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Termes IGN > sciences naturelles > physique > traitement d'image > traitement d'image radar > interféromètrie par radar à antenne synthétique
interféromètrie par radar à antenne synthétiqueSynonyme(s)interferometrie par radar a synthese d'ouverture ;Insar Ifsar |
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Detection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM / Jiehua Cai in Engineering Geology, vol 305 (August 2022)
[article]
Titre : Detection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM Type de document : Article/Communication Auteurs : Jiehua Cai, Auteur ; Lu Zhang, Auteur ; Jie Dong, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 106730 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cartographie des risques
[Termes IGN] déformation de surface
[Termes IGN] données lidar
[Termes IGN] données multisources
[Termes IGN] effondrement de terrain
[Termes IGN] géomorphologie
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image optique
[Termes IGN] image Sentinel-SAR
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] MNS lidar
[Termes IGN] MNS SRTM
[Termes IGN] séisme
[Termes IGN] Setchouan (Chine)
[Termes IGN] surveillance géologiqueRésumé : (auteur) On 8th August 2017, a catastrophic Ms. 7.0 earthquake with a focal depth of 20 km struck the Jiuzhaigou County in Sichuan Province, China. It exerted a strong influence on the slope stability within the surrounding areas and triggered numerous secondary geohazards including rockfalls and other co-seismic landslides, which incurred drastic surface changes, and thus can be easily identified from cloud-free high-resolution optical imagery. Most of such landslides became stabilized shortly after the earthquake while others moving very slowly for years. In contrast, some slopes were destabilized without significant surface change into slow-moving landslides, which may pose long-term potential threats to people's life and property. Therefore, it is crucial to accurately identify these slow-moving landslides and regularly monitor their post-seismic activity. In this study, we employed the synthetic aperture radar interferometry (InSAR) techniques to detect and monitor slow-moving landslides after the earthquake in the Jiuzhaigou area, and analyzed the impacts of the earthquake on these landslides through integration of multi-source data (InSAR, Lidar, optical image, and field survey). As a result, 16 slow-moving landslides were detected by InSAR in the Jiuzhaigou area, including several historical landslides. The results of time-series InSAR analyses enabled identification of three kinds of landslide evolution modes affected by the earthquake, i.e. acceleration of deformation of pre-existing landslides, reactivation of dormant landslide, and remobilization of earthquake-triggered landslide. Each mode is supported by detailed analyses of multi-source data. The results demonstrated that satellite InSAR combined with high-resolution Lidar and optical data can provide a cost-effective approach of post-earthquake geohazards detection and monitoring. Numéro de notice : A2022-469 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.enggeo.2022.106730 Date de publication en ligne : 28/05/2022 En ligne : https://doi.org/10.1016/j.enggeo.2022.106730 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100811
in Engineering Geology > vol 305 (August 2022) . - n° 106730[article]PS-InSAR based validated landslide susceptibility modelling: a case study of Ghizer valley, Northern Pakistan / Sajid Hussain in Geocarto international, vol 37 n° 13 ([15/07/2022])
[article]
Titre : PS-InSAR based validated landslide susceptibility modelling: a case study of Ghizer valley, Northern Pakistan Type de document : Article/Communication Auteurs : Sajid Hussain, Auteur ; Sun Hongxing, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 3941 - 3962 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] aléa
[Termes IGN] effondrement de terrain
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] PakistanRésumé : (auteur) Northern Pakistan is a rugged mountainous area that is seismically active, high gradients, disintegrated lithology, and glaciers in the high peaks. District Ghizer lies among the most vulnerable areas and experience landslides every year due to different causative factors. This study has carried out to prepare a detailed landslide inventory and to develop a susceptibility model for the area. The most followed and probabilistic approach, Frequency Ratio (FR) model and a semi-qualitative Analytical Hierarchy Process (AHP) approach were applied to find the correlation between causative factors and mapped landslides. Persistent Scatterer Interferometry (PSI) Interferometric Synthetic Aperture Radar (InSAR) technique was applied to check deformation movement in the susceptible zones of extracted