Persistent Scatterer Points Research Articles

A Persistent Scatterer Point Selection Method for Deformation Monitoring of Under-Construction Cross-Sea Bridges Using Statistical Theory and GMM-EM Algorithm

Using traditional algorithms to identify persistent scatterer (PS) points is challenging during bridge construction because of short-term changes at construction sites, such as earthworks, as well as the erection and dismantling of temporary structures. To address this issue, this study proposes a PS point selection method based on statistical theory and Gaussian Mixture Model-Expectation Maximization (GMM-EM) algorithm. This method adopts amplitude information as an incoherence evaluation indicator. Furthermore, the statistical median of the amplitude dispersion index and amplitude mean is screened twice to extract a set of candidate points, including PS points that exhibit stable backscattering over long durations. Temporal coherence is simultaneously used as the coherence evaluation indicator. Another candidate point set is obtained by extracting high-coherence PS points using the GMM-EM algorithm. These sets of candidate points are then combined to obtain a final PS points set. In the experiment, the deformation monitoring of the under-construction Shenzhen-Zhongshan Cross-Sea Bridge in China was selected as a case study, with 28 Sentinel-1A images used as the data source for PS selection and deformation information extraction. The results show that the proposed method enhanced the density and quality of PS points on the under-construction cross-sea bridge compared to existing PS selection methods, thus offering higher reliability. Deformation analysis further revealed fluctuating deformation trends at characteristic points of the Shenzhen-Zhongshan Cross-Sea Bridge, indicating the occurrence of elastic deformation during its construction.

Sentinel-1 InSAR-derived land subsidence assessment along the Texas Gulf Coast

Mapping large-scale coastal subsidence is significant in providing valuable support to decision-making stakeholders to recognize impacts of potential natural disasters. However, this task presents significant challenges due to its highly complex nature of the spatial–temporal variability. Recent advances in the observation capability of synthetic aperture radar (SAR) missions and the processing algorithms of interferometric SAR (InSAR) techniques have made it possible to efficiently map large-scale subsidence from space. This study utilized the persistent scatterer (PS) InSAR method to process four swathes of Sentinel-1 SAR images captured between 2016 and 2022 to map large-scale subsidence along the Texas coastline. The subsidence map, encompassing over 1.7 million PS points, was calibrated/validated with observations of 115 continuously operating global navigation satellite system (cGNSS) stations. Nineteen subsiding hotspots were identified and potential subsidence drivers were analyzed, including hydrocarbon extraction (HE), groundwater withdrawal (GW), and salt domes. The results suggest that HE activities were the primary driver of observed subsidence in the Coastal Bend and South Texas, as well as in the Southeast Texas regions. In the Houston-Galveston Area, subsidence appears to be influenced by a combination of GW, HE, and salt dome movements. Within 50 km of the Texas shorelines, subsidence rates were approximately −1.0 mm/yr within the coastal vicinity, while inland areas experience a gradually increasing trend. Specific coastal areas, such as Corpus Christi, Freeport, Seabrook, San Leon, and others, may face elevated flooding risks during high tide and storm events with the sea-level rise trend up to 24.0 mm/yr in relation to coastal subsiding land.

PREDICTION OF LONG-TERM SENTINEL-1 INSAR TIME SERIES ANALYSIS

Abstract. This paper presents an initial analysis of predicting time series derived from long-term interferometric Synthetic Aperture Radar (InSAR) data. Time series analysis provides insights into the temporal evolution, variation, and dynamic nature of events. In this study, we focus on the Istanbul region, which is the most populous city in Turkey and spans both Europe and Asia. While the area is prone to seismic risks caused by active tectonic faults, it is also susceptible to other risks due to various phenomena. Therefore, this study investigates landslides triggered by geological structure and human-induced activities, particularly in Tepekent, a landslide-prone area in the town of Buyukcekmece located on the European side. We utilized the StaMPS persistent scatterer InSAR (PSI) method to detect slow movements over time. A total of 157 archive Copernicus Sentinel-1 data, acquired over the region between June 2017 and August 2022, were processed, primarily observing human structures with a maximum displacement amount of approximately 1 cm/year. About 500 persistent scatterer points were identified in the region, and the time series was formed by taking the average of these points. The Long Short-Term Memory (LSTM) neural network method was used to estimate motion. We trained the model with data from the first three years of the time series and used the data from the remaining two years for estimation, while the accuracy analysis was performed with the 5-year time series data. The RMSE values for the training and test data were determined to be 0.725 mm/year and 0.656 mm/year, respectively. Additionally, we estimated the time series for the period from August 2022 to August 2024. The observation and prediction results could be beneficial in developing efficient mitigation risk actions and sustainable urban management strategies.

