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

Approches tomographiques structurelles pour l'analyse du milieu urbain par tomographie SAR THR : TomoSAR

SAR tomography consists in exploiting multiple images from the same area acquired from a slightly different angle to retrieve the 3-D distribution of the complex reflectivity on the ground. As the transmitted waves are coherent, the desired spatial information (along with the vertical axis) is coded in the phase of the pixels. Many methods have been proposed to retrieve this information in the past years. However, the natural redundancies of the scene are generally not exploited to improve the tomographic estimation step. This Ph.D. presents new approaches to regularize the estimated reflectivity density obtained through SAR tomography by exploiting the urban geometrical structures.La tomographie SAR exploite plusieurs acquisitions d'une même zone acquises d'un point de vue légerement différent pour reconstruire la densité complexe de réflectivité au sol. Cette technique d'imagerie s'appuyant sur l'émission et la réception d'ondes électromagnétiques cohérentes, les données analysées sont complexes et l'information spatiale manquante (selon la verticale) est codée dans la phase. De nombreuse méthodes ont pu être proposées pour retrouver cette information. L'utilisation des redondances naturelles à certains milieux n'est toutefois généralement pas exploitée pour améliorer l'estimation tomographique. Cette thèse propose d'utiliser l'information structurelle propre aux structures urbaines pour régulariser les densités de réflecteurs obtenues par cette technique

First Prismatic Building Model Reconstruction from TomoSAR Points Clouds

This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR) point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007) and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce) the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center) in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR

Investigation of Sea Ice Using Multiple Synthetic Aperture Radar Acquisitions

The papers of this thesis are not available in Munin. Paper I: Yitayew, T. G., Ferro-Famil, L., Eltoft, T. & Tebaldini, S. (2017). Tomographic imaging of fjord ice using a very high resolution ground-based SAR system. Available in IEEE Transactions on Geoscience and Remote Sensing, 55 (2):698-714. Paper II: Yitayew, T. G., Ferro-Famil, L., Eltoft, T. & Tebaldini, S. (2017). Lake and fjord ice imaging using a multifrequency ground-based tomographic SAR system. Available in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(10):4457-4468. Paper III: Yitayew, T. G., Divine, D. V., Dierking, W., Eltoft, T., Ferro-Famil, L., Rosel, A. & Negrel, J. Validation of Sea ice Topographic Heights Derived from TanDEMX Interferometric SAR Data with Results from Laser Profiler and Photogrammetry. (Manuscript).The thesis investigates imaging in the vertical direction of different types of ice in the arctic using synthetic aperture radar (SAR) tomography and SAR interferometry. In the first part, the magnitude and the positions of the dominant scattering contributions within snow covered fjord and lake ice layers are effectively identified by using a very high resolution ground-based tomographic SAR system. Datasets collected at multiple frequencies and polarizations over two test sites in Tromsø area, northern Norway, are used for characterizing the three-dimensional response of snow and ice. The presented experimental results helped to improve our understanding of the interaction between radar waves and snow and ice layers. The reconstructed radar responses are also used for estimating the refractive indices and the vertical positions of the different sub-layers of snow and ice. The second part of the thesis deals with the retrieval of the surface topography of multi-year sea ice using SAR interferometry. Satellite acquisitions from TanDEM-X over the Svalbard area are used for analysis. The retrieved surface height is validated by using overlapping helicopter-based stereo camera and laser profiler measurements, and a very good agreement has been found. The work contributes to an improved understanding regarding the potential of SAR tomography for imaging the vertical scattering distribution of snow and ice layers, and for studying the influence of both sensor parameters such as its frequency and polarization and scene properties such as layer stratification, air bubbles and small-scale roughness of the interfaces on snow and ice backscattered signal. Moreover, the presented results reveal the potential of SAR interferometry for retrieving the surface topography of sea ice

Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version

Buildings Detection in VHR SAR Images Using Fully Convolution Neural Networks

This paper addresses the highly challenging problem of automatically detecting man-made structures especially buildings in very high resolution (VHR) synthetic aperture radar (SAR) images. In this context, the paper has two major contributions: Firstly, it presents a novel and generic workflow that initially classifies the spaceborne TomoSAR point clouds $-$ generated by processing VHR SAR image stacks using advanced interferometric techniques known as SAR tomography (TomoSAR) $-$ into buildings and non-buildings with the aid of auxiliary information (i.e., either using openly available 2-D building footprints or adopting an optical image classification scheme) and later back project the extracted building points onto the SAR imaging coordinates to produce automatic large-scale benchmark labelled (buildings/non-buildings) SAR datasets. Secondly, these labelled datasets (i.e., building masks) have been utilized to construct and train the state-of-the-art deep Fully Convolution Neural Networks with an additional Conditional Random Field represented as a Recurrent Neural Network to detect building regions in a single VHR SAR image. Such a cascaded formation has been successfully employed in computer vision and remote sensing fields for optical image classification but, to our knowledge, has not been applied to SAR images. The results of the building detection are illustrated and validated over a TerraSAR-X VHR spotlight SAR image covering approximately 39 km$^2$ $-$ almost the whole city of Berlin $-$ with mean pixel accuracies of around 93.84%Comment: Accepted publication in IEEE TGR

