Differential Interferometric Synthetic Aperture Radar Data Research Articles

Spatio-Temporal Quality Indicators for Differential Interferometric Synthetic Aperture Radar Data

Satellite-based interferometric synthetic aperture radar (InSAR) is an invaluable technique in the detection and monitoring of changes on the surface of the earth. Its high spatial coverage, weather friendly and remote nature are among the advantages of the tool. The multi-temporal differential InSAR (DInSAR) methods in particular estimate the spatio-temporal evolution of deformation by incorporating information from multiple SAR images. Moreover, opportunities from the DInSAR techniques are accompanied by challenges that affect the final outputs. Resolving the inherent ambiguities of interferometric phases, especially in areas with a high spatio-temporal deformation gradient, represents the main challenge. This brings the necessity of quality indices as important DInSAR data processing tools in achieving ultimate processing outcomes. Often such indices are not provided with the deformation products. In this work, we propose four scores associated with (i) measurement points, (ii) dates of time series, (iii) interferograms and (iv) images involved in the processing. These scores are derived from a redundant set of interferograms and are calculated based on the consistency of the unwrapped interferometric phases in the frame of a least-squares adjustment. The scores reflect the occurrence of phase unwrapping errors and represent valuable input for the analysis and exploitation of the DInSAR results. The proposed tools were tested on 432,311 points, 1795 interferograms and 263 Sentinel-1 single look complex images by employing the small baseline technique in the PSI processing chain, PSIG of the geomatics division of the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC). The results illustrate the importance of the scores—mainly in the interpretation of the DInSAR outputs.

Mining large-gradient subsidence monitoring using D-InSAR optimized by GNSS

ABSTRACT In the process of developing mine resources, mining subsidence is inevitable. The D-InSAR (differential interferometric synthetic aperture radar) technology has been widely used to monitor large-scale ground subsidence in mining areas in recent years. However, the limitations of this technology mean that large-gradient ground subsidence cannot be monitored. This paper describes a weighted total least-squares method that can be used to determine the piecewise linear mapping between GNSS (global navigation satellite system) data and D-InSAR data. This mapping can be applied to optimize the conventional D-InSAR monitoring results, particularly in large-gradient subsidence areas, enabling the mining subsidence to be comprehensively evaluated. The proposed method is used to extract the surface subsidence information for a certain area of the Sihe mine in Shanxi Province, China. It is found that the optimized data is more reliable and accurate than the conventional D-InSAR monitoring data in the case of large-gradient subsidence.

Automatic delineation of glacier grounding lines in differential interferometric synthetic-aperture radar data using deep learning

Delineating the grounding line of marine-terminating glaciers—where ice starts to become afloat in ocean waters—is crucial for measuring and understanding ice sheet mass balance, glacier dynamics, and their contributions to sea level rise. This task has been previously done using time-consuming, mostly-manual digitizations of differential interferometric synthetic-aperture radar interferograms by human experts. This approach is no longer viable with a fast-growing set of satellite observations and the need to establish time series over entire continents with quantified uncertainties. We present a fully-convolutional neural network with parallel atrous convolutional layers and asymmetric encoder/decoder components that automatically delineates grounding lines at a large scale, efficiently, and accompanied by uncertainty estimates. Our procedure detects grounding lines within 232 m in 100-m posting interferograms, which is comparable to the performance achieved by human experts. We also find value in the machine learning approach in situations that even challenge human experts. We use this approach to map the tidal-induced variability in grounding line position around Antarctica in 22,935 interferograms from year 2018. Along the Getz Ice Shelf, in West Antarctica, we demonstrate that grounding zones are one order magnitude (13.3 ± 3.9) wider than expected from hydrostatic equilibrium, which justifies the need to map grounding lines repeatedly and comprehensively to inform numerical models.