On the quality checking of persistent scatterer interferometry data by spatial-temporal modelling

Abstract Today, rapid growth in infrastructure development and urbanisation process increases the attention for accurate deformation monitoring on a relatively large-scale. Furthermore, such deformation monitoring is of great importance in the assessment and management of natural hazard processes like landslides, earthquakes, and floods. In this study, the Persistent Scatterer Interferometry (PSI) technique is applied using open-source Synthetic Aperture Radar (SAR) data from the satellite Sentinel-1. It allows point-wise deformation monitoring based on time series analysis of specific points. It also enables performing spatio-temporal area-based deformation monitoring. Currently, these data do not have a sophisticated quality assurance process to judge the significance of deformations. To obtain different quality classes of the Persistent Scatterer (PS) data points, the first step is to classify them into buildings and ground types using LoD2 building models. Next, time series analysis of the PS points is performed to model systematic and random errors. It allows estimation of the offset and the deformation rate for each point. Finally, spatio-temporal modelling of neighbourhood relations of the PS points is carried out using local geometric patches which are approximated with a mathematical model, such as, e.g., multilevel B-Splines. Subsequently, the quality of SAR data from temporal and spatial neighbourhood relations is checked. Having an appropriate spatio-temporal quality model of the PS data, a deformation analysis is performed for areas of interest in the city of Hamburg. In the end, the results of the deformation analysis are compared with the BodenBewegungsdienst Deutschland (Ground Motion Service Germany) provided by the Federal Institute for Geosciences and Natural Resources (BGR), Germany.

MATCHING PERSISTENT SCATTERER CLUSTERS TO BUILDING ELEMENTS IN MESH REPRESENTATION

Abstract. The deformation time series of Persistent Scatterer points show a correlated behavior if they lay on the same rigid structure and therefore undergo the same deformation process. By clustering, such groups of Persistent Scatterer (PS) points can be identified. We use segmented mesh representations of single buildings, to find the optimal assignment of such clusters to parts of the structure. By applying a quality metric, the assignment is judged quantitatively. The proposed method is useful for the integration of PSInSAR into building information modeling (BIM) and aims at a cost-effective city-wide per-building monitoring.

Characterizing Micro-Displacements on Active Faults in the Gobi Desert with Time-Series InSAR

This research investigates small-scale tectonic activity in the Jiujing region in Beishan, northwest China through the application of persistent scatterer (PS) Interferometric synthetic aperture radar (InSAR). PS InSAR is an effective monitoring tool in this unpopulated, arid, and unvegetated rural area, whose surface geology is dominated by a single large granitic intrusion, and which represents a candidate site for a geological disposal facility (GDF) for high-level radioactive waste (HLW) in China. This research demonstrates that faults F16-2, F17, F18, and F20-2 are still active, producing dip-slip motions along the fault planes. The lithological variations in weathering and erosion can be discounted as the cause for these small-scale displacement variations. The work has also identified 11 previously unknown faults, characterising them from vertical (DU) and eastward horizontal (DE) displacements along and across the faults. These newly discovered structures demonstrate how PS InSAR can be used to monitor and measure micro-scale movements on regional-scale faults, which, in many cases, were previously considered to be inactive. Thus, this also improves our understanding of local stress regimes in this area. The Jiujing region is part of a convergent fault zone dominated by NE-SW compression, leading to NE-SW crustal shortening and NW-SE elongation. Through determination of the sense of ground movement measured at irregularly distributed PS points, some faults are reverse and trending NW-SE, while others are normal and trending NE-SW, highlighting how InSAR can be used to resolve fault type and relative movements to monitor tectonic fault blocks at a regional scale.

