Mexico City land subsidence in 2014-2015 with Sentinel-1 IW TOPS: results using the Intermittent SBAS (ISBAS) technique

Differential Interferometric Synthetic Aperture Radar (DInSAR) can be considered as an efficient and cost effective technique for monitoring land subsidence due to its large spatial coverage and high accuracy provided. The recent commissioning of the first Sentinel-1 satellite offers improved support to operational surveys using DInSAR due to regular observations from a wide-area product. In this paper we show the results of an intermittent small-baseline subset (ISBAS) time-series analysis of 18 Interferometric Wide swath (IW) products of a 39,000 km2 area of Mexico acquired between 3 October 2014 and 7 May 2015 using the Terrain Observation with Progressive Scans in azimuth (TOPS) imaging mode. The ISBAS processing was based upon the analysis of 143 small-baseline differential interferograms. After the debursting, merging and deramping steps necessary to process Sentinel-1 IW roducts, the method followed a standard approach to the DInSAR analysis. The Sentinel-1 ISBAS results confirm the magnitude and extent of the deformation that was observed in Mexico City, Chalco, Ciudad Nezahualcóyotl and Iztapalapa by other C-band and L-band DInSAR studies during the 1990s and 2000s. Subsidence velocities from the Sentinel-1 analysis are, in places, in excess of -24 cm/year along the satellite line-of-sight, equivalent to over ~-40 cm/year vertical rates. This paper demonstrates the potential of Sentinel-1 IW TOPS imagery to support wide-area DInSAR surveys over what is a very large and diverse area in terms of land cover and topography

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Elevation Extraction from Spaceborne SAR Tomography Using Multi-Baseline COSMO-SkyMed SAR Data

SAR tomography (TomoSAR) extends SAR interferometry (InSAR) to image a complex 3D scene with multiple scatterers within the same SAR cell. The phase calibration method and the super-resolution reconstruction method play a crucial role in 3D TomoSAR imaging from multi-baseline SAR stacks, and they both influence the accuracy of the 3D SAR tomographic imaging results. This paper presents a systematic processing method for 3D SAR tomography imaging. Moreover, with the newly released TanDEM-X 12 m DEM, this study proposes a new phase calibration method based on SAR InSAR and DEM error estimation with the super-resolution reconstruction compressive sensing (CS) method for 3D TomoSAR imaging using COSMO-SkyMed Spaceborne SAR data. The test, fieldwork, and results validation were executed at Zipingpu Dam, Dujiangyan, Sichuan, China. After processing, the 1 m resolution TomoSAR elevation extraction results were obtained. Against the terrestrial Lidar ‘truth’ data, the elevation results were shown to have an accuracy of 0.25 ± 1.04 m and a RMSE of 1.07 m in the dam area. The results and their subsequent validation demonstrate that the X band data using the CS method are not suitable for forest structure reconstruction, but are fit for purpose for the elevation extraction of manufactured facilities including buildings in the urban area

Multi-sensor synergy for persistent scatterer interferometry based ground subsidence monitoring