Contribution to ground-based and UAV SAR systems for Earth observation

Mankind's way of life is the main driver of a planetary-scale change that is marked by the growing of human population's demand of energy, food, goods, services and information. As a result, it have emerged new ecological, economical, social and geopolitical concerns. In this scenario, SAR remote sensing is a potential tool that provides unique information about the Earth's properties and processes that can be used to solve societal challenges of local and global dimension. SARs, which are coherent systems that are able to provide high resolution images with weather independence, represent a suitable alternative for EO with diverse applications. Some examples of SAR application areas are topography (DEM generation with interferometry), agriculture (crop classification or soil moisture), or geology (monitoring surface deformation). In this framework, the encompassing objective of the present doctoral work has been part of the implementation and the subsequent evaluation of capabilities of two X-band SAR sensors. On the one hand, the RISKSAR-X radar designed to be operated at ground to monitor small-scale areas of observation and, on the other, the ARBRES-X sensor designed to be integrated into small UAVs. Despite its inherently dissimilar conception, the concurrence of both sensors has been evidenced along this manuscript. By taking advantage of the similarities between them, it has been possible to analogously assess both sensors to obtain conclusions. In this context, the common link has been the development of the polarimetric OtF operation mode of the RISKSAR-X, allowing this sensor to be operated equivalently to the ARBRES-X. Regarding the RISKSAR-X SAR sensor, several hardware contributions have been developed during part of this Ph.D. with the aim of improving the system performance. By endowing the system with the capability to operate in the fully polarimetric OtF acquisition mode, the relative long scanning time has been reduced. It is of great interest since the measured scatterers that present a short term variable reflectivity during the scanning time, such as moving vegetation, may degrade the extracted parameters from the retrieved data and the SAR image reconstruction. During this doctoral activity, it has been studied the image blurring, the decorrelation and the coherence degradation introduced by this effect. Furthermore, a new term in the differential interferometric coherence that takes into account the image blurring has been introduced. Concerning the ARBRES-X SAR system, one of the main objectives pursued during this Ph.D. has been the integration of the sensor into a small UAV MP overcoming restrictions of weight, size and aerodynamics of the platform. The use of this type of platforms is expected to open up new possibilities in airborne SAR remote sensing, since it offers much more versatility than the commonly used fixed wings UAVs. Different innovative flight strategies with this type of platforms have been assessed and some preliminary results have been obtained with the use of the ARBRES-X SAR system. During the course of the present doctoral work, much effort has been devoted to achieve the first experimental repeat-pass interfereometric results obtained with the UAV MP together with the ARBRES-X. Moreover, the sensor has been endowed with fully polarimetric capabilities by applying the improvements developed to the RISKSAR-X radar, which is another example of the duality between both systems. Finally, a vertical and a semicircular aperture have been successfully performed obtaining SLC images of the scenario, which envisages the capability of the UAV MP to perform tomographic images and complete circular apertures in the future. In conclusion, the UAV MP is a promising platform that opens new potentials for several applications, such as repeat-pass interferometry or differential tomography imaging with the realization of almost arbitrary trajectories.El