A Most-Unfavorable-Condition Method for Bridge-Damage Detection and Analysis Using PSP-InSAR

The main contribution of this study is to provide a new idea to detect bridge damage by using PSP-InSAR technology. A most-unfavorable-condition method is proposed for bridge-damage detection and analysis. The method can determine the specific damaged location and occurrence time by using the differential deformation values of persistent scatterer (PS) points on bridge piers. Taking Beijing Suzhou Bridge as an experimental area, 96 COSMO-SkyMed time-series SAR images were used from September 2011 to November 2017. Deformation values of PS points around Suzhou Bridge were acquired and analyzed. Experimental results show that in July 2017, the unusual maximum differential deformation value was 25.73 mm. It occurred between piers D3 and D4 of Suzhou Bridge, and it was deduced that the main girder between piers D3 and D4 may have been damaged in July 2017. As a validation, taking the differential deformation value between piers D3 and D4 as an input, the maximum tensile stress, and the maximum compressive stress were calculated as 2.1 MPa and 8.4 MPa, respectively, through a finite element model. The tensile stress exceeded the design value of the concrete, further confirming the damage of the girder between piers D3 and D4. Moreover, all results are consistent with the Suzhou Bridge damage information shown in existing records, which verify the accuracy and reliability of the proposed method.

Comparison of density and positioning accuracy of PS extracted from super-resolution PSI with those from traditional PSI

In the application of persistent scatterer interferometry (PSI), deformation information is extracted from persistent scatterer (PS) points. Thus, the density and position of PS points are critical for PSI. To increase the PS density, a time-series In-SAR chain termed as "super-resolution persistent scatterer interferometry" (SR-PSI) is proposed. In this study, we investigate certain important properties of SR-PSI. First, we review the main workflow and dataflow of SR-PSI. It is shown that in the implementation of the Capon algorithm, the diagonal loading (DL) approach should be only used when the condition number of the covariance matrix is sufficiently high to reduce the discontinuities between the joint images. We then discuss the density and positioning accuracy of PS when compared with traditional PSI. The theory and experimental results indicate that SR-PSI can increase the PS density in urban areas. However, it is ineffective for the rural areas, which should be an important consideration for the engineering application of SR-PSI. Furthermore, we validate that the positioning accuracy of PS can be improved by SR-PSI via simulations.

Detecting Rock Glacier Displacement in the Central Himalayas Using Multi-Temporal InSAR

Rock glaciers represent typical periglacial landscapes and are distributed widely in alpine mountain environments. Rock glacier activity represents a critical indicator of water reserves state, permafrost distribution, and landslide disaster susceptibility. The dynamics of rock glacier activity in alpine periglacial environments are poorly quantified, especially in the central Himalayas. Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has been shown to be a useful technique for rock glacier deformation detection. In this study, we developed a multi-baseline persistent scatterer (PS) and distributed scatterer (DS) combined MT-InSAR method to monitor the activity of rock glaciers in the central Himalayas. In periglacial landforms, the application of the PS interferometry (PSI) method is restricted by insufficient PS due to large temporal baseline intervals and temporal decorrelation, which hinder comprehensive measurements of rock glaciers. Thus, we first evaluated the rock glacier interferometric coherence of all possible interferometric combinations and determined a multi-baseline network based on rock glacier coherence; then, we constructed a Delaunay triangulation network (DTN) by exploiting both PS and DS points. To improve the robustness of deformation parameters estimation in the DTN, we combined the Nelder–Mead algorithm with the M-estimator method to estimate the deformation rate variation at the arcs of the DTN and introduced a ridge-estimator-based weighted least square (WLR) method for the inversion of the deformation rate from the deformation rate variation. We applied our method to Sentinel-1A ascending and descending geometry data (May 2018 to January 2019) and obtained measurements of rock glacier deformation for 4327 rock glaciers over the central Himalayas, at least more than 15% detecting with single geometry data. The line-of-sight (LOS) deformation of rock glaciers in the central Himalayas ranged from −150 mm to 150 mm. We classified the active deformation area (ADA) of all individual rock glaciers with the threshold determined by the standard deviation of the deformation map. The results show that 49% of the detected rock glaciers (monitoring rate greater than 30%) are highly active, with an ADA ratio greater than 10%. After projecting the LOS deformation to the steep slope direction and classifying the rock glacier activity following the IPA Action Group guideline, 12% of the identified rock glaciers were classified as active and 86% were classified as transitional. This research is the first multi-baseline, PS, and DS network-based MT-InSAR method applied to detecting large-scale rock glaciers activity.