Ground subsidence is a common phenomenon which causes disturbances and damages on the Earth’s surface. Especially in urban areas, it poses risk to life and property. Establishing solutions for damage prevention requires knowledge of subsidence behavior over time and space, which entails the collection of geospatial information. The present work investigates the ground surface dynamics over a field of deep mining in Sondershausen, Germany based on multi-temporal Synthetic Aperture Radar (SAR) images. Deformation patterns are extracted by means of Persistent Scatterer Interferometry (PSI), a technique that exploits the spatio-temporal characteristics of interferometric signatures from persistent scatterers. Since the impact of subsidence on surface structures varies spatially, high-risk areas can only be identified when the subsidence profile is known. To model the geometry of the subsidence bowl, the present study extends the extracted point information to a surface of estimations by interpolation. Furthermore, by the synergistic usage of PS estimations from different satellite sensors, this research addresses the problem of undersampling in critical areas, which is a common limitation of the PSI approach. The methodology developed here estimates missing information, i.e. refines the initial model, by deformation map of a different sensor covering a different time interval. In order to extend the period of monitoring as well as to improve the spatial and temporal sampling, the ground subsidence in Sondershausen is monitored with a multi-sensor SAR dataset. The C- and L-band acquisitions of the sensors ERS-1/2 (1995–2005), Envisat-ASAR (2004–2010) and ALOS-PALSAR (2007–2010) are used to derive 15 years of subsidence information at the location of persistent scatterers. From a temporal viewpoint, the obtained deformation maps indicate a non-linearly decreasing trend of ground subsidence, which is consistent with the backfilling history of the mine. From a spatial viewpoint, the results suggest one major subsidence trough located in the urban area of Sondershausen and a minor one found in the nearby village of Großfurra. The PSI deformation maps and models are validated in reference to the available leveling measurements covering the site in Sondershausen. In general, the validation results suggest a good agreement between the PSI and surveying models with the normalized root-mean-square error (RMSE) lower than 0.11. However, some significant deviations of ERS estimations are also found for a critical region. In this area the absence of persistent scatterers contributes largely to the observed differences. Consequently, the spatial refinement by synergy is applied to this region. The integration of points from ASAR or PALSAR deformation maps result in an improvement in the modeled geometry of the subsidence trough. With this improvement the RMSE calculated for the ERS model is decreased from 0.061 to 0.054. The application demonstrates the synergistic potential of multi-sensor PSI analysis to improve the interpretation of ground subsidence characteristics and, thus, to increase the confidence of risk assessment.Absenkungen des Bodens stellen ein häufig auftretendes Phänomen dar. Diese Bodensenkungen verursachen Störungen und Schäden an der Erdoberfläche, die, insbesondere in urbanen Gebieten, Menschenleben gefährden und die bestehende Infrastruktur beschädigen können. Die Entwicklung von Lösungsansätzen zur Vermeidung von Schäden erfordert fundierte Kenntnisse über die räumliche und zeitliche Verteilung der Absenkungsbewegungen. Im Rahmen der vorliegenden Studie wurde die Dynamik der Bodenbewegungen über dem Salzabbaugebiet Sondershausen in Deutschland mittels Zeitserien von Synthetic Aperture Radar (SAR)-Aufnahmen untersucht. Zur Analyse der Zeitserien wurde das Verfahren der Persistent Scatterer Interferometry (PSI) eingesetzt. Diese Methode zur Extraktion der Bodendeformation basiert auf der Auswertung räumlicher und zeitlicher Charakteristika der interferometrischen Signaturen zeitlich stabiler Punktstreuer. Zur Bestimmung von Gebieten, die von den Bodensenkungen besonders stark betroffen sind, ist eine detailliertere Ermittlung der geometrischen Eigenschaften der Absenkung nötig, da die Oberflächenstrukturen entlang des Absenkungsprofiles variieren. Aufgrund dessen wurde in der vorliegenden Studie die punktweise gewonnene Information in die Flache extrapoliert, um eine räumliche Modellierung des Absenkungsbeckens zu ermöglichen. Zur genauen Vermessung von Absenkungen mittels PSI ist eine möglichst hohe räumliche und zeitliche Abtastrate anzustreben. Diese sind bei der Untersuchung eines Gebietes mithilfe eines einzelnen Radarsensors häufig nicht gewährleistet. Im Rahmen der vorliegenden Arbeit wird ein Lösungsansatz für diese Limitation vorgestellt, welcher auf der synergetischen Verschneidung von Deformationskarten mehrerer Radarsensoren basiert. Fehlende Messwerte in der ERS-Zeitreihe werden anhand von Punktstreuern in ASAR- und PALSAR-Szenen geschätzt. Die Bodenbewegungen im Gebiet Sondershausen wurden mithilfe von Daten verschiedener Radarsensoren beobachtet, um eine verbesserte räumliche und zeitliche Abtastrate zu erzielen. Hierzu wurden Aufnahmen der C- bzw. L-Band Sensoren ERS-1/2 (1995–2005), Envisat-ASAR (2004–2010) und ALOS-PALSAR (2007–2010) auf zeitlich stabile Punktstreuer untersucht. Die zeitliche Analyse der resultierenden Deformationskarten zeigt eine nicht-lineare Abnahme der Bodenabsenkungen. Dieses Verhalten steht im Einklang mit den rezenten Verfüllungsaktivitäten in der stillgelegten Mine. Die räumliche Auswertung der Daten deutet auf ein Absenkungsbecken im Stadtgebiet von Sondershausen hin. Ein weiteres, kleineres Becken konnte um die Siedlung Großfurra identifiziert werden. Sowohl die Deformationskarten als auch die abgeleiteten Modelle wurden einer umfangreichen Validierung anhand von Nivellement-Messungen unterzogen. Die Ergebnisse zeigen generell eine gute Übereinstimmung zwischen den PSI- und Bodenmessungen mit einem root-mean-square error (RMSE) von weniger als 0,11. Nur vereinzelt kommt es zu signifikanten Abweichungen, was insbesondere auf die ERS-Ergebnisse zutrifft. Dies lässt sich durch fehlende Punktstreuer in den aktiven Absenkungsbereichen während der ERS-Messungen begründen. Durch die Integration von Punkten aus den ASAR oder PALSAR-basierenden Deformationskarten konnte die Geometrie der Absenkungen verbessert werden. Der für das ERS-Modell ermittelte RMSE verringert sich auf diese Weise von 0,061 auf 0,054. Die vorliegende Anwendung zeigt das Synergiepotential multi-sensoraler Daten und Methoden verbesserten Interpretation von Bodenabsenkungen sowie zur genaueren Abschatzung und Bewertung von daraus resultierenden Risiken

