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Three-dimensional deformation monitoring of urban infrastructure by tomographic SAR using multitrack TerraSAR-X data stacks / Sina Montazeri in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 6868 - 6878 Titre : Three-dimensional deformation monitoring of urban infrastructure by tomographic SAR using multitrack TerraSAR-X data stacks Type de document : Article/Communication Auteurs : Sina Montazeri, Auteur ; Xiao Xiang Zhu, Auteur ; Michael Eineder, Auteur ; Richard Bamler, Auteur Année de publication : 2016 Article en page(s) : pp 6868 - 6878 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse comparative [Termes IGN] Berlin [Termes IGN] déformation d'édifice [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] semis de points [Termes IGN] surveillance d'ouvrage [Termes IGN] tomographie radar Résumé : (Auteur) Differential synthetic aperture radar tomography (D-TomoSAR), similar to its conventional counterparts such as differential interferometric SAR and persistent scatterer interferometry, is only capable of capturing 1-D deformation along the satellite's line of sight. In this paper, we propose a method based on L1-norm minimization within local spatial cubes to reconstruct 3-D displacement vectors from TomoSAR point clouds available from at least three different viewing geometries. The methodology is applied on two pairs of cross-heading-combination of ascending and descending-TerraSAR-X (TS-X) spotlight image stacks over the city of Berlin. The linear deformation rate and the amplitude of seasonal deformation are decomposed, and the results from two test sites with remarkable deformation pattern are discussed in detail. The results, to our knowledge, demonstrate the first attempt for motion decomposition using TomoSAR data from multiple viewing geometries. Numéro de notice : A2016-919 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2585741 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2585741 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83322 [article]

Geodetic SAR tomography / Xiao Xiang Zhu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)    

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 18 - 35 Titre : Geodetic SAR tomography Type de document : Article/Communication Auteurs : Xiao Xiang Zhu, Auteur ; Sina Montazeri, Auteur ; Christoph Gisinger, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 18 - 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] positionnement absolu [Termes IGN] semis de points [Termes IGN] tomographie radar Résumé : (auteur) In this paper, we propose a framework referred to as “geodetic synthetic aperture radar (SAR) tomography” that fuses the SAR imaging geodesy and tomographic SAR inversion (TomoSAR) approaches to obtain absolute 3-D positions of a large amount of natural scatterers. The methodology is applied on four very high resolution TerraSAR-X spotlight image stacks acquired over the city of Berlin. Since all the TomoSAR estimates are relative to the same reference point object whose absolute 3-D positions are retrieved by means of stereo SAR, the point clouds reconstructed using data acquired from different viewing angles can be geodetically fused. To assess the accuracy of the position estimates, the resulting absolute shadow-free 3-D TomoSAR point clouds are compared with a digital surface model obtained by airborne LiDAR. It is demonstrated that an absolute positioning accuracy of around 20 cm and a meter-order relative positioning accuracy can be achieved by the proposed framework using TerraSAR-X data. Numéro de notice : A2016-112 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2448686 En ligne : https://doi.org/10.1109/TGRS.2015.2448686 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79987 [article]

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