models, which showed the high Line of Sight (LOS) deformation velocity in high susceptible zones of both models. The extracted Landslide Susceptibility Index (LSI) models showed 82.82% and 73.43% of prediction accuracy for FR and AHP method calculated by Area Under Curve (AUC) of Receiver operating characteristic (ROC) method. The models revealed Slope, barrenness, and Geology are the main causative factors of landslide activities in the study area. Finally, both Landslide susceptibility index maps were classified into five susceptibility classes. As the study area is very prone to landslide disasters so these susceptibility models will be helpful to delineate hazardous zones for the medication of future landslides disasters in the area as well as it can be used as a tool in the planning strategies by decision-makers in development projects in the area. Numéro de notice : A2022-589 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1870165 Date de publication en ligne : 11/02/2021 En ligne : https://doi.org/10.1080/10106049.2020.1870165 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101363
in Geocarto international > vol 37 n° 13 [15/07/2022] . - pp 3941 - 3962[article]Validation of a corner reflector installation at Côte d’Azur multi-technique geodetic observatory / Xavier Collilieux in Advances in space research, vol 70 n° 2 (15 July 2022)
[article]
Titre : Validation of a corner reflector installation at Côte d’Azur multi-technique geodetic observatory Type de document : Article/Communication Auteurs : Xavier Collilieux , Auteur ; Clément Courde, Auteur ; Bénédicte Fruneau , Auteur ; Mourad Aimar, Auteur ; Guillaume Schmidt, Auteur ; Isabelle Delprat, Auteur ; Marie-Amélie Defresne, Auteur ; Damien Pesce, Auteur ; Fabien Bergerault, Auteur ; Guy Wöppelmann , Auteur Année de publication : 2022 Projets : Université de Paris / Clerici, Christine Article en page(s) : pp 360 - 370 Note générale : bibliographie
This study contributes to the IdEx Université de Paris ANR-18-IDEX-0001. It was supported by the Programme National GRAM INSAROME of CNRS/INSU with INP and IN2P3 co-funded by CNES but also by BQR-OCA.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] coin réflecteur
[Termes IGN] constellation Sentinel
[Termes IGN] Global Geodetic Observing System
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] observatoire astronomiqueRésumé : (auteur) We present the procedure we followed to design an artificial corner reflector (CR) at the Calern site of Côte d’Azur Observatory (France). Although still few in number, such reflectors are an integral part of the Global Geodetic Observing System (GGOS) infrastructure. They can be used as a stable radar target in SAR images to connect local InSAR deformation maps to the global Terrestrial Reference Frame and for SAR absolute determination. During a test phase, the orientation of the CR was changed in order to be aligned toward all possible orbits of Sentinel-1A/1B satellites. On the different SAR images, the CR exhibits a high backscattering signal, and provides a Signal-to-Clutter Ratio larger than 26 dB. Since December 2018, the CR is specifically oriented toward the relative orbit 88. It is clearly detected as a PS in our InSAR analyses and as expected, the standard deviation of displacement measured on the CR is lower than on surrounding PS. A first local survey was performed to locate precisely this CR with respect to the existing geodetic instruments and annual campaigns have been carried out since then to insure its stability over time. Numéro de notice : A2022-337 Affiliation des auteurs : ENSG+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2022.04.050 Date de publication en ligne : 29/04/2022 En ligne : https://doi.org/10.1016/j.asr.2022.04.050 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100694
in Advances in space research > vol 70 n° 2 (15 July 2022) . - pp 360 - 370[article]Fusion of GNSS and InSAR time series using the improved STRE model: applications to the San Francisco bay area and Southern California / Huineng Yan in Journal of geodesy, vol 96 n° 7 (July 2022)
[article]
Titre : Fusion of GNSS and InSAR time series using the improved STRE model: applications to the San Francisco bay area and Southern California Type de document : Article/Communication Auteurs : Huineng Yan, Auteur ; Wujiao Dai, Auteur ; Lei Xie, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] déformation de la croute terrestre
[Termes IGN] données GNSS
[Termes IGN] faille géologique
[Termes IGN] filtrage spatiotemporel
[Termes IGN] fusion de données
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] modélisation spatiale
[Termes IGN] rééchantillonnage