Basin scale assessment of landslides geomorphological setting by advanced InSAR analysis

An extensive investigation of more than 90 landslides affecting a small river basin in Central Italy was performed by combining field surveys and remote sensing techniques. We thus defined the geomorphological setting of slope instability processes. Basic information, such as landslides mapping and landslides type definition, have been acquired thanks to geomorphological field investigations and multi-temporal aerial photos interpretation, while satellite SAR archive data (acquired by ERS and Envisat from 1992 to 2010) have been analyzed by means of A-DInSAR (Advanced Differential Interferometric Synthetic Aperture Radar) techniques to evaluate landslides past displacements patterns. Multi-temporal assessment of landslides state of activity has been performed basing on geomorphological evidence criteria and past ground displacement measurements obtained by A-DInSAR. This step has been performed by means of an activity matrix derived from information achieved thanks to double orbital geometry. Thanks to this approach we also achieved more detailed knowledge about the landslides kinematics in time and space

Point target interferometry as applied to the characterization of localized deformation features

Title from PDF of title page (University of Missouri--Columbia, viewed on Feb. 23, 2010).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Dr. Brent Rosenblad, Dissertation Supervisor.Vita.Ph. D. University of Missouri--Columbia 2008.Monitoring of ground deformation is a critical component of geotechnical engineering practice. This study investigated the application of synthetic aperture radar interferometry (InSAR), using point target analysis (IPTA) for characterizing localized deformation features that are often associated with geotechnical engineering activities. In contrast to discrete point in-situ deformation measurement techniques, InSAR can be used to obtain a broader view of deformation processes at a site. Satellite data available for the time period of construction of the Los Angeles Metro Rail Red Line was utilized to characterize the technique in terms of dependence of the feasibility in its application on SAR image acquisition parameters. Additionally, a statistical assessment of the sensitivity of deformation rates and the associated standard errors to the size of the dataset analyzed was performed by analyzing randomly generated subsets of data. While the spatial and temporal signatures corresponding to tunneling during the construction of the Red Line were successfully detected, it was found that a minimum of twenty SAR acquisitions were required in order to constrain the deformation history of the study area. From the sensitivity analysis, it was found that the variability of the derived estimates of deformation parameters varied inversely as a function of the size of the dataset used for analysis.Includes bibliographical references

Advanced pixel selection and optimization algorithms for Persistent Scatterer Interferometry (PSI)

