Characterization and causes of land subsidence in Beijing,China

Long-term overexploitation of groundwater is the primary factor causing regional land subsidence in the Beijing plain area, China. Currently, large subsidence funnels exist, one each in southern and northern Beijing. We adopted the multi-temporal interferometric synthetic aperture radar (MT-InSAR) method, incorporating both persistent scatterer (PS) and small baseline (SB) approaches on 47 Envisat Advanced Synthetic Aperture Radar (ASAR) single look complex (SLC) images to map land subsidence in the Beijing plain area. The temporal and spatial variations of land subsidence and its seasonal variation were explained by the MT-InSAR results. Then, the InSAR results were combined with the dynamic monitoring of groundwater level, extensometer measurements, and hydrogeological data; the characterization and causes of land subsidence were analysed with Geographic Information System (GIS) spatial analysis methods. The results show the following. 1) Land subsidence developed rapidly in the Beijing plain area from 2003 to 2010, with obviously uneven settlement; settlement rates exceeded 100 mm year^?1 in some areas. Seasonal variation in settlement rates may be affected by changes in the precipitation rates and the exploitation of groundwater. 2) The contribution of different aquifer systems to land subsidence varies. The variation in the groundwater level in the second confined aquifer, at a depth of 100–180 m, has the greatest impact on land subsidence. 3) The settlement is centred in the lower part of the Wenyu–Chaobai and Yongding alluvial fan areas, where the compressible layer is more than 100 m thick. Meanwhile, land subsidence forms a structural feature with larger differences in the deformation gradient on both sides of faults.     

Annual rates of ground deformation (1993–2010) at Campi Flegrei,Italy, revealed by Persistent Scatterer Pair (PSP) – SAR interferometry

Campi Flegrei is an active volcanic district located along the Eastern Tyrrhenian continental margin, Italy, and is worldwide known for dramatic ground deformation phenomena (bradyseism) recorded over the last centuries. The purpose of this article is to present the annual rates of ground deformation fields (average velocity, average acceleration, and combined annual velocity/acceleration) at Campi Flegrei, during almost two decades (years 1993–2010). The research work was conducted based on a temporal analysis and advanced mapping of Persistent Scatterer Pair (PSP) data, obtained from interferometric processing of radar satellite European Remote Sensing-1/2 and Environmental Satellite (ENVISAT) scenes of the study area. Patterns and trends of annual PSP velocity have provided a reconstruction of the spatial and temporal variability of ground deformation in terms of uplift and/or subsidence along the satellite line of sight (LOS). The analysis of annual PSP velocity and acceleration has revealed an intense dynamics of the Campi Flegrei caldera collapse-resurgence system, testified by the high PSP velocity and acceleration values, as well as the significant changes in the rates of ground deformation through time. The main results of this research indicate that the largest ground deformation is localized within and around the structural border of the Campi Flegrei caldera and suggest a systematic recurrence of opposite trends (uplift vs. subsidence) in the ground deformation of the inner caldera region with respect to the surrounding areas throughout the analysed time period.     

Persistent Scatterers Interferometry detects and measures ground subsidence in Lisbon

Results from the application of Persistent Scatterers Interferometry in Lisbon Metropolitan Area revealed two previously unknown subsiding urban areas: one (Laranjeiras) is located in the center of Lisbon; another (Vialonga) is to be found toward the North, in an industrial region crossed by Lisbon's main highway and railway lines. The two subsiding sectors are bordered by sharp velocity gradients, and the subsidence pattern appears partially delimited by mapped geologic faults. Surface geology and urbanization alone are unable to explain the phenomena. In the Vialonga area, the historical record of water pore pressure shows a clear decline of the levels (up to 65 m in 27 years), providing evidence of over-exploitation of groundwater resources. Limited information from wells drilled inside and outside the subsidence area points to a spatial correlation between the subsidence and the water pressure levels, and suggests that faults could be acting as hydraulic barriers in the aquifer system. The surface subsidence detected is probably caused by compaction of a clay-rich Oligocene-aged aquitard, led by over-exploitation of adjacent aquifers. The same Oligocene aquitard layer is present in the Laranjeiras area, immediately bellow a multi-layered sand-clay-limestone Miocene aquifer, but further work is needed to diagnose the possibility of over-exploitation of groundwater here. In this work we were able to independently confirm the PSI results, by comparing autonomous PSI results processed for the same geographical areas, and by comparing PSI with leveling and continuous GPS derived subsidence velocities, whose close match provided further ground validation of the space-borne PSI technique.     