mode de viure de la humanitat és el principal motor d'un canvi a escala planetària que està marcat per la creixent demanda d'energia, d'aliment, de béns, de serveis i d'informació de les poblacions humanes. Com a resultat, han sorgit noves inquietuds ecològiques, econòmiques, socials i geopolítiques. En aquest escenari, la detecció remota SAR és una eina potencial que proporciona informació única sobre les propietats i processos de la Terra que es pot utilitzar per resoldre reptes socials de dimensió local i global. Els SARs, que són sistemes coherents que poden proporcionar imatges d'alta resolució amb independència del temps, representen una alternativa adequada per a l'observació de la Terra. Alguns exemples d'àrees d'aplicació SAR són la topografia (generació de DEM amb interferometria), l'agricultura (classificació de cultius o humitat del sòl) o la geologia (monitoratge de deformació superficial). En aquest context, l'objectiu general del present doctorat ha estat part de la implementació i posterior avaluació de les capacitats de dos sensors SAR de banda X. D'una banda, el radar RISKSAR-X dissenyat per funcionar a terra i monitoritzar àrees d'observació a petita escala i, d'altra, el sensor ARBRES-X dissenyat per ser integrat en petits UAVs. Malgrat la seva concepció inherentment diferent, la concurrència d'ambdós sensors s'ha evidenciat al llarg d'aquest manuscrit. Aprofitant les similituds entre ells, s'han pogut avaluar de forma anàloga els dos sensors per obtenir conclusions. En aquest sentit, el vincle comú ha estat el desenvolupament del mode de funcionament polimètric OtF del RISKSAR-X, permetent que aquest sensor operi de forma equivalent a l'ARBRES-X. Pel que fa al sensor RISKSAR-X, s'han desenvolupat diverses contribucions hardware durant part d'aquest doctorat amb l'objectiu de millorar el rendiment del sistema. En dotar el sistema de la possibilitat d'operar en el mode d'adquisició totalment polarimètric OtF, s'ha reduït el relatiu llarg temps d'escaneig. Això és de gran interès ja que els blancs mesurats que presenten una reflectivitat variable a curt termini, com ara la vegetació en moviment, poden degradar els paràmetres extrets de les dades recuperades i la reconstrucció d'imatges SAR. Durant aquesta activitat doctoral s'ha estudiat el desenfocat de la imatge, la decorrelació i la degradació de la coherència introduïts per aquest efecte. A més, s'ha introduït un nou terme en la coherència interferomètrica diferencial que té en compte el desenfocat de la imatge. Pel que fa al sistema ARBRES-X, un dels principals objectius perseguits durant aquest doctorat ha estat la integració del sensor en un petit UAV MP superant les restriccions de pes, grandària i aerodinàmica de la plataforma. S'espera que l'ús d'aquest tipus de plataformes obri noves possibilitats en la detecció remota SAR aerotransportada, ja que ofereix molta més versatilitat que els UAV d'ales fixes habituals. S'han avaluat diferents estratègies de vol innovadores amb aquest tipus de plataformes i s'han obtingut resultats preliminars amb l'ús del sistema ARBRES-X. Durant el transcurs del present treball, s'ha dedicat molt esforç a assolir els primers resultats experimentals d'interferometria de múltiple passada obtinguts amb l'UAV MP conjuntament amb l'ARBRES-X. A més, el sensor ha estat dotat de capacitats totalment polarimètriques aplicant les millores desenvolupades al radar RISKSAR-X, el qual constitueix un altre exemple de la dualitat entre ambdós sistemes. Finalment, s'han realitzat amb èxit una apertura vertical i semicircular obtenint imatges SLC de l'escenari, el qual permet preveure la capacitat de l'UAV MP per a realitzar imatges tomogràfiques i apertures circulars completes en el futur. En conclusió, l'UAV MP és una plataforma prometedora que obre nous potencials per a diverses aplicacions, com ara la interferometria de múltiple passada o la tomografia diferencial amb la realització de trajectòries gairebé arbitràries.Postprint (published version