[Termes IGN] série temporelleRésumé : (auteur) The spatio-temporal random effects (STRE) model is a classic dynamic filtering model, which can be used to fuse GNSS and InSAR deformation data. The STRE model uses a certain time span of high spatial resolution Interferometric Synthetic Aperture Radar (InSAR) time series data to establish a spatial model and then obtain a deformation result with high spatio-temporal resolution through the state transition equation recursively in time domain. Combined with the Kalman filter, the STRE model is continuously updated and modified in time domain to obtain higher accuracy result. However, it relies heavily on the prior information and personal experience to establish an accurate spatial model. To the authors' knowledge, there are no publications which use the STRE model with multiple sets of different deformation monitoring data to verify its applicability and reliability. Here, we propose an improved STRE model to automatically establish accurate spatial model to improve the STRE model, then apply it to the fusion of GNSS and InSAR deformation data in the San Francisco Bay Area covering approximately 6000 km2 and in Southern California covering approximately 100,000 km2. Our experimental results show that the improved STRE model can achieve good fusion effects in both study areas. For internal inspection, the average error RMS values in the two regions are 0.13 mm and 0.06 mm for InSAR and 2.4 and 2.8 mm for GNSS, respectively; for Jackknife cross-validation, the average error RMS values are 6.0 and 1.3 mm for InSAR and 4.3 and 4.8 mm for GNSS in the two regions, respectively. We find that the deformation rate calculated from the fusion results is highly consistent with the existing studies, the significant difference in the deformation rate on both sides of the major faults in the two regions can be clearly seen, and the area with abnormal deformation rate corresponds well to the actual situation. These results indicate that the improved STRE model can reduce the reliance on prior information and personal experience, realize the effective fusion of GNSS and InSAR deformation data in different regions, and also has the advantages of high accuracy and strong applicability. Numéro de notice : A2022-553 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/s00190-022-01636-7 Date de publication en ligne : 05/07/2022 En ligne : https://doi.org/10.1007/s00190-022-01636-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101165
in Journal of geodesy > vol 96 n° 7 (July 2022) . - n° 47[article]PolGAN: A deep-learning-based unsupervised forest height estimation based on the synergy of PolInSAR and LiDAR data / Qi Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)
[article]
Titre : PolGAN: A deep-learning-based unsupervised forest height estimation based on the synergy of PolInSAR and LiDAR data Type de document : Article/Communication Auteurs : Qi Zhang, Auteur ; Linlin Ge, Auteur ; Scott Hensley, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 123 - 139 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse discriminante
[Termes IGN] apprentissage non-dirigé
[Termes IGN] apprentissage profond
[Termes IGN] bande L
[Termes IGN] données lidar
[Termes IGN] forêt boréale
[Termes IGN] forêt tropicale
[Termes IGN] Global Ecosystem Dynamics Investigation lidar
[Termes IGN] hauteur de la végétation
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] polarimétrie radar
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] réseau antagoniste génératif
[Termes IGN] semis de pointsRésumé : (auteur) This paper describes a deep-learning-based unsupervised forest height estimation method based on the synergy of the high-resolution L-band repeat-pass Polarimetric Synthetic Aperture Radar Interferometry (PolInSAR) and low-resolution large-footprint full-waveform Light Detection and Ranging (LiDAR) data. Unlike traditional PolInSAR-based methods, the proposed method reformulates the forest height inversion as a pan-sharpening process between the low-resolution LiDAR height and the high-resolution PolSAR and PolInSAR features. A tailored Generative Adversarial Network (GAN) called PolGAN with one generator and dual (coherence and spatial) discriminators is proposed to this end, where a progressive pan-sharpening strategy underpins the generator to overcome the significant difference between spatial resolutions of LiDAR and SAR-related inputs. Forest height estimates with high spatial resolution and vertical accuracy are generated through a continuous generative and adversarial process. UAVSAR PolInSAR and LVIS LiDAR data collected over tropical and boreal forest sites are used for experiments. Ablation study is conducted over the boreal site evidencing the superiority of the progressive generator with dual discriminators employed in PolGAN (RMSE: 1.21 m) in comparison with the standard generator with dual discriminators (RMSE: 2.43 m) and the progressive generator with a single coherence (RMSE: 2.74 m) or spatial discriminator (RMSE: 5.87 m). Besides that, by reducing the dependency on theoretical models and utilizing the shape, texture, and spatial information embedded in the high-spatial-resolution features, the PolGAN method achieves an RMSE of 2.37 m over the tropical forest site, which is much more accurate than the traditional PolInSAR-based Kapok method (RMSE: 8.02 m). Numéro de notice : A2022-195 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.02.008 Date de publication en ligne : 17/02/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.02.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99962
