Non-Local Compressive Sensing Based SAR Tomography

Tomographic SAR (TomoSAR) inversion of urban areas is an inherently sparse reconstruction problem and, hence, can be solved using compressive sensing (CS) algorithms. This paper proposes solutions for two notorious problems in this field: 1) TomoSAR requires a high number of data sets, which makes the technique expensive. However, it can be shown that the number of acquisitions and the signal-to-noise ratio (SNR) can be traded off against each other, because it is asymptotically only the product of the number of acquisitions and SNR that determines the reconstruction quality. We propose to increase SNR by integrating non-local estimation into the inversion and show that a reasonable reconstruction of buildings from only seven interferograms is feasible. 2) CS-based inversion is computationally expensive and therefore barely suitable for large-scale applications. We introduce a new fast and accurate algorithm for solving the non-local L1-L2-minimization problem, central to CS-based reconstruction algorithms. The applicability of the algorithm is demonstrated using simulated data and TerraSAR-X high-resolution spotlight images over an area in Munich, Germany.Comment: 10 page

Time-variable 3D ground displacements from High-Resolution Synthetic Aperture Radar (SAR). Application to La Valette landslide (South French Alps).

International audienceWe apply an image correlation technique to multi-orbit and multi-temporal High-Resolution (HR) SAR data. Image correlation technique has the advantage of providing displacement maps in two directions; e.g. the Line of Sight direction (LoS) and the Azimuth direction. This information, derived from the two modes of data acquisition (ascending and descending), can be combined routinely to infer the three dimensional surface displacement field at different epochs. In this study, a methodology is developed to characterize the displacement pattern of the large La Valette landslide (South French Alps) using TerraSAR-X images acquired in 2010. The results allow mapping the dynamics of different units of the La Valette landslide at high spatial resolution. The study demonstrates the potential of this new application of High Resolution SAR image correlation technique for landslide ground surface deformation monitoring

Satellite SAR interferometric techniques in support to emergency mapping

This paper investigates the potential of Synthetic Aperture Radar (SAR) interferometry in the field of emergency mapping, assessing its suitability for both rapid mapping, aimed at supporting the immediate response phase after a disastrous event, and risk mapping, addressing risk prevention and mitigation activities. The conventional Differential Interferometric SAR technique (DInSAR) and the two currently available multi-temporal interferometric approaches, i.e. Permanent Scatterers (PS) and Small BAseline Subset (SBAS), have been evaluated focusing on the main emergency mapping requirements, namely crisis information product types, availability of optimal input data, requirements in terms of auxiliary data, processing time and expected accuracy. The aforementioned investigations have been carried out exploiting the European Space Agency (ESA) C-band Sentinel-1 mission, characterized by a free, full and open data policy. Therefore, this paper will not assess different SAR sensors and their different technical specifications, e.g. wavelength and space resolution. Representative results are presented and discussed with the aim to describe the possible interferometric product types in specific emergency mapping scenarios

Evaluation of Multi-frequency Synthetic Aperture Radar for Subsurface Archaeological Prospection in Arid Environments

