Search

Displacement time series (TS) provides temporal and spatial information related to ground defor- mation. This study aims to investigate temporal behavior of ground deformation TS, including classification of displacement trends and periodicity evaluation, which ease the interpretation of movements. To this end, we propose several modifications to an existing automatic classification workflow of Persistent Scatterers Interferometry (PSI) TS using new tests to classify ground deformations into seven main trends: Stable, Linear, Quadratic, Bilinear, Phase Unwrapping Errors (PUE), Discontinuous with constant and different velocities. We illustrate our approach over 1500 km2 of the Granada region and the metropolitan area of Barcelona, which were monitored using Sentinel-1 images and a PSI technique. This study provided the spatial distribution of different ground movement types and was useful to detect several TS anomalies due to PUE. The proposed approach also identified stable targets, which were wrongly classified as moving scatterers by the existing classification method. A periodicity analysis was finally performed using the Welch’s power spectral density estimator to investigate seasonal and yearly fluctuations. The method was vali- dated using simulated data, where the classified TSs characterized by probable phase unwrapping errors were verified by PSI experts. The overall classification accuracy was 77.8%, indicating that the proposed method has a considerable TS classification potential., The work of S. Mohammad Mirmazloumi has been funded by the Spanish State Research Agency, through a grant for a pre-doctorate contract (Ref: PRE2018-083394). The work of Yismaw Wassie has been funded by AGAUR, Generalitat de Catalunya, through a grant for the recruitment of early- stage research staff (Ref: 2019 FI_B 00050). The processing of Granada has been funded by the project “RISKCOAST” (SOE3/P4/E0868) of the Interreg SUDOE Programme., Peer Reviewed, Postprint (published version)

Persistent Scatterer interferometry (PSI) is a group of advanced differential interferometric Synthetic Aperture Radar (SAR) techniques used to measure and monitor terrain deformation. Sentinel-1 has improved the data acquisition throughout and, compared to previous sensors, increased considerably the Differential Interferometric SAR (DInSAR) and PSI deformation monitoring potential. The effect of the refractive atmosphere on the interferometric phase and phase unwrapping ambiguity are two critical issues of InSAR. The low density of Persistent Scatterer (PS) in non-urban areas, another critical issue, has inspired the development of alternative approaches and refinement of the PS chains. Along with the efforts to develop methods to mitigate the three above-mentioned problems, the work presented in this thesis also deals with the presence of a new signal in multilooked interferograms which cannot be explained by noise, atmospheric or earth surface topography changes. This paper describes a method for atmospheric phase screen estimation using rain station weather data and three different data driven procedures to obtain terrain deformation maps. These approaches aim to exploit Sentinel-1 highly coherent interferograms and their short revisit time. The first method called the splitting makes uses of the power spectrum of the interferograms to split the signals into high and low frequency, and following a mutually exclusive consecutive processing chain for the two sets. This approach has resulted in greater density of PSs with decreased phase unwrapping errors. The second approach, called Direct Integration (DI), aims at providing a very fast and straightforward approach to screen wide areas and easily detect active areas. This approach fully exploits the coherent interferograms from the consecutive images provided by Sentinel-1 resulting in a very high sampling density. However, it lacks robustness and its usability lays on the operator experience. The third method, c, La técnica Persistent Scatterer Interferometry (PSI) es un grupo de técnicas avanzadas de radar de apertura sintética interferométrica diferencial (SAR) que se utiliza para medir y monitorear losmovimientos del terreno. Sentinel-1 ha mejorado sensiblemente la adquisición de datos y, en comparación con los sensores SAR anteriores, ha aumentado considerablemente el potencial uso de la interferometría diferencial SAR y del PSI para medir y monitorizar desplazamientos del terreno. El efecto de la atmósfera sobre la fase interferométrica y la naturaleza ambigua de esta son dos cuestiones críticas de InSAR. Además, la baja densidad de Persistent Scatterer (PSs) en áreas no urbanas, es otro tema crítico que ha inspirado el desarrollo de enfoques alternativos y el refinamiento de las cadenas PS existentes. Junto con los esfuerzos por desarrollar métodos para mitigar los tres problemas antes mencionados, el trabajo presentado en esta tesis también aborda la presencia de una nueva señal en interferogramas multilooked que no puede explicarse por cambios de ruido, atmosféricos o topográficos de la superficie terrestre. Esta tesis describe un método para la estimación de la fase atmosférica utilizando datos meteorológicos adquiridos in-situ y tres aproximaciones diferentes basadas en datos Sentinel-1 para obtener mapas de deformación del terreno. Estos enfoques tienen como objetivo explotar los interferogramas altamente coherentes proporcionados por Sentinel-1 gracias a su corto tiempo de revisita. El primer método llamado división hace uso de filtros en el dominico frecuencial de los interferogramas para dividir las señales en alta y baja frecuencia, y siguiendo una cadena de procesamiento consecutiva independiente para cada clase. Este enfoque ha dado como resultado una mejora substancial de PS minimizando los errores debidos al desenrollado de fase. El segundo enfoque, llamado Integración Directa (DI), tiene como objetivo proporcionar un enfoque muy rápido y sencillo para exa, Postprint (published version)