Land Subsidence Susceptibility Mapping in Jakarta Using Functional and Meta-Ensemble Machine Learning Algorithm Based on Time-Series InSAR Data

Areas at risk of land subsidence in Jakarta can be identified using a land subsidence susceptibility map. This study evaluates the quality of a susceptibility map made using functional (logistic regression and multilayer perceptron) and meta-ensemble (AdaBoost and LogitBoost) machine learning algorithms based on a land subsidence inventory map generated using the Sentinel-1 synthetic aperture radar (SAR) dataset from 2017 to 2020. The land subsidence locations were assessed using the time-series interferometry synthetic aperture radar (InSAR) method based on the Stanford Method for Persistent Scatterers (StaMPS) algorithm. The mean vertical deformation maps from ascending and descending tracks were compared and showed a good correlation between displacement patterns. Persistent scatterer points with mean vertical deformation value were randomly divided into two datasets: 50% for training the susceptibility model and 50% for validating the model in terms of accuracy and reliability. Additionally, 14 land subsidence conditioning factors correlated with subsidence occurrence were used to generate land subsidence susceptibility maps from the four algorithms. The receiver operating characteristic (ROC) curve analysis showed that the AdaBoost algorithm has higher subsidence susceptibility prediction accuracy (81.1%) than the multilayer perceptron (80%), logistic regression (79.4%), and LogitBoost (79.1%) algorithms. The land subsidence susceptibility map can be used to mitigate disasters caused by land subsidence in Jakarta, and our method can be applied to other study areas.

A tentative test for measuring the sub-millimeter settlement and uplift of a high-speed railway bridge using COSMO-SkyMed images

This paper analyzed the dynamic behaviors of a high-speed railway (HSR) bridge and evaluated the possibility of measuring the sub-millimeter settlement and uplift using COSMO-SkyMed images. The capability of synthetic aperture radar interferometry (InSAR) technologies with the purpose of sub-millimeter deformation monitoring without ground control points has rarely been studied. In this paper, we conducted a tentative test for measuring the sub-millimeter settlement and uplift of a HSR bridge. Persistent scatterer (PS) and distributed scatterer (DS) were jointly detected to increase the point density. The temperature model was introduced to separate the thermal expansion and linear deformation. By analyzing the HSR structure and time-series deformation, we infer that PS points correspond to double-bounce scatterers mainly generated by the interactions between the girder and track slab and between the girder and fender, and DS points correspond to single-bounce scatterers generated by the bridge girder surface. The accuracy of linear deformation velocity and time-series deformation were evaluated, respectively. Under the assumptions by qualitative analysis, the results demonstrate that COSMO-SkyMed is capable of achieving sub-millimeter accuracy in linear deformation velocity. However, the leveling validation implies that it is difficult to achieve sub-millimeter accuracy in time-series deformation because of the uncertainties from incorrect ground data, location and time difference between the InSAR and ground data, the presence of lateral deformation, improper removal of the atmospheric phase screen, and inconsistency between the air temperature and bridge temperature.