D-InSAR monitoring of ground deformation related to the dewatering of construction sites. A case study of Glòries Square, Barcelona

The aim of this paper is to demonstrate how the integration of differential interferometric synthetic aperture radar (D-InSAR) and levelling improves the monitoring of ground deformation phenomena, thereby enabling their complete understanding. The complementarity between D-InSAR and levelling is illustrated through a case study of the construction of a road tunnel beneath Glòries Square, Barcelona; D-InSAR is employed to continuously monitor the works, notably the dewatering of the site. This study focuses primarily on D-InSAR data obtained from the processing of Sentinel-1A data following a persistent scatterer interferometry procedure. The spatial distribution of the deformation and its temporal evolution are analysed with detailed hydrogeological and piezometric data. The magnitude of deformation is discussed using levelling data and an analytical estimation based on the hydromechanical parameters of the ground obtained from a pre-existing hydrogeological numerical model and pumping tests. The D-InSAR results are shown to be essential for identifying the origin of ground deformation and the constraints on its spread. Such observations at the construction site and district (~2 km radius) scales with sub-centimetric deformation are precious contributions of D-InSAR data, whereas levelling offers a more accurate quantification of the deformation, although this remains an open issue to be further investigated. • Differential interferometric SAR as monitoring technique in civil works. • Ground deformation related to the dewatering of construction works. • Hydrogeological interpretation of D-InSAR results. • Complementarity of differential interferometric SAR and levelling.

Quantifying relationships between subsidence and longwall face advance using DInSAR

Surface subsidence that results from longwall mining can be large magnitude and can affect significant areas. Conventional methods for subsidence monitoring include leveling, global positioning system (GPS), and photogrammetric surveys. Remote sensing techniques including, aerial LiDAR, terrestrial laser scanning, and satellite-based Differential Interferometric Synthetic Aperture Radar (DInSAR), are also used to measure deformation associated with subsidence. DInSAR data are different than data from conventional subsidence surveys. Images capture data over large areas (hundreds of kilometers), and each pixel (data point) in an image quantifies the average displacement over an area of square meters. DInSAR data can have fairly high time resolution; imaging periods typically range from weeks to months. DInSAR data can be useful to monitor subsidence sequentially over short periods. Regularly monitoring subsidence may help define if caving is progressing normally and can establish relationships between surface deformation and longwall face advance, which has potential to help quantify possible risks to mine stability. In this study, subsidence at a longwall trona mine is monitored over short periods, typically 12 days, as the longwall face is advanced through a panel. C-band interferometric wide swath synthetic aperture radar (SAR) images from the sentinel satellites are used to quantify the subsidence. The onset of subsidence occurs close in time to the beginning of the longwall face advance, and overall, the development of subsidence closely follows the longwall face advance.

Modelling groundwater rebound in recently abandoned coalfields using DInSAR

Advances in differential interferometric synthetic aperture radar (DInSAR) processing algorithms, such as the Intermittent Small Baseline Subset (ISBAS), and increased data availability from SAR systems, such as Sentinel-1, provide the opportunity to increase the spatial and temporal density of ground deformation measurements. Such measurements, when combined with modelling, have the potential to make a significant cost-effective contribution to the progressive abandonment strategy of recently closed coalfields. Applications of DInSAR over coalfields have observed heave in coal measures rocks and temporal correlations between the rise of mine water and deformation time-series. The cessation of systematic dewatering can have a variety of detrimental impacts and knowledge of the time-scales (i.e. the rate of rebound) and structure of the mine system are crucial to the remediation strategy. Although mine plans and borehole measurements provide vital information in this regard, mine plans are often incomplete or inaccurate, whereas monitoring boreholes are spatially sparse. Consequently, groundwater can flow in unanticipated directions via goaf, mine shafts and roadways, making it difficult to determine where the impacts of rebound are likely to occur. In this study, ground deformation data obtained using ISBAS DInSAR on ENVISAT (2002–2009) and Sentinel-1 (2015–2019) data are used to develop a simple method to model groundwater rebound in abandoned coalfields. A forward analytical model based upon the principle of effective stress and mine water ponds is first implemented to estimate surface heave in response to changes in groundwater levels measured in monitoring boreholes. The forward model is then calibrated and validated using the ground deformation data. The DInSAR data were subsequently inverted to map the change in groundwater levels in greater detail across the coalfield and forecast surface discharges in order to support mitigation strategies.