Episodic ground deformation signals in Thessaly Plain (Greece) revealed by data mining of SAR interferometry time series

The Eastern Thessaly Plain presents an area of severe settlement phenomena, owing to the over-exploitation of the underground aquifer systems, causing significant damages to national infrastructures and private properties annually. Herein, both Persistent Scatterers (PS) and Small Baselines (SB) interferometric techniques were applied to study the history of ground deformation along the entire plain. Although the area consisted mostly of agricultural land, a sufficient number of point targets was obtained, well-distributed over the entire plain, permitting the recognition of spatial variations of the displacement field in addition to temporal trends. Our findings outline the southern part of the basin as the mostly affected area, whereas local subsidence patterns of lower magnitude were also recognized elsewhere. Episodes of significant ground subsidence, reaching several centimetres within a few months, characterize the deformation pattern of the area. Although average ground deformation rates do not exceed 2 cm year^?1, line-of-sight (LOS) displacements of up to 13 cm were observed, occurring during the summer–autumn periods. A geographic information system (GIS)-based post-processing approach for the analysis of synthetic aperture radar (SAR) time series is presented, by which these abrupt settlement episodes can be identified in both temporal and spatial domains. The analysis allows the separation between rapid subsidence phenomena during the summer–fall season and annual deformation rates, thereby providing valuable information regarding the actual deformation pattern of the area. The results confirm in situ geological observations, highlighting the unique behaviour of the area due to intense water pumping. The study underlines that average SAR displacement rate maps might be inadequate to describe complex deformation scenarios and could lead to misinterpretations. Exploitation of the full capacity of SAR time series by detailed examination of the displacement histories, through a tailored data-mining strategy, could provide valuable information to geotechnical engineers and planners.     

A methodology for improving landslide PSI data analysis

In this work, we present a methodology for improving persistent scatterer interferometry (PSI) data analysis for landslide studies. This methodology is a revision of previously described procedures with several improved and newly proposed aspects. To both evaluate and validate the results from this methodology, we used various persistent scatterer (PS) datasets from different satellites (ERS – ENVISAT, Radarsat, TerraSAR-X, and ALOS PALSAR) that were processed using three PSI techniques (stable point network – SPN, permanent scatterer interferometry – PSInSAR?, and SqueeSAR?) to map and monitor landslides in various mountainous environments in Spain and Italy. This methodology consists of a preprocessing model that predicts the presence of a PS over a certain area and a post-processing method used to determine the stability threshold, project the line of sight (LOS) velocity along the slope, estimate the E–W and vertical components of the velocity, and identify anomalous areas.     

Persistent Scatterers Interferometry Hotspot and Cluster Analysis (PSI-HCA) for detection of extremely slow-moving landslides