in ISPRS Journal of photogrammetry and remote sensing > vol 186 (April 2022) . - pp 123 - 139[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2022041 SL Revue Centre de documentation Revues en salle Disponible 081-2022043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2022042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Modélisation du lien entre éruptions et glissements de flancs au Piton de la Fournaise / Quentin Dumont (2022)PermalinkLand subsidence in Beijing’s sub-administrative center and its relationship with urban expansion inferred from Sentinel-1/2 observations / Jin Cao in Canadian journal of remote sensing, vol 47 n° 6 ([01/11/2021])PermalinkPersistent scatterer interferometry for Pettimudi (India) landslide monitoring using Sentinel-1A images / Hari Shankar in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)PermalinkEvaluation of methods for connecting InSAR to a terrestrial reference frame in the Latrobe Valley, Australia / P.J. Johnston in Journal of geodesy, vol 95 n° 10 (October 2021)PermalinkInvestigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations / Caglar Bayik in Natural Hazards, vol 109 n° 1 (October 2021)PermalinkOrbit error removal in InSAR/MTInSAR with a patch-based polynomial model / Yanan Du in International journal of applied Earth observation and geoinformation, vol 102 (October 2021)PermalinkEstimation of surface deformation due to Pasni earthquake using RADAR interferometry / Muhammad Ali in Geocarto international, vol 36 n° 14 ([01/08/2021])PermalinkGlacier elevation change in the Western Qilian mountains as observed by TerraSAR-X/TanDEM-X images / Qibing Zhang in Geocarto international, vol 36 n° 12 ([01/07/2021])PermalinkRefinement of interferometric SAR parameters using digital terrain model as an external reference / Jyunpei Uemoto in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)PermalinkDetecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network / Nantheera Anantrasirichai in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkA 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])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)PermalinkForest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques / Yue Huang in Remote sensing, Vol 13 n° 3 (February 2021)PermalinkReclaimed-airport surface-deformation monitoring by improved permanent-scatterer interferometric synthetic-aperture radar: a case study of Shenzhen Bao'an international airport, China / Lu Miao in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 2 (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)PermalinkFlood mapping from radar remote sensing using automated image classification techniques / Lisa Landuyt (2021)PermalinkRemote sensing and GIS / Basudeb Bhatta (2021)PermalinkPermalinkGeostatistical analysis and mitigation of the atmospheric phase screens in Ku-band terrestrial radar interferometric observations of an alpine glacier / Simone Baffelli in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)PermalinkCombined InSAR and terrestrial structural monitoring of bridges / Sivasakthy Selvakumaran in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)PermalinkThe 2018–2019 seismo-volcanic crisis east of Mayotte, Comoros islands: seismicity and ground deformation markers of an exceptional submarine eruption / Anne Lemoine in Geophysical journal international, vol 223 n° 1 (October 2020)PermalinkIlluminating the spatio-temporal evolution of the 2008–2009 Qaidam earthquake sequence with the joint use of Insar time series and teleseismic data / Simon Daout in Remote sensing, vol 12 n° 17 (September-1 2020)PermalinkDigital terrain, surface, and canopy height models from InSAR backscatter-height histograms / Gustavo H.X. Shiroma in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkFusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)PermalinkMonitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys / Ashutosh Tiwari in Geocarto international, vol 35 n° 5 ([01/04/2020])PermalinkLe sol s'affaisse, l'eau monte [Delta du Gange-Brahmapoutre-Meghna] / Marielle Mayo in Géomètre, n° 2179 (avril 2020)PermalinkA sequential Monte Carlo framework for noise filtering in InSAR time series / Mehdi Khaki in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)PermalinkComplex deformation at shallow depth during the 30 October 2016 Mw6.5 Norcia earthquake: interferencebetween tectonic and gravity processes? / Arthur Delorme in Tectonics, vol 39 n° 2 (February 2020)PermalinkMapping precipitable water vapor time series from Sentinel-1 interferometric SAR / Pedro Mateus in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkRadial interpolation of GPS and leveling data of ground deformation in a resurgent caldera: application to Campi Flegrei (Italy) / Andrea Bevilacqua in Journal of geodesy, vol 94 n°2 (February 2020)PermalinkSome thoughts on measuring earthquake deformation using optical imagery / Min Huang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkPermalinkIdentification of alpine glaciers in the central Himalayas using fully polarimetric L-Band SAR data / Guo-Hui Yao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)PermalinkRadar interferometry of unstable slopes / Theeba Raveendran (2020)PermalinkPermalinkOn the value of corner reflectors and surface models in InSAR precise point positioning / Mengshi Yang in ISPRS Journal of photogrammetry and remote sensing, Vol 158 (December 2019)PermalinkA temporal phase coherence estimation algorithm and its application on DInSAR pixel selection / Feng Zhao in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)PermalinkAn analytic expression for the phase noise of the goldstein–werner filter / Scott Hensley in IEEE Transactions on geoscience and remote sensing, vol 57 n° 9 (September 2019)PermalinkEvolution des techniques topographiques à EDF depuis les 40 dernières années / Rémy Boudon in XYZ, n° 160 (septembre 2019)PermalinkThe Parallel SBAS approach for Sentinel-1 interferometric wide swath deformation time-series generation: algorithm description and products quality assessment / Michele Manunta in IEEE Transactions on geoscience and remote sensing, vol 57 n° 9 (September 2019)PermalinkIntegration of corner reflectors for the monitoring of mountain glacier areas with Sentinel-1 time series / Matthias Jauvin in Remote sensing, vol 11 n° 8 (August 2019)PermalinkHigh-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland / Karina Wilgan in Journal of geodesy, vol 93 n°6 (June 2019)PermalinkObservation et suivi de déformations de surface d'origine anthropique par interférométrie radar satellitaire / Daniel Raucoules in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)PermalinkPrincipes de l'interférométrie d'images radar pour la mesure de la topographie et des déplacements du sol et avancées récentes / Elisabeth Simonetto in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)PermalinkGeneration of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar / Yang Lei in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)PermalinkTanDEM-X digital surface models in boreal forest above-ground biomass change detection / Kirsi Karila in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)PermalinkAnalyse de la déformation récente dans le Grand Tunis par interférométrie radar SAR / Anis Chaabani (2019)PermalinkCaractérisation des déplacements liés aux coulées de lave au Piton de la Fournaise à partir de données InSAR / Alexis Hrysiewicz (2019)PermalinkCartographie des déformations sur le site de colocalisation de Grasse par méthode INSAR / Isabelle Delprat (2019)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkVariabilité du niveau marin relatif le long du littoral de Brest (France) par combinaison de méthodes géodésiques spatiales (altimétrie radar, InSAR et GPS) / Cyril Poitevin (2019)PermalinkAtmospheric artifacts correction with a covariance-weighted linear model over mountainous regions / Zhongbo Hu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkLong-term land deformation monitoring using quasi-persistent scatterer (Q-PS) technique observed by sentinel-1A : case study Kelok Sembilan / Pakhrur Razi in Advances in Remote Sensing, vol 7 n° 4 (December 2018)PermalinkSeparating the influence of vegetation changes in polarimetric differential SAR interferometry / Virginia Brancato in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkInvestigation of the success of monitoring slow motion landslides using Persistent Scatterer Interferometry and GNSS methods / K.O. Hastaoglu in Survey review, vol 50 n° 363 (September 2018)PermalinkThe 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)PermalinkError-regulated multi-pass DInSAR analysis for landslide risk assessment / Jung Rack Kim in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 4 (April 2018)PermalinkActive tectonics of the onshore Hengchun Fault using UAS DSM combined with ALOS PS-InSAR time series (Southern Taiwan) / Benoit Deffontaines in Natural Hazards and Earth System Sciences, vol 18 n° 3 ([01/03/2018])PermalinkCartographier le relief sous les forêts, et le substrat sous les déserts de sable : les attentes de la mission radar Biomass / Laurent Polidori in XYZ, n° 154 (mars - mai 2018)PermalinkPermalinkCartographie des déformations de