Satellite interferometry for mapping surface deformation time series in one, two and three dimensions: A new method illustrated on a slow-moving landslide

Space-borne Differential Interferometric Synthetic Aperture Radar (DInSAR) has been extensively used in the last two decades to measure ground surface deformation, providing key information for the characterization and understanding of many natural and anthropogenic processes. However, conventional DInSAR technique measures only one component of the surface deformation (i.e. the satellite's line-of-sight (LOS)), causing the interpretation of DInSAR measurements to be challenging and potentially narrowing the understanding of the mechanisms and dynamics of the deformation processes at work. Presently available methods that estimate 3D surface deformation from DInSAR generally operate on individual interferograms and therefore do not produce 3D surface deformation time series. However, the availability of time series is essential for studying surface deformation processes, bringing information on, e.g., temporally and spatially-variable external forcing conditions and characteristics of future deformation patterns. The Multidimensional Small Baseline Subset (MSBAS) method was already able to produce 2D (east and vertical) surface deformation time series from multi-tracks and multi-sensors DInSAR data. Here we propose a novel version of the MSBAS (MSBAS-3D) method that can produce 3D (north, east, and vertical) surface deformation time series from ascending and descending DInSAR data. This new method proposes measuring the surface deformation for processes producing motion parallel to the surface, such as landslides and glacier flows, while conserving the DInSAR accuracy. The ability of MSBAS-3D to capture the full 3D deformation pattern of processes with a surface signature is illustrated for a large, slow-moving, deep-seated landslide, for which long DInSAR and dGNSS time series, as well as ground truth data, are available. Surface deformation is measured over a four-year period using 1D (LOS), 2D and 3D MSBAS methods, and the advantages and limitations of each approach are described. In this case, the novel MSBAS-3D technique produces superior results that greatly simplify interpretation of the processes at work. The MSBAS-3D software can be downloaded from http://insar.ca/.

Seasonal and multi-year surface displacements measured by DInSAR in a High Arctic permafrost environment

Arctic landscapes undergo seasonal and long-term changes as the active layer thaws and freezes, which can result in localized or irregular subsidence leading to the formation of thermokarst terrain. Differential Interferometric Synthetic Aperture Radar (DInSAR) is a technique capable of measuring ground surface displacements resulting from thawing permafrost at centimetre precision and is quickly gaining acceptance as a means of measuring ground displacement in permafrost regions. Using RADARSAT-2 stacked DInSAR data from 2013 and 2015 we determined the magnitude and patterns of land surface change in a continuous permafrost environment. At our study site situated in the Canadian High Arctic, DInSAR seasonal ground displacement patterns were consistent with field observations of permafrost degradation. As expected, many DInSAR values are close to the detection threshold (i.e., 1 cm) and therefore do not indicate significant change; however, DInSAR seasonal ground displacement patterns aligned well with climatological and soil conditions and offer geomorphological insight into subsurface processes in permafrost environments. While our dataset is limited to two years of data representing a three-year time period, the displacements derived from DInSAR provide insight into permafrost change in a High Arctic environment and demonstrate that DInSAR is an applicable tool for understanding environmental change in remote permafrost regions.

DInSAR data assimilation for settlement prediction: case study of a railway embankment in the Netherlands

Secondary settlements in soft soils represent a significant fraction of the total settlement induced by external loads. Consequently, these settlements can play a key role in performance, serviceability, and safety of engineering works such as buildings, roads, embankments, and pipelines. This paper addresses the development of a predictive settlement model for a railway embankment built on soft clayey–peaty soils by following an original procedure consisting of three cascading steps: (i) preliminary detection of the most settlement-affected portions of the infrastructure; (ii) development of an equivalent subsoil model to study secondary settlements; (iii) back-calculation of the parameters of a predictive settlement model (design subsoil model) via a variational data assimilation scheme that exploits ground displacement measurements derived from differential interferometric synthetic aperture radar (DInSAR) data. The main achievement relies on the retrieval of a stochastic prediction of secondary settlements that can contribute to rationalize both conventional monitoring campaigns and management of key infrastructure.

