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Combined InSAR and terrestrial structural monitoring of bridges / Sivasakthy Selvakumaran in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 10 (October 2020) . - pp 7141 - 7153 Titre : Combined InSAR and terrestrial structural monitoring of bridges Type de document : Article/Communication Auteurs : Sivasakthy Selvakumaran, Auteur ; Cristian Rossi, Auteur ; Andrea Marinoni, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 7141 - 7153 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] coin réflecteur [Termes IGN] données multisources [Termes IGN] image radar moirée [Termes IGN] incertitude des données [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] Londres [Termes IGN] pont [Termes IGN] surveillance d'ouvrage [Termes IGN] tachéomètre électronique Résumé : (auteur) This article examines advances in interferometric synthetic aperture radar (InSAR) satellite measurement technologies to understand their relevance, utilization, and limitations for bridge monitoring. Waterloo Bridge is presented as a case study to explore how InSAR data sets can be combined with traditional measurement techniques including sensors installed on the bridge and automated total stations. A novel approach to InSAR bridge monitoring was adopted by the installation of physical reflectors at key points of structural interest on the bridge, in order to supplement the bridge’s own reflection characteristics and ensure that the InSAR measurements could be directly compared and combined with in situ measurements. The interpretation and integration of InSAR data sets with civil infrastructure data are more than a trivial task, and a discussion of uncertainty of measurement data is presented. Finally, a strategy for combining and interpreting varied data from multiple sources to provide useful insights into each of these methods is presented, outlining the practical applications of this data analysis to support wider monitoring strategies. Numéro de notice : A2020-588 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2979961 Date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2979961 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95916 [article]

A novel preunmixing framework for efficient detection of linear mixtures in hyperspectral images / Andrea Marinoni in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4325 - 4333 Titre : A novel preunmixing framework for efficient detection of linear mixtures in hyperspectral images Type de document : Article/Communication Auteurs : Andrea Marinoni, Auteur ; Antonio J. Plaza, Auteur ; Paolo Gamba, Auteur Année de publication : 2017 Article en page(s) : pp 4325 - 4333 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] attribut géomètrique [Termes IGN] classification pixellaire [Termes IGN] combinaison linéaire [Termes IGN] image hyperspectrale [Termes IGN] optimisation (mathématiques) Résumé : (Auteur) In order to provide reliable information about the instantaneous field of view considered in hyperspectral images through spectral unmixing, understanding the kind of mixture that occurs over each pixel plays a crucial role. In this paper, in order to detect nonlinear mixtures, a method for fast identification of linear mixtures is introduced. The proposed method does not need statistical information and performs an a priori test on the spectral linearity of each pixel. It uses standard least squares optimization to achieve estimates of the likelihood of occurrence of linear combinations of endmembers by taking advantage of the geometrical properties of hyperspectral signatures. Experimental results on both real and synthetic data sets show that the aforesaid algorithm is actually able to deliver a reliable and thorough assessment of the kind of mixtures present in the pixels of the scene. Numéro de notice : A2017-494 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2691319 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2691319 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86424 [article]