The synthetic aperture radar (SAR) interferometry (InSAR) technique has already shown its importance in landslide mapping and monitoring applications. However, the usefulness of traditional differential InSAR applications is limited by disturbing factors such as temporal decorrelation and atmospheric disturbances. The Persistent Scatterers Interferometry (PSI) technique is a recently developed InSAR approach. It generates stable radar benchmarks (namely persistent scatterers, PSI point targets) using a multi-interferogram analysis of SAR images. The PSI technique has the advantage of reducing temporal decorrelation and atmospheric artefacts. The PSI technique is suitable for the investigation of extremely slow-moving landslides due to its capability to detect ground displacements with millimetre precision. However, the interpretation of PSI outputs is sometimes difficult for the large number of possible persistent scatterers (PSs). A new approach of PSI Hotspot and Cluster Analysis (PSI-HCA) is introduced here in order to develop a procedure for mapping landslides efficiently and automatically. This analysis has been performed on PSs in hilly and mountainous areas within the Arno river basin (Italy). The aim is to use PSs processed from 4 years (2003–2006) of Radarsat images for identifying areas preferentially affected by extremely slow-moving landslides. The Getis–Ord G_i *?statistic is applied in the study for the PSI-HCA approach. The velocity of PSs is used as weighting factor and the G_i *?index is calculated for each single point target. The results indicate that both high positive and low negative G_i *?values imply the clustering of potential mass movements. High positive values suggest the moving direction towards the sensor along the satellite line-of-sight (LOS), whereas low negative values imply the movement away from the sensor. Furthermore, the kernel function is used to estimate PS density based on these derived G_i *?values. The output is a hotspot map which highlights active mass movements. This spatial statistic approach of PSI-HCA is considered an effective way to extract useful information from PSs at a regional scale, thus providing an innovative approach for rapid mapping of extremely slow-moving landslides over large areas.     

Estimation of land subsidence in deltaic areas through differential SAR interferometry: the Po River Delta case study (Northeast Italy)

ABSTRACT

River deltas are very complex environments vulnerable to flooding. Most of the world’s deltas are facing the immediate threat of land subsidence that jeopardizes the safety of millions of people worldwide. In Italy, the Po River Delta (PRD) (Northeast Italy) is an area historically affected by high rate of subsidence due to natural and anthropic factors. Even if the subsidence rates remarkably reduced during the last three decades, this process continues to be alarming in particular in low-lying sectors and along the coastline, where the loss of elevation, combined with the sea-level rise, increases the risk related to flooding. In this study, we monitored the subsidence affecting the entire PRD area with advanced differential interferometric synthetic aperture radar (A-DInSAR) techniques applied to three C-band SAR data sets acquired by the European Remote Sensing satellites, Environmental Satellite, and Sentinel-1A satellite in the last 25 years (from 1992 to 2017). The results of the interferometric processing, consisting of both mean velocity and displacement time series along the satellite line of sight, validated by comparison with levelling and global positioning system measurements, show increasing subsidence moving from the inland to the coastline, with maximum deformation velocities, for the most recent data, in the order of ?30 mm year^?1. In particular, many embankments near the coastal area are affected by high values of subsidence, which increase the flooding hazard of the entire deltaic territory. This work shows the importance of adopting A-DInSAR techniques to update the knowledge of the extent and rates of deformation of subsiding areas in low-lying territories such as river deltas. The outputs of such monitoring can be of primary importance for the future protection of the territory and the flooding risk mitigation.     

Surface deformation from persistent scatterers SAR interferometry and fusion with leveling data: A case study over the Choushui River Alluvial Fan, Taiwan

The Choushui River Alluvial Fan (CRAF), one of the most important agricultural areas in Taiwan, suffers severe subsidence caused by groundwater withdrawal. We use 20 ENVISAT images from 2006 to 2008 to derive vertical deformation over CRAF by persistent scatterer interferometry (PSI), which effectively reduces errors affecting conventional DInSAR techniques. The pixel density over CRAF is 107.6 pixels/km², compared to 0.19 points/km² of the leveling benchmarks. PSI yields vertical displacements matching the leveling result to 0.6 cm/year (RMS), and provides a higher spatial resolution of subsidence than the latter. We also develop a data fusion method that considers the high-precision, low point-density leveling result as a smoothed correction to the PSI result. The combined field is more representative of overall deformation characteristics than the PSI-only or leveling-only field, and it is better suited for the assessment of the impact of subsidence over CRAF.     