Subsidence at Cerro Prieto Geothermal Field and postseismic slip along the Indiviso fault from 2011 to 2016 RADARSAT‐2 DInSAR time series analysis

AbstractWe present RADARSAT‐2 Differential Interferometric Synthetic Aperture Radar (DInSAR) observations of deformation due to fluid extraction at the Cerro Prieto Geothermal Field (CPGF) and afterslip on the 2010 M7.2 El Mayor‐Cucapah (EMC) earthquake rupture during 2011–2016. Advanced multidimensional time series analysis reveals subsidence at the CPGF with the maximum rate greater than 100 mm/yr accompanied by horizontal motion (radial contraction) at a rate greater than 30 mm/yr. During the same time period, more than 30 mm of surface creep occurred on the Indiviso fault ruptured by the EMC earthquake. We performed inversions of DInSAR data to estimate the rate of volume changes at depth due to the geothermal production at the CPGF and the distribution of afterslip on the Indiviso fault. The maximum coseismic slip due to the EMC earthquake correlates with the Coulomb stress changes on the Indiviso fault due to fluid extraction at the CPGF. Afterslip occurs on the periphery of maximum coseismic slip areas. Time series analysis indicates that afterslip still occurs 6 years after the earthquake.

Multi-scale analysis of settlement-induced building damage using damage surveys and DInSAR data: A case study in The Netherlands

Highly compressible clayey and peaty (soft) soils may expose structures (e.g. buildings) and infrastructures (e.g. roads and embankments) resting on them to absolute/differential settlements. These latter, with passing of time, can induce damages whose level of severity depends on several factors such as: the spatial distribution of the thickness pertaining to soft soil layers; the groundwater regime; the characteristics of the exposed structures and infrastructures along with their state of maintenance. The analysis of damages and the resulting management of the built-up environment usually require high costs due to the amount of data necessary for setting up reliable forecasting models as well as for defining the most suitable restoration works. This paper presents a multi-scale procedure tailored to analyze the settlement-induced building damage. The selected case study deals with an urban area in The Netherlands where, at medium scale, the role of soft soils in predisposing the occurrence of ground surface settlements is first investigated. Then, at large scale the relationship between cause (i.e. settlements) and effects (i.e. damage) is analyzed for building aggregates via the combination of high-resolution advanced differential interferometric synthetic aperture radar (DInSAR) and in-situ damage survey data. Finally, as main novelty of the proposed multi-scale procedure, both the above datasets are used to generate, at detailed scale, empirical fragility curves for single buildings that, once further validated, could be valuably adopted for damage forecasting purposes in similar urban areas.

Study on high-precision regional monitoring method of high-grade highways subsidence under the influence of underground mining

High-grade highways are the foundation of regional economic development. How to monitor the deformation of high-grade highways under the influence of underground mining and guarantee their safe operation is very important and is directly relevant to regional economic development. Considering that Differential interferometric synthetic aperture radar (D-InSAR) technology has low monitoring accuracy around the maximum subsidence and high-accuracy levelling can only monitor the deformation of finite number points, the method of assimilating the D-InSAR data and levelling monitoring data based on Kalman filtering theory is proposed to improve precision of regional monitoring. Research results indicate that data assimilation results based on ensemble Kalman filter are much better than the inversion results and D-InSAR data. When applied to Zouji Highway of Jining, the total RMS is 17.7 mm after assimilating the D-InSAR data and levelling monitoring data, which can meet accuracy requirements of deformation monitoring of high-grade highways. Research results are of theoretical and practical significance to guarantee safe operation of high-grade highways under the influence of mining activities.

Integration of space-borne DInSAR data in a multi-method monitoring concept for alpine mass movements

This study presents the results of an experimental application of a multi-method measurement concept for the monitoring of alpine mass movements. Satellite-borne differential interferometric synthetic aperture radar (DInSAR) was applied as the key technology. To improve the information contents of the DInSAR displacement data for an individual mass movement, a complementary measurement was carried out with a three dimensional measurement system. The information on the 3D movement characteristics obtained by this complementary measurement was used to extrapolate subsequent DInSAR measurements to 3D. Terrestrial laser scanning (TLS) and Global Navigation Satellite System (GNSS) data were tested as complementary 3D measurement systems. The deviations between the single measurement systems were mainly controlled by the error budgets of the different methods. An exception were short term GNSS single point time series which included small scale surface movements that were not captured by the other methods. TLS proved to be the most suitable complementary method. A single TLS repeat measurement was sufficient to create a mask, which enables the projection of DInSAR displacement data to 3D. The application of satellite-borne DInSAR in alpine terrain is challenging; signal decorrelation is a problem due to fast terrain movements and snow coverage and can cause failure of the measurement system.