Detecting and monitoring of landslides using persistent scattering synthetic aperture radar interferometry

Persistent scatterer synthetic aperture radar interferometry (PSInSAR) is an applied time series technique to overcome limitations of InSAR (temporal and geometrical decorrelation and atmospheric delay anomalies) for monitoring of ground surface deformations. This method only monitors displacements on pixels with nearly constant temporal backscattering characteristics. In this study, datasets of ascending ALOS PALSAR (L-band) images recorded from 2006 to 2010 and descending ENVISAT ASAR (C-band) images acquisitioned between 2003 and 2010 were processed to detect and monitor the landslide occurred in the Noghol area, Iran. Application of the PSInSAR technique on both PALSAR and ASAR images has significantly improved monitoring of the Noghol landslide. However, the determination of vertical displacement of the landslide by the ASAR images processing is more correct compared to results of the PALSAR processing due to the descending orbital motion of ASAR. The ASAR images also overwhelm PALSAR images for determination of the landslide extent because of detection of more persistent scatterer points. The landslide displacement and aspect obtained by the Global Navigation Satellite System (GNSS) and PSInSAR techniques are in agreement (about 1.2–1.5 m westward in the period of 2003–2010). Particularly, processing results of the ASAR images are more similar to the GNSS measurements. Furthermore, assessment of the landslide type, mechanism and its displacement direction were possible by integration of the PALSAR and ASAR radar images with ascending and descending orbital motions, respectively.

Monitoring of recent ground surface subsidence in the Cangzhou region by the use of the InSAR time-series technique with multi-orbit Sentinel-1 TOPS imagery

ABSTRACTBy collecting 39 scenes of descending images and 26 scenes of ascending images of Sentinel-1 synthetic aperture radar (SAR), we monitored the ground subsidence situation of Cangzhou in China during the period from March 2015 to February 2017 with the advanced synthetic aperture radar interferometry (InSAR) time-series technique and obtained the time-series subsidence rates of Cangzhou. We then selected the two sets of results of the monitoring obtained during the same period (from July 2015 to December 2016) to verify the results’ accuracy, considering three overlapping areas (Xinhua District, Botou County, and Dongguang County). This analysis clearly indicated that both types of results have good consistency, and the maximum subsidence occurred in Dongguang County. By further study of the central area of Dongguang and the related urban development, we found that the subsidence reached about 80.0 mm over the study period and there was a close relationship between the subsidence trend and the main direction of the city development. Moreover, by combining the two sets of results, we confirmed that there has been subsidence of the high-speed railway line in the whole of the Cangzhou area, among which the most obvious subsidence has occurred in Dongguang and Qing Counties. Finally, it was proved that the Sentinel-1 data can be used to monitor ground surface subsidence, and the data are especially effective in identifying persistent scatterer points along a linear feature. Therefore, this article could provide reliable data to assist with important decisions about urban development projects in the Cangzhou area in the next few years.

A RESEARCH ON MONITORING SURFACE DEFORMATION AND RELATIONSHIPS WITH SURFACE PARAMETERS IN QINGHAI TIBETAN PLATEAU PERMAFROST

Abstract. The Qinghai Tibetan Plateau permafrost has been the largest permafrost region in middle-low latitude in the world for its high altitude. For the large area permafrost, especially surface deformation brought by it, have serious influence on the road engineering, road maintaining and regional economic development. Consequently, it is essential to monitor the surface deformation and study factors that influent it. We monitored an area named Wudaoliang from July 25, 2015 to June 1, 2016 and 15 Sentinel images were obtained during this time. The area we chose is about 35 kilometers long and 2 kilometers wide, and the national road 109 of China passes through the area. The traditional PS-INSAR (Persistent Scatterer Interferometric Synthetic Aperture Radar) method is not suitable because less historical images in the research area and leading to the number of PS (Persistent Scatterer) points is not enough to obtain accurate deformation results. Therefore, in this paper, we used another method which named QUASI-PSInSAR (QUASI Persistent Scatterer Interferometric Synthetic Aperture Radar) to acquire deformation for it has the advantage to weaken or eliminate the effects of spatial and temporal correlation, which has proved by other scholar. After processing 15 images in the SARproz software, we got the conclusions that, 1) the biggest deformation velocity in the whole area was about 127.9mm/year and about 109.3 mm/year in the road; 2) apparent deformation which have surface deformation more than 30mm/year was about 1.7Km in the road. Meanwhile, soil moisture(SM), Land surface temperature (LST) and surface water(SW), which are primary parameters of the land surface over the same time were reversed by using Sentinel data, Landsat data and ZY-3 data, respectively. After analyzing SM, LST , SW and deformation, we obtained that wet areas which had bigger SM, lower LST and more SW, had greater percentage of severe deformation than arid areas; besides, deformation pattern were different in arid areas and wet areas. During the research time, frost heaving firstly accounted for a large proportion both in the arid and wet areas with the decrease of downward radiation from July to December; after December, thaw settlement came into prominence with the increase downward radiation in the arid areas, while in the wet areas, surface put into diverse situations because of water transformation leading to severe deformation. In summary, soil moisture is an important factor that influences the surface deformation. This relationship between deformation process and soil moisture will be researched more in our further work.

