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Termes IGN > imagerie > image radar > image radar moirée
image radar moiréeSynonyme(s)Interferogramme ;image SAR ;Image rso ;Image radar interférométrique Image par radar à antenne synthétiqueVoir aussi
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Using a fully polarimetric SAR to detect landslide in complex surroundings: Case study of 2015 Shenzhen landslide / Chaoyang Niu in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)
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[article]
Titre : Using a fully polarimetric SAR to detect landslide in complex surroundings: Case study of 2015 Shenzhen landslide Type de document : Article/Communication Auteurs : Chaoyang Niu, Auteur ; Haobo Zhang, Auteur ; Wei Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 56 - 67 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] décomposition d'image
[Termes IGN] détection de changement
[Termes IGN] effondrement de terrain
[Termes IGN] image radar moirée
[Termes IGN] mouvement de terrain
[Termes IGN] polarimétrie radar
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] ShenzhenRésumé : (auteur) Synthetic aperture radar (SAR) polarimetry has demonstrated high efficiency in the detection of landslides in vegetated mountainous areas. In such places, post-landslide soil layers appear to correspond to the typical surface scattering mechanism, which is significantly different from the volume scattering behaviour of the surrounding vegetation. However, a landslide in the complex surroundings of various landforms, involving naked hillslopes, construction fields, bare farmlands, and other such aspects, may not be accurately identified owing to the occurrence of surface scattering behaviours. In order to detect landslides using SAR polarimetry without the limitation of vegetated mountainous areas, we propose a novel method of combining change detection (CD) and an analytic hierarchy process (AHP) based on the Yamaguchi decomposition (YD) to identify landslides while ensuring fewer false alarms. In particular, CD is applied to a pair of pre- and post-event datasets to determine the regions modified by landslides or human activities, and the AHP is performed over the post-event dataset to identify the suspect landslide region characterised by the surface scattering mechanism. Finally, the two results are fused by a logical operation to identify the actual landslide by removing the non-modified surface scattering regions. A case study of the Shenzhen landslide in complex surroundings was considered to verify the performance of the proposed method (CD-AHP). The results indicate that the method could clearly define the main body of the Shenzhen landslide from the city suburbs with a small number of false alarms. Therefore, this method provides a considerable perspective for landslide detection in complex surroundings using SAR polarimetry. Numéro de notice : A2021-207 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.022 Date de publication en ligne : 19/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.022 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97184
in ISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 56 - 67[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021041 SL Revue Centre de documentation Revues en salle Disponible 081-2021043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt A soil texture categorization mapping from empirical and semi-empirical modelling of target parameters of synthetic aperture radar / Shoba Periasamy in Geocarto international, vol 36 n° 5 ([15/03/2021])
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Titre : A soil texture categorization mapping from empirical and semi-empirical modelling of target parameters of synthetic aperture radar Type de document : Article/Communication Auteurs : Shoba Periasamy, Auteur ; Divya Senthil, Auteur ; Ramakrishnan S Shanmugam, Auteur Année de publication : 2021 Article en page(s) : pp 581 - 598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Argile
[Termes IGN] bande C
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] constante diélectrique
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de végétation
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] limon
[Termes IGN] polarisation croisée
[Termes IGN] rugosité du sol
[Termes IGN] sable
[Termes IGN] texture du solRésumé : (auteur) The present study investigates the potential of synthetic aperture radar in demonstrating the relative percentage of sand, silt and clay content in the soil. The contribution of vegetation and topography in the backscattering coefficient has been significantly reduced by employing the terrain correction model, dual polarized SAR vegetation index and water cloud model. The target parameters namely ‘Soil Roughness (hrms-soil)’ and ‘Dielectric Constant’ (ε′vv−soil ) has arrived from cross-polarization ratio and modified Dubois model. The extracted target parameters are sufficiently correlated with in situ sand (R2 = 0.81) and clay measurements (R2 = 0.78). The relative percentage of silt was mapped by the novel idea of performing the correlation analysis between hrms-soil and ε′vv−soil and thus represented the percentage of silt with reasonable accuracy (R2 = 0.77). From the soil triangle formed with three estimated target parameters, we found that the clay category has shared around 35% of the total area followed by sandy loam (23%). Numéro de notice : A2021-253 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1618924 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1618924 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97276