Evolution of urban monitoring with radar interferometry in Madrid City: performance of ERS-1/ERS-2, ENVISAT,COSMO-SkyMed,and Sentinel-1 products

During the last decades, synthetic aperture radar (SAR) image exploitation has matured with the launch of different satellite missions and the development of different techniques, which allow exploiting the capabilities of the radar images. Among these techniques, persistent scatterer interferometry (PSI) has proven to be a powerful tool to derive terrain deformations over urban areas. It is based on the use of a large number of images over wide areas in order to obtain terrain displacements time series. The imagery from the different SAR missions has led to an archive with data that covers up to 30 years in the past. Moreover, different methods and algorithms have been proposed in order to perform this complex task. In this line, this work aims at identifying if data from different missions and processed by different techniques can be combined in order to study the evolution of urban monitoring. Three different PSI techniques are used in order to process data from four SAR missions: European Remote Sensing (ERS)-1/2, Environmental Satellite, COSMO-SkyMed, and the recent Sentinel-1 A/B. The rapidly evolving urban area of Madrid, where numerous undergrounding works have been carried out in the last decade, has been chosen as the testing environment. The density of persistent scatterers, the deformation accuracy validated with GPS displacements and deformation trends are used as the key performance items for the assessment.     

PSI-HSR: a new approach for representing Persistent Scatterer Interferometry (PSI) point targets using the hue and saturation scale

Persistent Scatterer Interferometry (PSI) is a recently developed radar processing technique that enables the measurement of ground motion with millimetre accuracy. This technique makes use of an analysis of multi-temporal Synthetic Aperture Radar (SAR) images to detect stable PSI point targets, so-called persistent scatterers (PSs). These PSs are usually integrated in a geographic information system (GIS) as a standard point-based map, using colour coding on their velocities, with separation of ascending and descending data. In this paper we introduce the PSI-HSR (PSI Hue–Saturation Representation), a new method for representing PSI point targets using the hue–saturation scale. The aim was to render a unique colour for each PSI point target, based on a combination of displacements assessed along two different lines of sight. PSI-HSR provides a straightforward way to describe ground movement. To demonstrate the usefulness of this approach, an example of detecting ground subsidence in the Pistoia-Prato-Firenze basin is presented.     

The present status of subsiding land vulnerable to roof collapse in the Jharia Coalfield,India, as obtained from shorter temporal baseline C-band DInSAR by smaller spatial subset unwrapped phase profiling

In this paper, we identified recently subsiding areas in Jharia Coalfield, Jharkhand, India from the shorter temporal baseline Radarsat-2 C-band interferometric synthetic aperture radar (InSAR) data pairs of 2012. Although shorter wavelength C-band differential InSAR (DInSAR) is more sensitive to slow deformation and better suited for higher precision land subsidence measurement, the dynamic and adverse land cover in mining areas and resulting temporal decorrelation problem poses a serious problem for DInSAR observation in mining areas. We used smaller temporal baseline data pairs and adopted InSAR coherence-guided incremental filtering with smaller moving windows to highlight the deformation fringes over temporal decorrelation noise. We identified the deformation fringes and validated them based on ground information to prepare the land subsidence map of the coalfield in 2012. Several new, previously unreported subsidence areas were detected in the present study with a total subsiding area of 6.9 km². The recent incidence of roof collapse on 15 November 2014 at Angar Patra village in Katras region of the coalfield where 45 houses collapsed and 10 people were injured is situated in a highly subsiding vulnerable area as obtained from the present study. Due to spatial discontinuities of InSAR coherence, DInSAR phase unwrapping for the entire study area in one go did not appear feasible. To avoid this problem, we performed DInSAR processing in smaller spatial subsets and unwrapping of the subset interferograms by a ‘minimum cost flow’ algorithm. Subsequently, we plotted unwrapped phase profiles across the deformation fringes and retrieved the maximum deformation phase with respect to background phase and translated them into radar line of sight (LOS) displacement rates. For obtaining the average subsidence rates, we adopted InSAR coherence-weighted LOS displacement rates taking into account the contribution of each data pair as a function of DInSAR phase quality of the fringe areas. Ground-based subsidence measurements by precision levelling were conducted in four test sites that had been undergoing active underground mining during the observation period. We compared space-borne DInSAR-based subsidence rates obtained by the adopted technique with precision levelling measurements. Overall, the results are found to agree well. In the four test sites with gentle to flat topography, land subsidence occurs at slow to moderate rates due to compression of in-filled material (resulting from sand stowing in underground mining), without any evidence of roof collapse. In such cases, the horizontal displacement component is less significant, and overall surface displacement occurs essentially in the vertical direction. However, we assessed the nature of subtle horizontal strain to infer relative shrinkage or dilation of the land surface which could be additive or subtractive to vertical displacement in DInSAR-based LOS displacement.     