The discovery of the subsurface paleochannels in the Saharan Desert with the 1981 Shuttle Imaging Radar (SIR-A) sensor was hugely significant in the field of synthetic aperture radar (SAR) remote sensing. Although previous studies had indicated the ability of microwaves to penetrate the earth’s surface in arid environments, this was the first applicable instance of subsurface imaging using a spaceborne sensor. And the discovery of the ‘radar rivers’ with associated archaeological evidence in this inhospitable environment proved the existence of an earlier less arid paleoclimate that supported past populations. Since the 1980’s SAR subsurface prospection in arid environments has progressed, albeit primarily in the fields of hydrology and geology, with archaeology being investigated to a lesser extent. Currently there is a lack of standardised methods for data acquisition and processing regarding subsurface imaging, difficulties in image interpretation and insufficient supporting quantitative verification. These barriers keep SAR technology from becoming as integral as other remote sensing techniques in archaeological practice The main objective of this thesis is to undertake a multi-frequency SAR analysis across different site types in arid landscapes to evaluate and enhance techniques for analysing SAR within the context of archaeological subsurface prospection. The analysis and associated fieldwork aim to address the gap in the literature regarding field verification of SAR image interpretation and contribute to the understanding of SAR microwave penetration in arid environments. The results presented in this thesis demonstrate successful subsurface imaging of subtle feature(s) at the site of ‘Uqdat al-Bakrah, Oman with X-band data. Because shorter wavelengths are often ignored due to their limited penetration depths as compared to the C-band or L-band data, the effectiveness of X-band sensors in archaeological prospection at this site is significant. In addition, the associated ground penetrating radar and excavation fieldwork undertaken at ‘Uqdat al-Bakrah confirm the image interpretation and support the quantitative information regarding microwave penetration

Characterizing slope instability kinematics by integrating multi-sensor satellite remote sensing observations

Over the past few decades, the occurrence and intensity of geological hazards, such as landslides, have substantially risen due to various factors, including global climate change, seismic events, rapid urbanization and other anthropogenic activities. Landslide disasters pose a significant risk in both urban and rural areas, resulting in fatalities, infrastructure damages, and economic losses. Nevertheless, conventional ground-based monitoring techniques are often costly, time-consuming, and require considerable resources. Moreover, some landslide incidents occur in remote or hazardous locations, making ground-based observation and field investigation challenging or even impossible. Fortunately, the advancements in spaceborne remote sensing technology have led to the availability of large-scale and high-quality imagery, which can be utilized for various landslide-related applications, including identification, monitoring, analysis, and prediction. This efficient and cost-effective technology allows for remote monitoring and assessment of landslide risks and can significantly contribute to disaster management and mitigation efforts. Consequently, spaceborne remote sensing techniques have become vital for geohazard management in many countries, benefiting society by providing reliable downstream services. However, substantial effort is required to ensure that such benefits are provided. For establishing long-term data archives and reliable analyses, it is essential to maintain consistent and continued use of multi-sensor spaceborne remote sensing techniques. This will enable a more thorough understanding of the physical mechanisms responsible for slope instabilities, leading to better decision-making and development of effective mitigation strategies. Ultimately, this can reduce the impact of landslide hazards on the general public. The present dissertation contributes to this effort from the following perspectives: 1. To obtain a comprehensive understanding of spaceborne remote sensing techniques for landslide monitoring, we integrated multi-sensor methods to monitor the entire life cycle of landslide dynamics. We aimed to comprehend the landslide evolution under complex cascading events by utilizing various spaceborne remote sensing techniques, e.g., the precursory deformation before catastrophic failure, co-failure procedures, and post-failure evolution of slope instability. 2. To address the discrepancies between spaceborne optical and radar imagery, we present a methodology that models four-dimensional (4D) post-failure landslide kinematics using a decaying mathematical model. This approach enables us to represent the stress relaxation for the landslide body dynamics after failure. By employing this methodology, we can overcome the weaknesses of the individual sensor in spaceborne optical and radar imaging. 3. We assessed the effectiveness of a newly designed small dihedral corner reflector for landslide monitoring. The reflector is compatible with both ascending and descending satellite orbits, while it is also suitable for applications with both high-resolution and medium-resolution satellite imagery. Furthermore, although its echoes are not as strong as those of conventional reflectors, the cost of the newly designed reflectors is reduced, with more manageable installation and maintenance. To overcome this limitation, we propose a specific selection strategy based on a probability model to identify the reflectors in satellite images

Very High Resolution Tomographic SAR Inversion for Urban Infrastructure Monitoring — A Sparse and Nonlinear Tour