in Geocarto international > vol 36 n° 5 [15/03/2021] . - pp 581 - 598[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2021051 RAB Revue Centre de documentation En réserve L003 Disponible Cluster-based empirical tropospheric corrections applied to InSAR time series analysis / Kyle Dennis Murray in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)
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Titre : Cluster-based empirical tropospheric corrections applied to InSAR time series analysis Type de document : Article/Communication Auteurs : Kyle Dennis Murray, Auteur ; Rowena B. Lohman, Auteur ; David P. S. Bekaert, Auteur Année de publication : 2021 Article en page(s) : pp 2204 - 2212 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande C
[Termes IGN] bruit atmosphérique
[Termes IGN] classification par nuées dynamiques
[Termes IGN] déformation de la croute terrestre
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] Mexique
[Termes IGN] retard troposphérique
[Termes IGN] série temporelleRésumé : (Auteur) Interferometric synthetic aperture radar (InSAR) allows for mapping of crustal deformation on land with high spatial resolution and precision in areas with high signal-to-noise ratios. Efforts to obtain precise displacement time series globally, however, are severely limited by radar path delays within the troposphere. The tropospheric delay is integrated along the full path length between the ground and the satellite, resulting in correlations between the interferometric phase and elevation that can vary dramatically in both space and time. We evaluate the performance of spatially variable, empirical removal of phase-elevation dependence within SAR interferograms through the use of the K -means clustering algorithm. We apply this method to both synthetic test data, as well as to C-band Sentinel-1a/b time series acquired over a large area in south-central Mexico along the Pacific coast and inland—an area with a large elevation gradient that is of particular interest to researchers studying tectonic- and anthropogenic-related deformation. We show that the clustering algorithm is able to identify cases where tropospheric properties vary across topographic divides, reducing total root mean square (rms) by an average of 50%, as opposed to a spatially constant phase-elevation correction, which has insignificant error reduction. Our approach also reduces tropospheric noise while preserving test signals in synthetic examples. Finally, we show the average standard deviation of the residuals from the best-fit linear rate decreases from approximately 3 to 1.5 cm, which corresponds to a change in the error on the best-fit linear rate from 0.94 to 0.63 cm/yr. Numéro de notice : A2021-215 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3003271 Date de publication en ligne : 30/06/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3003271 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97204
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 3 (March 2021) . - pp 2204 - 2212[article]Compressive Sensing appliqué au traitement de données InSAR pour le suivi de la déformation des zones urbaines / Matthieu Rebmeister in XYZ, n° 166 (mars 2021)
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Titre : Compressive Sensing appliqué au traitement de données InSAR pour le suivi de la déformation des zones urbaines Type de document : Article/Communication Auteurs : Matthieu Rebmeister, Auteur Année de publication : 2021 Article en page(s) : pp 50 - 56 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] acquisition comprimée
[Termes IGN] estimation des paramètres
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] site urbain
[Termes IGN] télédétection en hyperfréquenceRésumé : (Auteur) Les méthodes de traitement du signal, dites de“Compressive Sensing”, ont été développées vers la fin des années 1990 afin de résoudre des systèmes linéaires sous-déterminés. Il est envisageable d’appliquer ces nouveaux algorithmes aux images SAR à cause de leur géométrie d’acquisition particulière. À partir de plusieurs scènes SAR, il est possible de reconstruire la hauteur de chaque pixel possédant au minimum un réflecteur dominant et d’estimer la vitesse de déformation linéaire ainsi que la dilatation thermique des points concernés. Le problème est mal conditionné, ce qui signifie que sa résolution via les algorithmes de Compressive Sensing ne suffit pas à obtenir une solution robuste et plusieurs traitements doivent être effectués pour améliorer le résultat fourni. Un algorithme de traitement complet a été développé et est présenté dans cet article. Afin de tester son efficacité, celui-ci est appliqué sur des données issues du satellite TerraSAR-X. Les résultats montrent que l’estimation est cohérente avec le contexte topographique et urbain. L’algorithme développé permet ainsi de reconstruire en 3D et de suivre le déplacement des zones étudiées. Numéro de notice : A2021-248 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97327