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

ABSTRACT

By 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.     

Analysis of ground subsidence at a coal-mining area in Huainan using time-series InSAR

In Huainan City, Anhui Province, China, ground subsidence persistently occurs due to underground coal mining, which has caused several environmental issues. A modified time-series Interfermetric synthetic aperture radar (InSAR) technique is applied to obtain ground movement in Huainan over a period of approximately two years using 20 ascending Radarsat-2 images. In particular, distributed scatterers (DSs) are efficiently identified using classification information and statistical characteristics. Classified information is used to identify the specific DS classes and statistical characteristics are used to refine the DS candidates. To control error propagation and improve computational efficiency, the deformation rate and digital elevation model (DEM) error of persistent scatterers (PSs) are first retrieved using conventional persistent scatterer intermemetry (PSI). Then, a region-growing-based strategy is applied to extract the deformation rate of DSs. Land subsidence is detected in coal-mining areas of central Dingji, Guqiao, Zhangjiaji, Xinji I, and Xinji II, which suggests that the subsidence is primarily caused by underground mining. The fastest subsidence occurring in non-urban areas is particularly vulnerable to subsidence and collapsed lakes. It is also found that the collapsed lakes have expanded during the observation period, with an expanded mining area of 0.842 km² near Guqiao. A linear relationship between the observed subsidence and expansion of collapsed lakes was found, which indicates that the expansion of collapsed lakes hass resulted from subsidence due to underground coal mining.     

Recent subsidence in Tianjin,China: observations from multi-looking TerraSAR-X InSAR from 2009 to 2013

Tianjin, China, has been suggested to have serious ground subsidence due to excessive extraction of groundwater. It is essential to monitor this subsidence, which has potential hazards and risks. Time series InSAR (TS-InSAR), such as small baselines subset (SBAS), is a powerful tool that can monitor ground deformation with high accuracy and at high spatial resolution over a long time interval. However, the high computational complexity may exceed computer memory limit when high-spatial resolution SAR (such as TerraSAR-X, TSX) images are used. In this article, the multi-look approach is introduced to the SBAS tool from StaMPS/MTI (Stanford method for persistent scatter/multi-temporal InSAR) in order to balance the spatial resolution and subsidence information in detection. The looks used for multi-looking are first fixed in terms of the accuracy of deformation and the density of coherent points. Then, the recent subsidence in Tianjin is extracted using multi-looking SBAS based on 48 TSX images acquired from 2009 to 2013. The results are validated by levelling measurements with a root mean square error (RMSE) of 4.7 mm year^–1, which demonstrates that SBAS analysis can effectively monitor deformation based on multi-looking TSX acquisitions in the area under investigation. Besides, the results also show that Tianjin has been suffering from subsidence during this period, and there were two separate large subsidence basins located in this study area with more than 500 mm cumulative subsidence. Moreover, the subsidence rate increased after December 2010 in Tianjin.     