The topic of this thesis is very high resolution (VHR) tomographic SAR inversion for urban infrastructure monitoring. To this end, SAR tomography and differential SAR tomography are demonstrated using TerraSAR-X spotlight data for providing 3-D and 4-D (spatial-temporal) maps of an entire high rise city area including layover separation and estimation of deformation of the buildings. A compressive sensing based estimator (SL1MMER) tailored to VHR SAR data is developed for tomographic SAR inversion by exploiting the sparsity of the signal. A systematic performance assessment of the algorithm is performed regarding elevation estimation accuracy, super-resolution and robustness. A generalized time warp method is proposed which enables differential SAR tomography to estimate multi-component nonlinear motion. All developed methods are validated with both simulated and extensive processing of large volumes of real data from TerraSAR-X

Monitorización de infraestructuras críticas expuestas a riesgos naturales y antrópicos mediante interferometría radar de satélite

[EN] Synthetic Aperture Radar Interferometry (InSAR) is a remote sensing technique very effective for the measure of smalldisplacements of the Earth’s surface over large areas at a very low cost as compared with conventional geodetictechniques. Advanced InSAR time series algorithms for monitoring and investigating surface displacement on Earth arebased on conventional radar interferometry. These techniques allow us to measure deformation with uncertainties of 1mm/year, interpreting time series of interferometric phases at coherent point scatterers (PS) without the need for humanor special equipment presence on the site. By applying InSAR processing techniques to a series of radar images over thesame region, it is possible to detect line-of-sight (LOS) displacements of infrastructures on the ground and therefore identifyabnormal or excessive movement indicating potential problems requiring detailed ground investigation. A major advantageof this technology is that a single radar image can cover a major area of up to 100 km by 100 km or more as, for example,Sentinel-1 C-band satellites data cover a 250 km wide swath. Therefore, all engineering infrastructures in the area, suchas dams, dikes, bridges, ports, etc. subject to terrain deformation by volcanos, landslides, subsidence due to groundwater,gas, or oil withdrawal could be monitored, reducing operating costs effectively. In this sense, the free and open accessCopernicus Sentinel-1 data with currently up to 6-days revisit time open new opportunities for a near real-time landmonitoring. In addition, the new generation of high-resolution radar imagery acquired by SAR sensors such as TerraSARX,COSMO-SkyMed, and PAZ, and the development of multi-interferogram techniques has enhanced our capabilities inrecent years in using InSAR as deformation monitoring tool. In this paper, we address the applicability of using spaceborneSAR sensors for monitoring infrastructures in geomatics engineering and present several cases studies carried out by ourgroup related to anthropogenic and natural hazards, as well as monitoring of critical infrastructures.[ES] La interferometría radar de apertura sintética (InSAR) es una técnica de teledetección muy eficaz para medir pequeños desplazamientos de la superficie terrestre en grandes áreas a un coste muy pequeño en comparación con las técnicas geodésicas convencionales. Los algoritmos avanzados de series temporales InSAR para monitorizar e investigar el desplazamiento de la superficie terrestre se basan en la interferometría radar convencional. Estas técnicas nos permiten medir la deformación con incertidumbres de un milímetro por año, interpretando series temporales de fases interferométricas en retrodispersores puntuales coherentes (PS) sin necesidad de presencia humana o de equipos especiales en el sitio. Al aplicar técnicas de procesamiento InSAR a una serie de imágenes radar de la misma región, es posible detectar desplazamientos de infraestructuras proyectados en la línea de vista del satélite (line-of-sight o LOS) y, por lo tanto, identificar movimientos anormales o excesivos que indiquen problemas potenciales que requieran una investigación detallada del terreno. Una de las principales ventajas de esta tecnología es que una sola imagen radar puede cubrir un