in XYZ > n° 166 (mars 2021) . - pp 50 - 56[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 112-2021011 RAB Revue Centre de documentation En réserve L003 Disponible Damage detection using SAR coherence statistical analysis, application to Beirut, Lebanon / Tamer ElGharbawi in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)
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Titre : Damage detection using SAR coherence statistical analysis, application to Beirut, Lebanon Type de document : Article/Communication Auteurs : Tamer ElGharbawi, Auteur ; Fawzi Zarzoura, Auteur Année de publication : 2021 Article en page(s) : pp 1 - 9 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Beyrouth
[Termes IGN] corrélation
[Termes IGN] décorrélation
[Termes IGN] dommage matériel
[Termes IGN] étude d'impact
[Termes IGN] filtre passe-haut
[Termes IGN] image radar moirée
[Termes IGN] risque technologiqueRésumé : (auteur) Early well-coordinated response during unexpected catastrophes can define the near future of the stricken regions. Beirut city, Lebanon, was one of the unfortunate regions to endure the horrific ordeal of an unexpected explosion that caused thousands of human casualties, billions of dollars’ worth of property damage, and destroyed its main maritime entry point. In this paper, we identify damaged regions and classify their severity using a simple and robust SAR correlation technique. We employ phase coherence and amplitude correlation of a SAR stack to estimate pixels’ damage probability using hypothesis testing. We use a spatial phase filter applied in the frequency domain to improve the estimated coherence by removing the spatial decorrelation component of the total estimated coherence. Using this filter improved the coherence of nearly 44.2% of pixels identified with coherence less than 0.25 in our study area. The estimated damaged regions are presented and compared against a damage map issued by Advanced Rapid Imaging and Analysis (ARIA) which shows an average agreement of 68.3%. Also, a fine agreement was observed when compared to optical satellite images. Numéro de notice : A2021-100 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.00 Date de publication en ligne : 15/01/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.001 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96871
in ISPRS Journal of photogrammetry and remote sensing > vol 173 (March 2021) . - pp 1 - 9[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021031 SL Revue Centre de documentation Revues en salle Disponible 081-2021033 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021032 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Integration of an InSAR and ANN for sinkhole susceptibility mapping: A case study from Kirikkale-Delice (Turkey) / Hakan Nefeslioglu in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)
PermalinkRobust unsupervised small area change detection from SAR imagery using deep learning / Xinzheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)
PermalinkSaline-soil deformation extraction based on an improved time-series InSAR approach / Wei Xiang in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)
PermalinkComprehensive time-series analysis of bridge deformation using differential satellite radar interferometry based on Sentinel-1 / Matthias Schlögl in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)
PermalinkMultiscale CNN with autoencoder regularization joint contextual attention network for SAR image classification / Zitong Wu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)
PermalinkOptimizing flood mapping using multi-synthetic aperture radar images for regions of the lower mekong basin in Vietnam / Vu Anh Tuan in European journal of remote sensing, vol 54 n° 1 (2021)
PermalinkSAR image speckle reduction based on nonconvex hybrid total variation model / Yuli Sun in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)
PermalinkSpruce budworm tree host species distribution and abundance mapping using multi-temporal Sentinel-1 and Sentinel-2 satellite imagery / Rajeev Bhattarai in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)
PermalinkStudy of systematic bias in measuring surface deformation with SAR interferometry / Homa Ansari in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)
PermalinkTropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning / Maryam Pourshamsi in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)
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