CHANGE DETECTION BASED ON PERSISTENT SCATTERER INTERFEROMETRY – A NEW METHOD OF MONITORING BUILDING CHANGES

Abstract. Persistent Scatterer Interferometry (PSI) is a technique to detect a network of extracted persistent scatterer (PS) points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC) points. On the other hand, incoherent change detection (ICD) relies on local comparison of multi-temporal images (e.g. image difference, image ratio) to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.

CHANGE DETECTION BASED ON PERSISTENT SCATTERER INTERFEROMETRY – A NEW METHOD OF MONITORING BUILDING CHANGES

Persistent Scatterer Interferometry (PSI) is a technique to detect a network of extracted persistent scatterer (PS) points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC) points. On the other hand, incoherent change detection (ICD) relies on local comparison of multi-temporal images (e.g. image difference, image ratio) to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.

Estimation of small surface displacements in the Upper Rhine Graben area from a combined analysis of PS-InSAR, levelling and GNSS data

The intra-plate deformation of the Upper Rhine Graben (URG) located in Central Europe is investigated using geodetic measurement techniques. We present a new approach to calculate a combined velocity field from InSAR, levelling and GNSS measurements. As the expected tectonic movements in the URG area are small (less than 1mma−1), the best possible solutions for linear velocity rates from single-technique analyses are estimated in a first step. Second, we combine the velocity rates obtained from InSAR (line of sight velocity rates in ascending and descending image geometries), levelling (vertical velocity rates) and GNSS (horizontal velocity rates) using least-squares adjustment (LSA). Focusing on the Northern URG area, we analyse SAR data on four different image stacks (ERS ascending, ERS descending, Envisat ascending, Envisat descending) using the Persistent Scatterer (PS) approach. The linear velocity rates in ascending and descending image geometries, respectively, are estimated in an LSA from joint time-series analysis of ERS and Envisat data. Vertical velocity rates from levelling are obtained from a consistent adjustment of more than 40 000 measured height differences using a kinematic displacement model. Horizontal velocity rates in east and north direction are calculated from a time-series analysis of daily coordinate estimates at 76 permanently operating GNSS sites in the URG region. As the locations, at which the measurement data of PS-InSAR, levelling and GNSS reside, do not coincide, spatial interpolation is needed during several steps of the rigorous processing. We use Ordinary Kriging to interpolate from a given set of data points to the locations of interest with a special focus on the modeling and propagation of errors. The final 3-D velocity field is calculated at a 200 m grid, which carries values only close to the location of PS points, resulting in a mean horizontal and vertical precision of 0.30 and 0.13 mm a−1, respectively. The vertical component of the combined velocity field shows a significant subsidence of about 0.5 mm a−1 in the northern part of the graben coinciding with a well-known quaternary basin structure. Horizontal displacement rates of up to 0.8 mm a−1 in southeast direction are observed outside the graben, in reasonable alignment with the average direction of maximum horizontal stress. Within the graben, the velocity directions rotate toward east in the non-subsiding part, while an opposite trend is observed in the subsiding part of the graben. The complexities of the observed velocity field are compatible to the geomechanical situation in our investigation area which is characterized by a transition from a restraining to a releasing bend setting. Glacial isostatic adjustment is another potential source influencing the observed velocity field, as well as anthropogenic signals due to mining, oil exploration and groundwater usage that have been identified in some places.

