrate ground subsidence with decaying velocity over the observation period around the geothermal field. The spatial pattern of ground subsidence includes sharp boundaries of subsidence that can be interpreted as fault traces. We demonstrated the usefulness of PS-InSAR analysis with the space adaptive filtering to estimate surface displacements with high spatial resolution and high spatial density around a geothermal field.

Spatial–temporal evolution patterns of land subsidence with different situation of space utilization

Long-term over-exploitation of underground water, static and dynamic load is increasing year by year, which influenced the occurrence and development of regional land subsidence in Beijing, China. We used Envisat advanced synthetic aperture radar data acquired from 2003 to 2009 and PSI (persistent scatterers for SAR interferometry) and small baseline technology to estimate regional land subsidence information in Beijing, China. In different situation of space utilization, we chose five typical settlement areas according to classified information of land-use, multi-spectral remote sensing images and geological data. We analyzed the time-series evolution characteristics of uneven subsidence by GIS spatial analysis. The comparative analysis results suggest that for five typical settlement areas, the complex situations of space utilization affect the trend of uneven subsidence, the simpler space utilization situation (relatively fewer transport lines, construction), the smaller settlement differences and the smaller trend of the uneven subsidence.

Spatial correlation between land subsidence and urbanization in Beijing, China

The large-scale construction of buildings, extensive road and rail networks, and increased traffic flow associated with urbanization has the potential to cause land subsidence. Land subsidence caused by urbanization is an increasingly significant problem in Beijing, China; therefore, it is important to investigate the relationship between urbanization and land subsidence. Landsat TM images covering the Beijing plain were used to acquire spatial changes information of built-up areas by calculating an index-based built-up index (IBI). We used ENVISAT Advanced Synthetic Aperture Radar data acquired from 2003 to 2009 and persistent scatterers for SAR interferometry (PSI) technology to estimate land subsidence. Geographic information systems spatial analysis method was used to identify the relationship between the settlement rate and the IBI value for three different sampling units. The result showed that it was a positive correlation between construction density and land subsidence; for land subsidence, the effect from the combination of high-density building clusters and extensive transportation networks was more significant than the presence of buildings alone. However, there may be a delay between the completion of building construction and the development of land subsidence.

Landslide inventory updating by means of Persistent Scatterer Interferometry (PSI): the Setta basin (Italy) case study

This paper illustrates the contribution of Persistent Scatterer SAR Interferometry (PSInSAR) technique to landslide detection, using interferometric data acquired in C-band by European remote-sensing satellite (ERS) 1/2 and environmental satellite (ENVISAT) satellites. The main purpose is to update a pre-existing landslide inventory map, by changing or confirming the landslide geometry and state of activity and eventually, identifying new phenomena.This work presents an application of satellite remote sensing to analyse ground displacement movements in the Setta basin, located on the northern Appennine (Bologna province, Italy) and extended up 268 km2.The proposed methodology, resting upon pre-existing works already consolidated in the scientific community, combines interferometric measures with aerial imagery and other auxiliary data, in order to detect landslide indicators, finally validated with field surveys. The use of an activity matrix allows the identification of the state of activity of landslide phenomena with respect to the velocity of the radar displacement rates. Field validations are carried out in the areas that are more relevant because of the highest ground velocities and the presence of structures extensively affected by ground movements.The final updated landslide database of the Setta basin, based on Persistent Scatterer Interferometry analysis and in situ checks, consists of 1550 landslides, 236 of which have persistent scatterer information.

Monitoring subsidence rates along road network by persistent scatterer SAR interferometry with high-resolution TerraSAR-X imagery

Ground subsidence is one of the key factors damaging transportation facilities, e.g., road networks consisting of highways and railways. In this paper, we propose to apply the persistent scatterer synthetic aperture radar interferometry (PS-InSAR) approach that uses high-resolution TerraSAR-X (TSX) imagery to extract the regional scale subsidence rates (i.e., average annual subsidence in mm/year) along road networks. The primary procedures involve interferometric pair selection, interferogram generation, persistent scatterer (PS) detection, PS networking, phase parameterization, and subsidence rate estimation. The Xiqing District in southwest Tianjin (China) is selected as the study area. This district contains one railway line and several highway lines. A total of 15 TSX images covering this area between April 2009 and June 2010 are utilized to obtain the subsidence rates by using the PS-InSAR (PSI) approach. The subsidence rates derived from PSI range from −68.7 to −1.3 mm/year. These findings show a significantly uneven subsidence pattern along the road network. Comparison between the PSI-derived subsidence rates and the leveling data obtained along the highways shows that the mean and standard deviation (SD) of the discrepancies between the two types of subsidence rates are 0.1 and ±3.2 mm/year, respectively. The results indicate that the high-resolution TSX PSI is capable of providing comprehensive and detailed subsidence information regarding road networks with millimeter-level accuracy. Further inspections under geological conditions and land-use categories in the study area indicate that the observed subsidence is highly related to aquifer compression due to groundwater pumping. Therefore, measures should be taken to mitigate groundwater extraction for the study area.