Potential of small-baseline SAR interferometry for monitoring land subsidence related to underground coal fires: Wuda (Northern China) case study

Uncontrolled coal fires can result in massive surface displacements due to the change in volume of burning coal and thermal effects in the adjacent rock mass; simultaneously, the resultant surface breakings provide greater access to air and water that in turn can aggravate the problem of underground coal seam burning. In this case study, we have investigated the feasibility and potential of detecting the land subsidence accompanying coal fires by means of satellite InSAR observations. Three groups of small-baseline InSAR approaches (PSI, stacking and 2-passDInSAR) were applied to the Wuda coalfield (Northern China) to reveal the spatial and temporal signals of the land subsidence in the areas affected by the coal fires. The interferometric results agree well with GPS observations and coal fire data obtained by field investigation, which demonstrates that the small-baseline InSAR techniques have remarkable potential to detect this land subsidence of interest. In particular, our results show that the development of coal fires can lead to new subsiding areas and also accelerate the ongoing surface subsidence, typically within the areas of mature coal fires, through a comparison of the interferometric observations and the multi-temporal coal fire maps. This timely and reliable information on land subsidence will be useful for the detection and mapping of the coal fire affected regions and thereby assist in fighting and controlling coal seam burning.     

Subsidence induced by urbanisation in the city of Rome detected by advanced InSAR technique and geotechnical investigations

We applied the Interferometric Point Target Analysis (IPTA) technique to study the city of Rome (Italy) aiming to detect and measure the surface movements of buildings and urban structures. The available SAR dataset has been delivered by ESA CAT1 3258 and ranges the period 1992-2005. In particular ERS1-ERS2 data processed covers 1995-2000, while Envisat ASAR 2002-2005. The Point Target velocity map shows a general stability except for some very local areas affected by subsidence rate larger than 10 mm/year. The analysis of the time series, compared to a detailed geological and geotechnical investigation of the lithostratigraphy of the alluvial sediments of the Tiber River, and combined with a temporal reconstruction of the expansion of the city over the alluvial valleys, allowed us to depict the main factors controlling the observed subsidence. These are: the in situ effective stress conditions, the related compressibility and viscous characteristics of the loaded soils, the thickness of the compressible stratum, the time since loading instant, and the entity of loading. Furthermore the observed subsidence is time-dependent, even at a long time-scale, with respect to the age of the buildings being most of the buildings constructed since the '50s still affected by slow subsidence. We mainly focused on the Grottaperfetta stream valley that is characterized by an anomalous high and time-lasting subsidence. Original data on the lithostratigraphic setting of this alluvial valley indicate that the high subsidence rate measured up to 2005 is caused by a still active primary consolidation process.     

Landslide detection in La Paz City (Bolivia) based on time series analysis of InSAR data

Geologically, La Paz City is located in an unstable area. During the history of La Paz city, many landslides have destroyed houses and valuable infrastructures. In the last decades, time series Interferometric Synthetic Aperture Radar (InSAR) technologies have demonstrated a great capacity for detecting slow ground displacement, achieving an accuracy of millimetre-level. In order to have a better landslide monitoring of La Paz city, in this study, the Sentinel-1 SAR images have been processed by Persistent Scatterer Interferometry (PSI) and the Small Baseline Subset (SBAS) techniques. The time span of the datasets is from March 2015 to August 2016. Both ascending and descending Synthetic Aperture Radar (SAR) images have been processed to obtain the line of sight (LOS) ground velocity, and then the results have been combined to estimate the up-down and east-west displacement. Several active movement areas have been identified, showing a surface velocity up to 158 mm year^?1 westward and 49 mm year^?1 eastward. Furthermore, two important findings have been discovered. First, the InSAR result has detected movement in Auquisamaa hill before the area collapsed (15 February 2017), where five houses are buried. Second, the InSAR result has identified that there are still some unstable sites in Callapa area, where a mega-landslide has destroyed more than a thousand of houses in February 2011. In conclusion, we have verified that the InSAR technology could be a very useful tool to help La Paz public institutions for a better management of urban planning, landslide areas delimitation and landslide risk mitigation.     