Tesi amb diferents seccions retallades per dret de l'editorPremi Extraordinari de Doctorat, promoció 2018-2019. Àmbit de les TICGround deformation measurements can provide valuable information for minimization of associated loss and damage caused by natural and environmental hazards. As a kind of remote sensing technique, Persistent Scatterer Interferometry (PSI) SAR is able to measure ground deformation with high spatial resolution, efficiently. Moreover, the ground deformation monitoring accuracy of PSI techniques can reach up to millimeter level. However, low coherence could hinderthe exploitation of SAR data, and high-accuracy deformation monitoring can only be achieved by PSI for high quality pixels. Therefore, pixel optimization and identification of coherent pixels are crucial for PSI techniques. In this thesis, advanced pixel selection and optimization algorithms have been investigated. Firstly, a full-resolution pixel selection method based on the Temporal Phase Coherence (TPC) has been proposed. This method first estimates noise phase term of each pixel at interferogram level. Then, for each pixel, its noise phase terms of all interferograms are used to assess this pixel’s temporal phase quality (i.e., TPC). In the next, based on the relationship between TPC and phase Standard Deviation (STD), a threshold can be posed on TPC to identify high phase quality pixels. This pixel selection method can work with both Deterministic Scatterers (PSs) and Distributed Scatterers (DSs). To valid the effectiveness of the developed method, it has been used to monitor the Canillo (Andorra) landslide. The results show that the TPC method can obtained highest density of valid pixels among the employed three approaches in this challenging area with X-band SAR data. Second, to balance the polarimetric DInSAR phase optimization effect and the computation cost, a new PolPSI algorithm is developed. This proposed PolPSI algorithm is based on the Coherency Matrix Decomposition result to determine the optimal scattering mechanism of each pixel, thus it is named as CMD-PolPSI. CMDPolPSI need not to search for solution within the full space of solution, it is therefore much computationally faster than the classical Equal Scattering Mechanism (ESM) method, but with lower optimization performance. On the other hand, its optimization performance outperforms the less computational costly BEST method. Third, an adaptive algorithm SMF-POLOPT has been proposed to adaptive filtering and optimizing PolSAR pixels for PolPSI applications. This proposed algorithm is based on PolSAR classification results to firstly identify Polarimetric Homogeneous Pixels (PHPs) for each pixel, and at the same time classify PS and DS pixels. After that, DS pixels are filtered by their associated PHPs, and then optimized based on the coherence stability phase quality metric; PS pixels are unfiltered and directly optimized based on the DA phase quality metric. SMF-POLOPT can simultaneously reduce speckle noise and retain structures’ details. Meanwhile, SMF-POLOPT is able to obtain much higher density of valid pixels for deformation monitoring than the ESM method. To conclude, one pixel selection method has been developed and tested, two PolPSI algorithms have been proposed in this thesis. This work make contributions to the research of “Advanced Pixel Selection and Optimization Algorithms for Persistent Scatterer InterferometryLes mesures de deformació del sòl poden proporcionar informació valuosa per minimitzar les pèrdues i els danys associats causats pels riscos naturals i ambientals. Com a tècnica de teledetecció, la interferometria de dispersors persistents (Persistent Scatter Interferometry, PSI) SAR és capaç de mesurar de forma eficient la deformació del terreny amb una alta resolució espacial. A més, la precisió de monitorització de la deformació del sòl de les tècniques PSI pot arribar a arribar a nivells del mil·límetre. No obstant això, una baixa coherència pot dificultar l’explotació de dades SAR i el control de deformació d’alta precisió només es pot aconseguir mitjançant PSI per a píxels d’alta qualitat. Per tant, l’optimització de píxels i la identificació de píxels coherents són crucials en les tècniques PSI. En aquesta tesi s¿han investigat algorismes avançats de selecció i optimització de píxels. En primer lloc, s'ha proposat un mètode de selecció de píxels de resolució completa basat en la coherència temporal de fase (Temporal Phase Coherence, TPC). Aquest mètode estima per primera vegada el terme de fase de soroll de cada píxel a nivell d’interferograma. A continuació, per a cada píxel, s'utilitzen els termes de la fase de soroll de tots els interferogrames per avaluar la qualitat de fase temporal d'aquest píxel (és a dir, TPC). A la següent, basant-se en la relació entre el TPC i la desviació estàndard de fase (STD), es pot plantejar un llindar de TPC per identificar píxels de qualitat de fase alta. Aquest mètode de selecció de píxels es capaç de detectar tant els dispersors deterministes (PS) com els distribuïts (DS). Per validar l’eficàcia del mètode desenvolupat, s’ha utilitzat per controlar l’esllavissada de Canillo (Andorra). Els resultats mostren que el mètode TPC pot obtenir la major densitat de píxels vàlids, comparat amb els mètodes clàssics de selecció, en aquesta àrea difícil amb dades de SAR de banda X. En segon lloc, per equilibrar l’efecte d’optimització de fase DInSAR polarimètrica i el cost de càlcul, es desenvolupa un nou algorisme de PolPSI. Aquest algorisme proposat de PolPSI es basa en el resultat de la descomposició de la matriu de coherència per determinar el mecanisme de dispersió òptim de cada píxel, de manera que es denomina CMD-PolPSI. CMDPolPSI no necessita buscar solucions dins de l’espai complet de la solució, per tant, és molt més eficient computacionalment que el mètode clàssic de mecanismes d’igualtat de dispersió (Equal Scattering Mechanism, ESM), però amb un efecte d’optimització no tant òptim. D'altra banda, el seu efecte d'optimització supera el mètode BEST, el que te un menor cost computacional. En tercer lloc, s'ha proposat un algoritme adaptatiu SMF-POLOPT per al filtratge adaptatiu i l'optimització de píxels PolSAR per a aplicacions PolPSI. Aquest algorisme proposat es basa en els resultats de classificació PolSAR per identificar primer els píxels homogenis polarimètrics (PHP) per a cada píxel i, alhora, classificar els píxels PS i DS. Després d'això, els píxels DS es filtren pels seus PHP associats i, a continuació, s'optimitzen en funció de la mètrica de qualitat de la fase d'estabilitat de coherència; els píxels classificats com PS no es filtren i s'optimitzen directament en funció de la mètrica de qualitat de la fase DA. SMF-POLOPT pot reduir simultàniament el soroll de la fase interferomètrica i conservar els detalls de les estructures. Mentrestant, SMF-POLOPT aconsegueix obtenir una densitat molt més alta de píxels vàlids per al seguiment de la deformació que el mètode ESM. Per concloure, en aquesta tesi s’ha desenvolupat i provat un mètode de selecció de píxels, i s’han proposat dos algoritmes PolPSI. Aquest treball contribueix a la recerca en "Advanced Pixel Selection and Optimization Algorithms for Persistent Scatterer Interferometry"Postprint (published version