Persistent scatterer interferometry (PSI) has been proved to be an advanced Interferometric Synthetic Aperture Radar (InSAR) technique used to measure and monitor terrain deformation. Two of the critical problems with InSAR have been the effect of the refractive atmosphere and decorrelation on the interferometric phases due to long spatial-temporal baseline. The low density of persistent scatterers (PS) in non-urban areas affected by spatial-temporal decoherence more seriously has inspired the development of alternative approaches. Sentinel-1 (S1) has improved the data acquisition throughout, and compared to previous sensors, increased considerably the differential interferometric SAR (DInSAR) and PSI deformation monitoring potential. This paper describes an innovative methodology to process S1 SAR data. Different with PSI, its most original part includes two key processing stages: high and low frequency splitting from wrapped phases, prior to atmospheric filtering, and final direct integration to generate the complete deformation with time series containing linear and nonlinear components. The proposed method has two fundamental advantages compared with traditional PSI approach: the final monitoring results with excellent coverage of coherent points and the generation of active maps even for the areas with serious deformation in short term to break through the inherent limitation of PSI. The effectiveness of the proposed tools is illustrated using a case study located in Catalonia (Spain). This methodology has supposed a definitive step towards the implementation of DInSAR based techniques to support decision makers against geohazards. In this work, the deformation procedures happened in three different areas of the Catalonia (Spain) are presented and analysed. The maximum accumulated subsidence of over – 60 cm induced by mining activity can be detected by proposed methodology with nice coverage from January 2017 to January 2019. These reported cases illustrate how, Peer Reviewed, Postprint (author's final draft)

Persistent scatterer interferometry (PSI) is a group of advanced interferometric synthetic aperture radar (SAR) techniques used to measure and monitor terrain deformation. Sentinel-1 has improved the data acquisition throughout and, compared to previous sensors, increased considerably the differential interferometric SAR (DInSAR) and PSI deformation monitoring potential. The low density of persistent scatterer (PS) in non-urban areas is a critical issue in DInSAR and has inspired the development of alternative approaches and refinement of the PS chains. This paper proposes two different and complementary data-driven procedures to obtain terrain deformation maps. These approaches aim to exploit Sentinel-1 highly coherent interferograms and their short revisit time. The first approach, called direct integration (DI), aims at providing a very fast and straightforward approach to screen-wide areas and easily detects active areas. This approach fully exploits the coherent interferograms from consecutive images provided by Sentinel-1, resulting in a very high sampling density. However, it lacks robustness and its usability lays on the operator experience. The second method, called persistent scatterer interferometry geomatics (PSIG) short temporal baseline, provides a constrained application of the PSIG chain, the CTTC approach to the PSI. It uses short temporal baseline interferograms and does not assume any deformation model for point selection. It is also quite a straightforward approach, which improves the performances of the standard PSIG approach, increasing the PS density and providing robust measurements. The effectiveness of the approaches is illustrated through analyses performed on different test sites., This work has been partially funded by AGAUR, Generalitat de Catalunya, through a grant for the recruitment of early-stage research staff (Ref: FI_B 00741) and through the Consolidated Research Group RSE, “Remote Sensing” (Ref: 2017-SGR-00729). It has been also partially funded by the Spanish Ministry of Economy and Competitiveness through the DEMOS project “Deformation monitoring using Sentinel-1 data” (Ref: CGL2017-83704-P) and by AGAUR., Peer Reviewed, Postprint (published version)

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., This work shows two examples on the use of Sentinel-1 data for monitoring different natural processes, like active geohazards or glacier dynamics in the Patagonia region. Sentinel-1 is a two-satellite constellation, launched by the European Space Agency (ESA), that provides SAR imagery with interferometric capabilities. It is in operation since 2014 and has supposed a significant improvementin the exploitation of these type of data for applications like natural hazards mapping and monitoring. The acquisition policy, that guarantees an acquisition each few days (12 days in Patagonia region) for both ascending and descending trajectories, and the data distribution policy, that allows free access to the images without legal constrains, are the main reasons for this improvement., This work has been partially funded by the Ministry of education and professional training of the Spanish government through the program abroad stages for young researchers José Castillejo (Ref: CAS19/00190) and by the Spanish Ministry of Economy and Competitiveness through the DEMOS project “Deformation monitoring using Sentinel-1 data” (Ref: CGL2017-83704-P), Postprint (published version)

This paper describes a Persistent Scatterer Interferometry procedure for deformation monitoring. Its more original part concerns an approach to estimate the atmospheric phase component. The procedure can be used to monitor deformation areas that are relatively small and are surrounded by stable areas. The proposed procedure is described step by step. The procedure can be applied using SAR data coming from different sensors. However, in this work we discuss results obtained using Sentinel-1 data. A case study is described, where the deformation is caused by water pumping associated with construction works. In this case study, a stack of 78 Sentinel-1 images were analysed. The main part of the paper concerns the analysis of the atmospheric component. A comprehensive characterization of this component is first described, considering the original non-filtered phases. This is followed by the characterization of the residual filtered phases. This analysis highlights the goodness of the proposed procedure. This is further confirmed by the analysis of two deformation time series. The procedure can work with any type of deformation phenomena, provided that its spatial extension is sufficiently small., This work has been partially funded by the Spanish Ministry of Economy and Competitiveness through the DEMOS project “Deformation monitoring using Sentinel-1 data” (Ref: CGL2017-83704-P), This work has been partially funded by the Spanish Ministry of Economy and Competitiveness through the DEMOS project “Deformation monitoring using Sentinel-1 data” (Ref: CGL2017-83704-P), Postprint (published version)

This paper describes the monitoring of the deformation associated to the construction works of a tunnel. The deformation is monitored using a Persistent Scatterer Interferometry technique and Sentinel-1 SAR data. A particular implementation of a PSI technique is described, which makes use of stable areas in the vicinity of the study area. The monitoring results include maps of accumulated deformation, to spatially describe the deformation, and deformation time series to describe the temporal evolution of deformation over the measured points, This work has been partially funded by AGAUR, Generalitat de Catalunya (Catalan Government), through the Consolidated Research Group RSE, “Remote Sensing” (Ref: 2017-SGR-00729)., Postprint (published version)