surface sur l’île de Taiwan par interférométrie RADAR Sentinel-1 / Miloud Fekaouni (2018)PermalinkEtude préalable à l'installation d'un coin radar sur le site de co-localisation de Calern / Guillaume Schmidt (2018)PermalinkPotential and limits of Sentinel-1 data for small alpine glaciers monitoring / Matthias Jauvin (2018)PermalinkUtilisation des réseaux de capteurs Géocubes pour la mesure de déformation des volcans en temps réel par GNSS / Mohamed-Amjad Lasri (2018)PermalinkVector-based approach for combining ascending and descending persistent scatterers interferometric point measurements / Michael Foumelis in Geocarto international, vol 33 n° 1 (January 2018)PermalinkA wavelet decomposition and polynomial fitting-based method for the estimation of time-varying residual motion error in airborne interferometric SAR / Hai Qiang Fu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkInSAR data for geohazard assessment in UNESCO World Heritage sites: state-of-the-art and perspectives in the Copernicus era / Deodato Tapete in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)PermalinkInSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico / Pascal Castellazzi in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)PermalinkSmall reflectors for ground motion monitoring with InSAR / Prabu Dheenathayalan in IEEE Transactions on geoscience and remote sensing, vol 55 n° 12 (December 2017)PermalinkShallow geological structures triggered during the Mw 6.4 Meinong earthquake, southwestern Taiwan / Maryline Le Béon in Terrestrial Atmospheric Oceanic sciences journal, vol 28 n° 5 (October 2017)PermalinkTectonic and anthropogenic deformation at the Cerro Prieto geothermal step-over revealed by sentinel-1A InSAR / Xiaohua Xu in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)PermalinkRobust object-based multipass InSAR deformation reconstruction / Jian Kang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)PermalinkDisplacement monitoring and modelling of a high-speed railway bridge using C-band Sentinel-1 data / Qihuan Huang in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)PermalinkAn unsupervised two-stage clustering approach for forest structure classification based on X-band InSAR data — A case study in complex temperate forest stands / Sahra Abdullahi in International journal of applied Earth observation and geoinformation, vol 57 (May 2017)PermalinkSentinel-1 interferometric SAR mapping of precipitable water vapor over a country-spanning area / Pedro Mateus in IEEE Transactions on geoscience and remote sensing, vol 55 n° 5 (May 2017)PermalinkEstimation of 3-D surface displacement based on InSAR and deformation modeling / Jun Hu in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)PermalinkPermalinkMise en place de l’utilisation d’instruments de mesure 3D dans le cadre d’auscultations de barrages / Cyril Cadiou (2017)PermalinkPresent-day deformation in Taiwan mountain belt as monitored by InSAR / Bénédicte Fruneau (2017)PermalinkTélédétection pour l'observation des surfaces continentales, Volume 2. Observation des surfaces continentales par télédétection micro-onde / Nicolas Baghdadi (2017)PermalinkDetection of ground surface deformation caused by the 2016 Kumamoto earthquake by InSAR using ALOS-2 data / Basara Miyahara in Bulletin of the GeoSpatial Information authority of Japan, vol 64 (December 2016)PermalinkUse of a GPS-derived troposphere model to improve InSAR deformation estimates in the San Gabriel Valley, California / Nicolas Houlié in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkInvestigation of ionospheric effects on SAR Interferometry (InSAR): A case study of Hong Kong / Wu Zhu in Advances in space research, vol 58 n° 4 (August 2016)PermalinkAtmospheric correction in time-series SAR interferometry for land surface deformation mapping : A case study of Taiyuan, China / Wei Tang in Advances in space research, vol 58 n° 3 (August 2016)PermalinkLidar imagery and InSAR for digital forestry / Benoît Saint-Onge in GIM international, vol 30 n° 7 (July 2016)PermalinkSource model from ALOS-2 ScanSAR of the 2015 Nepal earthquakes / Youtian Liu in Journal of applied geodesy, vol 10 n° 2 (June 2016)PermalinkHigh-precision positioning of radar scatterers / Prabu Dheenathayalan in Journal of geodesy, vol 90 n° 5 (May 2016)PermalinkPersistent Scatterer Interferometry: A review / Michele Crosetto in ISPRS Journal of photogrammetry and remote sensing, vol 115 (May 2016)PermalinkSatellite radar interferometry / Sabine de Milliano in GIM international, vol 30 n° 5 (May 2016)PermalinkInterferometric processing of Sentinel-1 TOPS Data / Néstor Yagüe-Martínez in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)PermalinkDeck and cable dynamic testing of a single-span bridge using radar interferometry and videometry measurements / George Piniotis in Journal of applied geodesy, vol 10 n° 1 (March 2016)Permalink