New results on ground deformation in the Upper Silesian Coal Basin (southern Poland) obtained during the DORIS Project (EU-FP 7)

This paper presents application of satellite interferometric methods (persistent scatterer interferometric synthetic aperture radar (PSInSAR™) and differential interferometric synthetic aperture radar (DInSAR)) for observation of ground deformation in the Upper Silesian Coal Basin (USCB) in Southern Poland. The presented results were obtained during the DORIS project (EC FP 7, Grant Agreement n. 242212, www.doris-project.eu). Several InSAR datasets for this area were analysed. Most of them were processed by Tele-Rilevamento Europa - T.R.E. s.r.l. Italy. Datasets came from different SAR satellites (ERS 1 and 2, Envisat, ALOS- PALSAR and TerraSAR-X) and cover three different SAR bands (L, C and X). They were processed using both InSAR techniques: DInSAR, where deformations are presented as interferometric fringes on the raster image, and PSInSAR, where motion is indentified on irregular set of persistent scatterer (PS) points. Archival data from the C-band European Space Agency satellites ERS and ENVISAT provided information about ground movement since 1992 until 2010 in two separate datasets (1992–2000 and 2003–2010). Two coal mines were selected as examples of ground motion within inactive mining areas: Sosnowiec and Saturn, where mining ceased in 1995 and 1997, respectively. Despite well pumping after closure of the mines, groundwater rose several dozen meters, returning to its natural horizon. Small surface uplift clearly indicated on satellite interferometric data is related to high permeability of the hydrogeological subregion and insufficient water withdrawal from abandoned mines. The older 1992–2000 PSInSAR dataset indicates values of ground motion ranging from –40.0 to 0.0 mm. The newer 2003–2010 dataset shows values ranging from –2.0 to +7.0 mm. This means that during this period of time subsidence was less and uplift greater in comparison to the older dataset. This is even more evident in the time series of randomly selected PS points from both coal mines. The presence of bentonite deposits in the Saturn coal mine can also have influence on the ground surface uplift. Analysis of interferometric L and X-band data in Upper Silesia has enabled observation and monitoring of the underground mining front for several months. It was indicated by the example from the Halemba–Wirek coal mine. Analysis of the TerraSAR–X dataset processed by SqueeSAR algorithms proved to be the most effective for this purpose. X-band persistent scatterer interferometry (PSI) time series can help to indentify small seemingly negligible movements and are successfully supplemented by fringes when displacement becomes significant. Differential interferograms from the L-band dataset detect similar displacement values but, thanks to longer wavelength, are characterized by better coherence, especially in the middle of the subsidence trough. Results on ground deformation proved that ground motion above abandoned mines continues long after their closure. Therefore, existing regulations stating that abandoned mines are considered fully safe five years after mine closure should change. Moreover, it should be emphasised that construction in these areas should be avoided due to existing potential risks.

Monitoring of Surface Deformation in Northern Taiwan Using DInSAR and PSInSAR Techniques

We investigated the surface deformation of the northern Taiwan area, including the Taipei basin and its surrounding mountainous areas of the last fifteen years using the ERS-1, ERS-2 and ENVISAT SAR images. Although the Taipei basin now is well developed and amenable to research gathering using the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique, the mountainous areas surrounding the basin are densely covered with various vegetation throughout different seasons inducing high noise ratio in interferograms. Therefore the DInSAR technique is ineffective for observation of surface deformations of these areas. As a result, we developed the Persistent Scatterer (PS) InSAR technique to extract the phase signal of the chosen PS points for this study. Our analysis result shows that the atmospheric disturbance and DEM residual can be successfully reduced and the precise information of surface deformation can be effectively obtained by the PSInSAR technique not only in the basin but also in the mountainous areas. Integrating the DInSAR and PSInSAR results, we observed conspicuous deformation events in northern Taiwan including: (1) the slight uplift in the Western Foothills, the Tatun volcanoes, the Linkou Tableland and the Taoyuan area; (2) the subsidence at the border of the Taipei basin; and (3) relative slight uplift rebound in the center of Taipei basin. The displacements along the Shanchiao, Chinshan, and Kanchiao Faults are large enough to be observed; the Taipei, Hsinchuang, and Nankang Faults are too small and cannot be discerned. Further comparison between the DInSAR, PSInSAR, and their corresponding leveling data shows a very coincidental pattern and measurably improves the authenticity of radar interferometry.