MONITORING OF LAND SUBSIDENCE IN RAVENNA MUNICIPALITY USING INTEGRATED SAR - GPS TECHNIQUES: DESCRIPTION AND FIRST RESULTS

The Emilia Romagna Region (N-E Italy) and in particular the Adriatic Sea coastline of Ravenna, is affected by a noticeable subsidence that started in the 1950s, when the exploitation of on and off-shore methane reservoirs began, along with the pumping of groundwater for industrial uses. In such area the current subsidence rate, even if lower than in the past, reaches the -2 cm/y. Over the years, local Authorities have monitored this phenomenon with different techniques: spirit levelling, GPS surveys and, more recently, Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques, confirming the critical situation of land subsidence risk. In this work, we present the comparison between the results obtained with DInSAR and GPS techniques applied to the study of the land subsidence in the Ravenna territory. With regard to the DInSAR, the Small Baseline Subset (SBAS) and the Coherent Pixel Technique (CPT) techniques have been used. Different SAR datasets have been exploited: ERS-1/2, ENVISAT, TerraSAR-X and Sentinel-1. Some GPS campaigns have been also carried out in a subsidence prone area. 3D vertices have been selected very close to existing persistent scatterers in order to link the GPS measurement results to the SAR ones. GPS data were processed into the International reference system and the comparisons between the coordinates, for the first 6 months of the monitoring, provided results with the same trend of the DInSAR data, even if inside the precision of the method.

MONITORING OF LAND SUBSIDENCE IN RAVENNA MUNICIPALITY USING INTEGRATED SAR - GPS TECHNIQUES: DESCRIPTION AND FIRST RESULTS

Abstract. The Emilia Romagna Region (N-E Italy) and in particular the Adriatic Sea coastline of Ravenna, is affected by a noticeable subsidence that started in the 1950s, when the exploitation of on and off-shore methane reservoirs began, along with the pumping of groundwater for industrial uses. In such area the current subsidence rate, even if lower than in the past, reaches the -2 cm/y. Over the years, local Authorities have monitored this phenomenon with different techniques: spirit levelling, GPS surveys and, more recently, Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques, confirming the critical situation of land subsidence risk. In this work, we present the comparison between the results obtained with DInSAR and GPS techniques applied to the study of the land subsidence in the Ravenna territory. With regard to the DInSAR, the Small Baseline Subset (SBAS) and the Coherent Pixel Technique (CPT) techniques have been used. Different SAR datasets have been exploited: ERS-1/2, ENVISAT, TerraSAR-X and Sentinel-1. Some GPS campaigns have been also carried out in a subsidence prone area. 3D vertices have been selected very close to existing persistent scatterers in order to link the GPS measurement results to the SAR ones. GPS data were processed into the International reference system and the comparisons between the coordinates, for the first 6 months of the monitoring, provided results with the same trend of the DInSAR data, even if inside the precision of the method.

Growth of a young pingo in the Canadian Arctic observed by RADARSAT-2 interferometric satellite radar