área importante de hasta 100 km por 100 km o más, ya que, por ejemplo, los datos de los satélites de banda C Sentinel-1 cubren una franja de 250 km de ancho. Por lo tanto, todas las infraestructuras civiles de la zona, como presas, diques, puentes, puertos, etc., sujetas a deformaciones del terreno por actividad volcánica, deslizamientos de tierra, hundimientos por extracción de agua subterránea, gas o petróleo, podrían ser monitorizados, reduciendo los costes operativos de manera efectiva. En este sentido, los datos Sentinel-1 de Copernicus, de acceso abierto, con hasta 6 días de tiempo de revisión actual abren nuevas oportunidades para una monitorización terrestre casi en tiempo real. Además, la nueva generación de imágenes radar de alta resolución adquiridas por sensores SAR como TerraSAR-X, COSMOSkyMed y PAZ, y el desarrollo de técnicas multi-interferograma ha mejorado nuestras capacidades en los últimos años en el uso del InSAR como herramienta para el control de deformaciones. En este trabajo se aborda la aplicabilidad del uso de sensores SAR espaciales para la monitorización de infraestructuras civiles en ingeniería geomática y presentamos varios casos de estudio realizados por nuestro grupo relacionados con riesgos naturales y antrópicos, así como de monitorización de infraestructura crítica.ERS-1/2 and Envisat datasets were provided by the European Space Agency (ESA). Sentinel-1A/B data were freely provided by ESA through Copernicus Programme. Data have been processed by DORIS (TUDelft), StaMPS (Andy Hooper), SARPROZ (Copyright (c) 2009-2020 Daniele Perissin), and SNAP (ESA). The satellite orbits are from TUDelft and ESA, as well as from the ESA Quality Control Group of Sentinel-1. Research was supported by [ESA Research and Service Support] for providing hardware resources employed in this work; [Spanish Ministry of Economy, Industry and Competitiveness] under ReMoDams project ESP2017-89344-R (AEI/FEDER, UE); [University of Jaén (Spain)] under PAIUJA-2021/2022 and CEACTEMA; [Junta de Andalucía (Spain)] under RNM-282 research group; [ERDF through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme] within project «POCI-01-0145-FEDER006961»; [National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology)] as part of project UID/EEA/50014/2013; [The Ministry of Education, Youth and Sports from the National Programme of Sustainability (NPU II)] under project «IT4Innovations excellence in science - LQ1602» (Czech Republic); and [Slovak Grant Agency VEGA] under projects No. 2/0100/20Ruiz-Armenteros, A.; Delgado-Blasco, J.; Bakon, M.; Lazecky, M.; Marchamalo-Sacristán, M.; Lamas-Fernández, F.; Ruiz-Constán, A.... (2021). Monitoring critical infrastructure exposed to anthropogenic and natural hazards using satellite radar interferometry. En Proceedings 3rd Congress in Geomatics Engineering. Editorial Universitat Politècnica de València. 137-146. https://doi.org/10.4995/CiGeo2021.2021.12736OCS13714

Interferometric Synthetic Aperture RADAR and Radargrammetry towards the Categorization of Building Changes

The purpose of this work is the investigation of SAR techniques relying on multi image acquisition for fully automatic and rapid change detection analysis at building level. In particular, the benefits and limitations of a complementary use of two specific SAR techniques, InSAR and radargrammetry, in an emergency context are examined in term of quickness, globality and accuracy. The analysis is performed using spaceborne SAR data

Landslide mapping and monitoring by using radar and optical remote sensing: examples from the EC-FP7 project SAFER

This paper focuses on the Landslide Thematic services of the EU-funded FP7-SPACE project SAFER (Services and Applications For Emergency Response) for inventory mapping, monitoring and rapid mapping by using Earth Observation (EO). We exploited satellite Interferometric Synthetic Aperture Radar (InSAR) and Object-Based Image Analysis (OBIA), and discuss example applications in South Tyrol and Abruzzo (Italy), Lower Austria (Austria), Lubietova (Slovakia) and the Kaohsiung County (Taiwan). These case studies showcase the significance of radar and optical EO data, InSAR and OBIA methods for landslide mapping and monitoring in different geological environments and during all phases of emergency management: mitigation, preparedness, crisis and recovery