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

Ground-based synthetic aperture radar (GBSAR) interferometry for deformation monitoring

Ph. D ThesisGround-based synthetic aperture radar (GBSAR), together with interferometry, represents a powerful tool for deformation monitoring. GBSAR has inherent flexibility, allowing data to be collected with adjustable temporal resolutions through either continuous or discontinuous mode. The goal of this research is to develop a framework to effectively utilise GBSAR for deformation monitoring in both modes, with the emphasis on accuracy, robustness, and real-time capability. To achieve this goal, advanced Interferometric SAR (InSAR) processing algorithms have been proposed to address existing issues in conventional interferometry for GBSAR deformation monitoring. The proposed interferometric algorithms include a new non-local method for the accurate estimation of coherence and interferometric phase, a new approach to selecting coherent pixels with the aim of maximising the density of selected pixels and optimizing the reliability of time series analysis, and a rigorous model for the correction of atmospheric and repositioning errors. On the basis of these algorithms, two complete interferometric processing chains have been developed: one for continuous and the other for discontinuous GBSAR deformation monitoring. The continuous chain is able to process infinite incoming images in real time and extract the evolution of surface movements through temporally coherent pixels. The discontinuous chain integrates additional automatic coregistration of images and correction of repositioning errors between different campaigns. Successful deformation monitoring applications have been completed, including three continuous (a dune, a bridge, and a coastal cliff) and one discontinuous (a hillside), which have demonstrated the feasibility and effectiveness of the presented algorithms and chains for high-accuracy GBSAR interferometric measurement. Significant deformation signals were detected from the three continuous applications and no deformation from the discontinuous. The achieved results are justified quantitatively via a defined precision indicator for the time series estimation and validated qualitatively via a priori knowledge of these observing sites.China Scholarship Council (CSC), Newcastle Universit