Abstract. Advancements in radar technology are increasing our ability to detect Earth surface deformation in permafrost environments. In this paper we use satellite Differential Interferometric Synthetic Aperture Radar (DInSAR) to describe the growth of a large, relatively young pingo in the Tuktoyaktuk Coastlands. High-resolution RADARSAT-2 imagery (2011–2014) analyzed with the Multidimensional Small Baseline Subset (MSBAS) DInSAR revealed a maximum 2.7 cm yr−1 of domed uplift located in a drained lake basin. Satellite measurements suggest that this feature is one of the largest diameter pingos in the region that is presently growing. Observed changes in elevation were modeled as a 348 × 290 m uniformly loaded elliptical plate with clamped edge. Analysis of historical aerial photographs suggested that ground uplift at this location initiated sometime between 1935 and 1951 following drainage of the residual pond. Uplift is largely due to the growth of intrusive ice, because the 9 % expansion of pore water associated with permafrost aggradation into saturated sands is not sufficient to explain the observed short- and long-term deformation rates. The modeled thickness of ice-rich permafrost using the Northern Ecosystem Soil Temperature (NEST) was consistent with the maximum height of this feature. Modeled permafrost aggradation from 1972 to 2014 approximated elevation changes estimated from aerial photographs for that time period. Taken together, these lines of evidence indicate that uplift is at least in part a result of freezing of the sub-pingo water lens. Seasonal variations in the uplift rate seen in the DInSAR data closely match the modeled seasonal pattern in the deepening rate of freezing front. This study demonstrates that interferometric satellite radar can detect and contribute to understanding the dynamics of terrain uplift in response to permafrost aggradation and ground ice development in remote polar environments. The present-day growth rate is smaller than predicted by the modeling and no clear growth is observed at other smaller pingos in contrast with field studies performed mainly before the 1990s. Investigation of this apparent discrepancy provides an opportunity to further develop observation methods and models.

Assimilation of GPS-Derived Atmospheric Propagation Delay in DInSAR Data Processing

Microwave radiation is almost insensitive in terms of power attenuation to the presence of atmosphere; the atmosphere is however an error source in repeat pass interferometry due to propagation delay variations. This effect represents a main limitation in the detection and monitoring of weak deformation patterns in differential interferometric Synthetic Aperture Radar (DInSAR), especially in emergency conditions. Due to the wavelength reduction current, X-Band sensors are even more sensitive to such error sources: procedures adopted in classical advanced DInSAR for atmospheric filtering may fail in the presence of higher revisiting rates. In this work, we show such effect on data acquired by the COSMO-SkyMed constellation. The dataset has been acquired with very high revisiting rates during the emergency phase. This feature allows clearly showing the inability of standard filtering adopted in common processing chains in handling seasonal atmospheric delay variations over temporal intervals spanning periods shorter than 1 year. We discuss a procedure for the mitigation of atmospheric propagation delay (APD) that is based on the integration of data of GPS systems which carries out measurements with large observation angles diversity practically in continuous time. The proposed algorithm allows a robust assimilation of the GPS atmospheric delay measurements in the multipass DInSAR processing and found on a linear approximation with the height of the atmospheric delay corresponding to a stratified atmosphere. Achieved results show a significant mitigation of the seasonal atmospheric variations.

Evaluation of RADARSAT-2 DInSAR Seasonal Surface Displacement in Discontinuous Permafrost Terrain, Yellowknife, Northwest Territories, Canada

