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

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

Monitoring land subsidence of airport using InSAR time-series techniques with atmospheric and orbital error corrections

Land subsidence is one of the common geological hazards worldwide and mostly caused by human activities including the construction of massive infrastructures. Large infrastructure such as airport is susceptible to land subsidence due to several factors. Therefore, monitoring of the land subsidence at airport is crucial in order to prevent undesirable loss of property and life. Remote sensing technique, especially Interferometric Synthetic Aperture Radar (InSAR) has been successfully applied to measure the surface deformation over the past few decades although atmospheric artefact and orbital errors are still a concerning issue in this measurement technique. Multi-temporal InSAR, an extension of InSAR technique, uses large sets of SAR scenes to investigate the temporal evolution of surface deformation and mitigate errors found in a single interferogram. This study investigates the long-term land subsidence of the Kuala Lumpur International Airport (KLIA), Malaysia and Singapore Changi Airport (SCA), Singapore by using two multi-temporal InSAR techniques like Small Baseline Subset (SBAS) and Multiscale InSAR Time Series (MInTS). General InSAR processing was conducted to generate interferogram using ALOS PALSAR data from 2007 until 2011. Atmospheric and orbital corrections were carried out for all interferograms using weather model, namely European Centre for Medium Range Weather Forecasting (ECMWF) and Network De-Ramping technique respectively before estimating the time series land subsidence. The results show variation of subsidence with respect to corrections (atmospheric and orbital) as well as difference between multi-temporal InSAR techniques (SBAS and MInTS) used. After applying both corrections, a subsidence ranging from 2 to 17 mm/yr was found at all the selected areas at the KLIA. Meanwhile, for SCA, a subsidence of about less than 10 mm/yr was found. Furthermore, a comparison between two techniques (SBAS and MInTS) show a difference rate of subsidence of about less than 1 mm/yr for both study area. SBAS technique shows more linear result as compared to the MInTS technique which shows slightly scattering pattern but both techniques show a similar trend of surface deformation in both study sites. No drastic deformation was observed in these two study sites and slight deformation was detected which about less than 20mm/yr for both study areas probably occurred due to several reasons including conversion of the land use from agricultural land, land reclamation process and also poor construction. This study proved that InSAR time series surface deformation measurement techniques are useful as well as capable to monitor deformation of large infrastructure such as airport and as an alternative to costly conventional ground measurement for infrastructure monitoring