A Comparison of Precise Leveling and Persistent Scatterer SAR Interferometry for Building Subsidence Rate Measurement

It is well known that the most accurate method to detect changes of height is the geodetic precise leveling method. Due to the high demand work and time needed for precise leveling alternative methods are studied to obtain high quality height information. Differential SAR interferometry techniques such as the Persistent Scatterer Interferometry (PSI) method are studied to detect millimeter level deformations in urban areas. Additionally, SAR analysis will provide spatially extensive information on subsidence. On the other hand, PSI subsidence rates have not yet been comprehensively compared to the precise leveling measurements of the subsidence of individual buildings. Typically subsidence rates are interpolated to a continuous spatial surface, but in this study, spatially discontinuous subsidence was measured for a set of individual buildings. Therefore, we conducted three precise leveling campaigns and measured in total 82 geodetic-grade bolts, which were tightly attached to the building foundations. Moreover, we used additional leveling data (obtained from the local authorities), which contained long time series of leveling data for individual buildings. In the present study, ERS and ENVISAT satellite SAR data were processed using a PSI algorithm and the results were compared to leveling data of individual buildings.

Hybrid conventional and Persistent Scatterer SAR interferometry for land subsidence monitoring in the Tehran Basin, Iran

Excessive groundwater extraction has caused land subsidence in a large rural area located southwest of Tehran, Iran. We used radar images to estimate the temporal and spatial variation in the magnitude of the subsidence. Due to the large perpendicular baselines and rapid temporal decorrelation of the available data, the application of conventional synthetic aperture radar interferometry (InSAR) to monitor the deformation was not possible. Instead, we applied a recently developed Persistent Scatterer InSAR (PSI) method but found that displacements were underestimated in some areas due to high deformation rates that cause temporal aliasing of the signal. We therefore developed a method that combines conventional InSAR and PSI to estimate the high deformation rates in the southwestern Tehran Basin. We used rates estimated from conventional small temporal baseline interferograms to reduce the likelihood of aliasing and then applied PSI to the residual phase. The method was applied to descending and ascending ENVISAT ASAR images spanning from 2003 to 2009. Mean line-of-sight velocities obtained from both orientations that were further decomposed into horizontal and vertical deformation components were highly compatible with each other, indicating the high performance of the applied method. The mean precision of the estimated vertical component is 2.5mm/yr. We validated our results using measurements from a continuous GPS station located in one of the subsiding areas. The results also compare favourably with levelling data acquired over a different time interval. Finally, we compared the estimated displacements to hydraulic head variations and geologic profiles at several piezometric wells. We found that the geology is the most important factor controlling the subsidence rate in the southwestern Tehran Basin, regardless of the water level decline.

Monitoring of active tectonic deformations in the Longitudinal Valley (Eastern Taiwan) using Persistent Scatterer InSAR method with ALOS PALSAR data

This paper presents new observation of the interseismic deformation along the Longitudinal Valley (Eastern Taiwan) that represents a major tectonic boundary of the Taiwan collision zone. We investigate the southern part of the Valley from Rueisuei to Taitung (latitude 23.5°N–22.7°N), which is the part of the Valley where interseismic surface creep has already been observed at some points of the Longitudinal Valley Fault (LVF). A Persistent Scatterer SAR interferometry approach (StaMPS) is applied using ten L-band SAR images from ALOS satellite acquired over the period 2007–2010. Interferograms from L-Band data show a dramatic improvement of coherence in comparison to previous studies using C-Band ERS data. The density of measurement resulting from StaMPS processing is the highest achieved so far in the area (about 40–55 points per km2 for a total of 77,000 points) allowing a continuous view of the deformation along the Valley and also giving information on its borders (Central Range and Coastal Range). The most striking feature of the resulting mean velocity map is a clear velocity discontinuity localized in a narrow band (0.1–1km) along the LVF and responsible for up to 3cm/yr velocity offset along the radar line of sight, which is attributed to shallow interseismic creep. InSAR results are in good agreement with continuous GPS measurements over the same period (0.3cm/yrrms). The density of measurement allows us to improve fault trace map along the creeping section of the LVF (with accuracy of about 100m) and to find new field evidences of the fault activity. In some places, our trace differs significantly (hundreds of meters) from previous published traces. The creep rate shows significant variations along the fault. At the southern end of the valley the deformation is distributed on several structures, including the Luyeh Strand, and drops significantly south of the Peinanshan. However there are discrepancies with previous studies made from ERS data over the period 1993–1999 that remain to be investigated. The mean velocity for each point of measure and the improved faults' trace are provided as Supplementary data.