Subsidence analysis of ELH Bridge through ground-based interferometric radar during the crossing of a subway shield tunnel underneath the bridge

Ground-based interferometric radar is a popular technique for the deformation monitoring and analysis of civil engineering constructions. Many researchers have applied this technique to different operative scenarios, but only a few studies have analysed deformation time series derived through ground-based interferometric radar in consideration of the effect of coloured noise. In this study, deformation information was retrieved through the joint application of ground-based interferometric radar and maximum likelihood estimation (MLE) in consideration of the effects of white and coloured noises. A case study was conducted on the subsidence of East Lake High-tech Bridge during subway shield tunnel crossing underneath this bridge (from 16 to 18 November 2016). The subsidence time series was derived through ground-based interferometric radar. Afterward, the subsidence time series was verified by levelling at an accuracy better than 0.33 mm. Furthermore, white and coloured noises were detected in the denoized subsidence time series through a spectral analysis and MLE. For the subsidence time series of Nos. 7 and 8 piers, the coloured noise amplitudes were 0.3824 and 0.6261 mm, respectively, and the white noise values were 0.0414 and 0.0610 mm, respectively. Accurate subsidence rates and accumulative subsidence were derived through MLE by using the estimated noise characteristics in the subsidence time series. The subsidence rates of Nos. 7 and 8 piers were ?0.0122 ± 0.0060 and ?0.0065 ± 0.0058 mm hour^?1, respectively, and the accumulative subsidence values were ?0.6365 and ?0.3370 mm, respectively. This finding suggests that the bridge is stable and safe.     

Integration of TerraSAR-X and PALSAR PSI for detecting ground deformation

In connection with the detection of various spatial- and temporal-scale ground settlements, an integrated persistent scatterer interferometry (PSI) approach is discussed using multi-source, multi-temporal, and multi-resolution synthetic aperture radar (SAR) data. Based on the comprehensive analysis of characteristics of available radar sensors, two remote-sensing SAR data sets were selected: 1 m resolution X-band TerraSAR-X and 10 m resolution L-band Advanced Land Observing Satellite (ALOS) phased array L-band SAR. ‘Tianjin Binhai New Area’ has become one of the most important economic centres in China, and one of its fast-developing urban areas, Tanggu, was selected as the study area. PSI processing was conducted on both data sets. Substantial validation was performed for PSI results from both data sources using levelling measurement. The overall good agreement confirmed the ground deformation maps derived from both data sets. Integration of PSI results appears to be a potentially significant contribution to solving the problems related to common spatial and temporal gaps when using single-type data sets. Application of both data sets revealed the capability of integrated PSIs to measure ground deformation with strong temporal and spatial variation, thereby improving the interpretation of ground deformation characteristics which increases the confidence of hazard assessment and provides some insight into complex underlying mechanisms.     

Deformation retrieval in large areas based on multibaseline DInSAR algorithm: a case study in Cangzhou,northern China

The DInSAR technique with a multibaseline is becoming popular nowadays to investigate slow urban deformation. In this paper, we focus on deformation retrieval in large areas, including urban and suburban areas. Based on the multibaseline DInSAR algorithm proposed by Mora, three extensions are derived. First, least‐squares adjustment and error‐controlling methods are used to obtain stable deformation velocity and height error estimations. The least‐squares QR factorizaiton algorithm is emphasized to solve large, linear, and sparse functions. Second, a new complex network is presented to limit noise effects on the Delaunay triangular network. Third, by combining complex and Delaunay networks, large‐area deformation is investigated, from centre urban areas to suburban areas. The enhanced algorithm is performed to investigate the subsidence of Cangzhou, Hebei province (northern China) during 1993–1997 by using 9 ERS SLC data. The experimental results show serious subsidence in the region and are validated by levelling data and groundwater wells data. Compared with levelling data, the estimation errors of linear deformation velocity in urban areas are in the range of (?2, 2) mm year^?1, and in suburban areas, the errors are in the range of (?26, 15) mm year^?1, which is sufficiently feasible to determine the status of subsidence relative to the maximum deformation velocity of about ?100 mm year^?1. The subsidence centres in urban areas are consistent with the spatial distribution of groundwater wells, which provides evidence that groundwater overexploitation is the main cause of subsidence in Cangzhou. The closure of wells will be a good way to control subsidence in the future.