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The 2015 Mw 6.4 Pishan earthquake, China: geodetic modelling inferred from Sentinel-1A TOPS interferometry / Yongsheng Li in Survey review, vol 50 n° 363 (September 2018)  

Public [article]  inSurvey review > vol 50 n° 363 (September 2018) . - pp 522 - 530 Titre : The 2015 Mw 6.4 Pishan earthquake, China: geodetic modelling inferred from Sentinel-1A TOPS interferometry Type de document : Article/Communication Auteurs : Yongsheng Li, Auteur ; Yi Luo, Auteur ; Jingfa Zhang, Auteur ; Wenliang Jiang, Auteur Année de publication : 2018 Article en page(s) : pp 522 - 530 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] déformation de la croute terrestre [Termes IGN] faille géologique [Termes IGN] image Sentinel-SAR [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] modèle géologique [Termes IGN] séisme [Termes IGN] Sinkiang (Chine) Résumé : (Auteur) This study investigates the 3 July 2015 (Mw=6.4) earthquake that affected Pishan County in Xinjiang, China. Using Synthetic Aperture Radar interferometry (InSAR), we mapped the near-field surface displacement of this event to better characterize the seismic source parameters. The inverted results suggest that a conjugate fault system could produce very similar deformation patterns as those observed in both ascending and descending InSAR observations, and the south-dipping fault is selected as the optimal fault responsible for the event. The selected fault was concentrated on a thrust fault with a strike of 112°, a dip of 25° and an average rake angle of 89°. The InSAR analysis reveals a fragmentation of the Western Kunlun north margin fault, and the overall deformation of the seismogenic fault is characterized by thrust motion, which is consistent with the transpressional tectonic characteristics of the major faults in this region. Numéro de notice : A2018-451 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2017.1335381 Date de publication en ligne : 07/06/2017 En ligne : https://doi.org/10.1080/00396265.2017.1335381 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91037 [article]

Fusion of space-borne multi-baseline and multi-frequency interferometric results based on extended Kalman filter to generate high quality DEMs / Xiaojie Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 111 (January 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 111 (January 2016) . - pp 32 – 44 Titre : Fusion of space-borne multi-baseline and multi-frequency interferometric results based on extended Kalman filter to generate high quality DEMs Type de document : Article/Communication Auteurs : Xiaojie Zhang, Auteur ; Qiming Zeng, Auteur ; Jian Jiao, Auteur ; Jingfa Zhang, Auteur Année de publication : 2016 Article en page(s) : pp 32 – 44 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Chine [Termes IGN] distorsion d'image [Termes IGN] filtre de Kalman [Termes IGN] fusion de données [Termes IGN] image Envisat-ASAR [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] modèle numérique de terrain Résumé : (auteur) Repeat-pass Interferometric Synthetic Aperture Radar (InSAR) is a technique that can be used to generate DEMs. But the accuracy of InSAR is greatly limited by geometrical distortions, atmospheric effect, and decorrelations, particularly in mountainous areas, such as western China where no high quality DEM has so far been accomplished. Since each of InSAR DEMs generated using data of different frequencies and baselines has their own advantages and disadvantages, it is therefore very potential to overcome some of the limitations of InSAR by fusing Multi-baseline and Multi-frequency Interferometric Results (MMIRs). This paper proposed a fusion method based on Extended Kalman Filter (EKF), which takes the InSAR-derived DEMs as states in prediction step and the flattened interferograms as observations in control step to generate the final fused DEM. Before the fusion, detection of layover and shadow regions, low-coherence regions and regions with large height error is carried out because MMIRs in these regions are believed to be unreliable and thereafter are excluded. The whole processing flow is tested with TerraSAR-X and Envisat ASAR datasets. Finally, the fused DEM is validated with ASTER GDEM and national standard DEM of China. The results demonstrate that the proposed method is effective even in low coherence areas. Numéro de notice : A2016-039 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.11.005 Date de publication en ligne : 12/12/2015 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.11.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79519 [article]