. Differential Interferometric Synthetic Aperture Radar (DInSAR) is an increasingly viable method for assessing permafrost terrain stability, but the accuracy and performance within discontinuous permafrost terrain has not been well studied. We used a RADARSAT-2 DInSAR data stack for a 120-day period in the summer of 2010 to map seasonal surface displacement in the discontinuous permafrost terrain of Yellowknife, Northwest Territories. Calculated displacement was compared to surficial geology and municipal land use zones. Displacement results reveal that glaciofluvial, glaciolacustrine, humanly modified, and organic terrain are increasingly unstable, in contrast to predominantly stable bedrock. Within municipal zones, increased proportional displacement is related to higher proportions of glaciolacustrine sediments and organic terrain. Organic terrain, associated with the highest proportion of the moderate downward displacement (−3.0 cm to −6.0 cm), occupies less than 6% of the total area. Widespread glaciolacustrine sediments (30% total area) are associated with most of the downward displacement in municipal zones. Semi-quantitative field and geotechnical validations indicate that most areas of moderate seasonal downward displacement in developed areas also represent areas of long-term subsidence. This work shows that even a short InSAR data stack and a simple stack processing method can yield information that is useful for municipal knowledge and planning.Résumé. L’interférométrie différentielle par radar à synthèse d’ouverture (DInSAR) est une méthode de plus en plus viable pour évaluer la stabilité des terrains en zone de pergélisol, mais la précision et la performance dans les zones de pergélisol discontinu ne sont pas bien étudiées. Nous avons utilisé une pile de données DInSAR de RADARSAT-2 d’une période de 120 jours au cours de l’été 2010 pour cartographier le déplacement saisonnier de la surface du sol dans la zone de pergélisol discontinu de Yellowknife, Territoires du Nord-Ouest. Le déplacement calculé a été comparé à la géologie de surface et les zones municipales d’utilisation des terres. Les résultats de déplacements révèlent qu’en ordre de stabilité, du plus stable au moins stable, on trouve les zones fluvio-glaciaires, glacio-lacustres, humainement modifiées et organiques, tandis que le substrat rocheux est essentiellement stable. Dans les zones municipales, le déplacement proportionnel accru est lié à des proportions plus élevées de sédiments glacio-lacustres et du terrain organique. Le terrain organique, associé à la plus forte proportion du déplacement modéré vers le bas (−3.0 à −6.0 cm), occupe moins de 6% de la superficie totale. Les sédiments glacio-lacustres répandus (30% de la superficie totale) sont associés à la plupart des déplacements vers le bas dans les zones municipales. Les validations semi-quantitatives de terrain et géotechniques indiquent que la plupart des zones de déplacement saisonnier modéré vers le bas dans les régions développées représentent également des zones d’affaissement à long terme. Ce travail montre que même une pile de données InSAR de courte durée et une méthode de traitement de pile simple peuvent donner des informations utiles pour la connaissance et la planification municipale.

Modelling of Yingxiu–Beichuan fault zone based on refined DInSAR data of 2008 Wenchuan earthquake

Differential interferometric synthetic aperture radar (DInSAR) provides an essential constraint for forward modelling of seismic faulting. However, the crucial evidence of deformation along the very near vicinity of a seismic fault is often missing because chaotic ruptures destroy the InSAR signal coherence; such is the case of the Yingxiu–Beichuan fault zone of the 2008 Wenchuan earthquake. We developed an Adaptive Local Kriging (ALK) interpolation method to produce a refined DInSAR dataset which continues without the interruption of decoherence gaps. Thus the 3D configuration of the seismic faulting can be better constrained for forward modelling using the Poly3D software. Through parameter fine tuning in a sequence of trial and error simulation, the best fitting between the simulated interferogram and the ALK refined DInSAR interferograms is achieved using a structural model of the Yingxiu–Beichuan fault zone which comprises a total of 14 segments with dip angles varying from 20° to 60°, in the south-west, to 40° to 70°, in the north-east; some major fault segments are composed of multiple planes with varying dip angles. The model reveals that in the much disputed Beichuan–Pengguan area, the Yingxiu–Beichuan fault links with the Pengguan fault (which dips to the NW at ~30°) at a depth of ~13km. These two structures are interpreted as representing the foreland propagation of the Yingxiu–Beichuan fault by footwall collapse, a process that, in the vicinity of the Pengguan fault, involves the transfer of displacement from the older, Yingxiu–Beichuan fault to the younger Pengguan fault.

Numerical simulation of dynamic surface deformation based on DInSAR monitoring

Differential interferometric synthetic aperture radar (DInSAR) technology is a new method to monitor the dynamic surface subsidence. It can monitor the large scope of dynamic deformation process of surface subsidence basin and better reflect the surface subsidence form in different stages. But under the influence of factors such as noise and other factors, the tilt and horizontal deformation curves regularity calculated by DInSAR data are poorer and the actual deviation is larger. The tilt and horizontal deformations are the important indices for the safety of surface objects protection. Numerical simulation method was used to study the dynamic deformation of LW32 of West Cliff colliery in Australia based on the DInSAR monitoring data. The result indicates that the subsidence curves of two methods fit well and the correlation coefficient is more than 95%. The other deformations calculated by numerical simulation results are close to the theory form. Therefore, considering the influence, the surface and its subsidiary structures and buildings due to mining, the numerical simulation method based on the DInSAR data can reveal the distribution rules of the surface dynamic deformation values and supply the shortcomings of DInSAR technology. The research shows that the method has good applicability and can provide reference for similar situation.