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

Contribution to ground-based and UAV SAR systems for Earth observation

Mankind's way of life is the main driver of a planetary-scale change that is marked by the growing of human population's demand of energy, food, goods, services and information. As a result, it have emerged new ecological, economical, social and geopolitical concerns. In this scenario, SAR remote sensing is a potential tool that provides unique information about the Earth's properties and processes that can be used to solve societal challenges of local and global dimension. SARs, which are coherent systems that are able to provide high resolution images with weather independence, represent a suitable alternative for EO with diverse applications. Some examples of SAR application areas are topography (DEM generation with interferometry), agriculture (crop classification or soil moisture), or geology (monitoring surface deformation). In this framework, the encompassing objective of the present doctoral work has been part of the implementation and the subsequent evaluation of capabilities of two X-band SAR sensors. On the one hand, the RISKSAR-X radar designed to be operated at ground to monitor small-scale areas of observation and, on the other, the ARBRES-X sensor designed to be integrated into small UAVs. Despite its inherently dissimilar conception, the concurrence of both sensors has been evidenced along this manuscript. By taking advantage of the similarities between them, it has been possible to analogously assess both sensors to obtain conclusions. In this context, the common link has been the development of the polarimetric OtF operation mode of the RISKSAR-X, allowing this sensor to be operated equivalently to the ARBRES-X. Regarding the RISKSAR-X SAR sensor, several hardware contributions have been developed during part of this Ph.D. with the aim of improving the system performance. By endowing the system with the capability to operate in the fully polarimetric OtF acquisition mode, the relative long scanning time has been reduced. It is of great interest since the measured scatterers that present a short term variable reflectivity during the scanning time, such as moving vegetation, may degrade the extracted parameters from the retrieved data and the SAR image reconstruction. During this doctoral activity, it has been studied the image blurring, the decorrelation and the coherence degradation introduced by this effect. Furthermore, a new term in the differential interferometric coherence that takes into account the image blurring has been introduced. Concerning the ARBRES-X SAR system, one of the main objectives pursued during this Ph.D. has been the integration of the sensor into a small UAV MP overcoming restrictions of weight, size and aerodynamics of the platform. The use of this type of platforms is expected to open up new possibilities in airborne SAR remote sensing, since it offers much more versatility than the commonly used fixed wings UAVs. Different innovative flight strategies with this type of platforms have been assessed and some preliminary results have been obtained with the use of the ARBRES-X SAR system. During the course of the present doctoral work, much effort has been devoted to achieve the first experimental repeat-pass interfereometric results obtained with the UAV MP together with the ARBRES-X. Moreover, the sensor has been endowed with fully polarimetric capabilities by applying the improvements developed to the RISKSAR-X radar, which is another example of the duality between both systems. Finally, a vertical and a semicircular aperture have been successfully performed obtaining SLC images of the scenario, which envisages the capability of the UAV MP to perform tomographic images and complete circular apertures in the future. In conclusion, the UAV MP is a promising platform that opens new potentials for several applications, such as repeat-pass interferometry or differential tomography imaging with the realization of almost arbitrary trajectories.El mode de viure de la humanitat és el principal motor d'un canvi a escala planetària que està marcat per la creixent demanda d'energia, d'aliment, de béns, de serveis i d'informació de les poblacions humanes. Com a resultat, han sorgit noves inquietuds ecològiques, econòmiques, socials i geopolítiques. En aquest escenari, la detecció remota SAR és una eina potencial que proporciona informació única sobre les propietats i processos de la Terra que es pot utilitzar per resoldre reptes socials de dimensió local i global. Els SARs, que són sistemes coherents que poden proporcionar imatges d'alta resolució amb independència del temps, representen una alternativa adequada per a l'observació de la Terra. Alguns exemples d'àrees d'aplicació SAR són la topografia (generació de DEM amb interferometria), l'agricultura (classificació de cultius o humitat del sòl) o la geologia (monitoratge de deformació superficial). En aquest context, l'objectiu general del present doctorat ha estat part de la implementació i posterior avaluació de les capacitats de dos sensors SAR de banda X. D'una banda, el radar RISKSAR-X dissenyat per funcionar a terra i monitoritzar àrees d'observació a petita escala i, d'altra, el sensor ARBRES-X dissenyat per ser integrat en petits UAVs. Malgrat la seva concepció inherentment diferent, la concurrència d'ambdós sensors s'ha evidenciat al llarg d'aquest manuscrit. Aprofitant les similituds entre ells, s'han pogut avaluar de forma anàloga els dos sensors per obtenir conclusions. En aquest sentit, el vincle comú ha estat el desenvolupament del mode de funcionament polimètric OtF del RISKSAR-X, permetent que aquest sensor operi de forma equivalent a l'ARBRES-X. Pel que fa al sensor RISKSAR-X, s'han desenvolupat diverses contribucions hardware durant part d'aquest doctorat amb l'objectiu de millorar el rendiment del sistema. En dotar el sistema de la possibilitat d'operar en el mode d'adquisició totalment polarimètric OtF, s'ha reduït el relatiu llarg temps d'escaneig. Això és de gran interès ja que els blancs mesurats que presenten una reflectivitat variable a curt termini, com ara la vegetació en moviment, poden degradar els paràmetres extrets de les dades recuperades i la reconstrucció d'imatges SAR. Durant aquesta activitat doctoral s'ha estudiat el desenfocat de la imatge, la decorrelació i la degradació de la coherència introduïts per aquest efecte. A més, s'ha introduït un nou terme en la coherència interferomètrica diferencial que té en compte el desenfocat de la imatge. Pel que fa al sistema ARBRES-X, un dels principals objectius perseguits durant aquest doctorat ha estat la integració del sensor en un petit UAV MP superant les restriccions de pes, grandària i aerodinàmica de la plataforma. S'espera que l'ús d'aquest tipus de plataformes obri noves possibilitats en la detecció remota SAR aerotransportada, ja que ofereix molta més versatilitat que els UAV d'ales fixes habituals. S'han avaluat diferents estratègies de vol innovadores amb aquest tipus de plataformes i s'han obtingut resultats preliminars amb l'ús del sistema ARBRES-X. Durant el transcurs del present treball, s'ha dedicat molt esforç a assolir els primers resultats experimentals d'interferometria de múltiple passada obtinguts amb l'UAV MP conjuntament amb l'ARBRES-X. A més, el sensor ha estat dotat de capacitats totalment polarimètriques aplicant les millores desenvolupades al radar RISKSAR-X, el qual constitueix un altre exemple de la dualitat entre ambdós sistemes. Finalment, s'han realitzat amb èxit una apertura vertical i semicircular obtenint imatges SLC de l'escenari, el qual permet preveure la capacitat de l'UAV MP per a realitzar imatges tomogràfiques i apertures circulars completes en el futur. En conclusió, l'UAV MP és una plataforma prometedora que obre nous potencials per a diverses aplicacions, com ara la interferometria de múltiple passada o la tomografia diferencial amb la realització de trajectòries gairebé arbitràries

Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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