Centre dedocumentation
scientifique

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)  

Public [article]  inEngineering Geology > vol 305 (August 2022) . - n° 106730 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 géologique Résumé : (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 [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])  

Public [article]  inGeocarto international > vol 37 n° 13 [15/07/2022] . - pp 3941 - 3962 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] Pakistan Résumé : (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 [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)  

Public [article]  inAdvances in space research > vol 70 n° 2 (15 July 2022) . - pp 360 - 370 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 astronomique Résumé : (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 [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)  

Public [article]  inJournal of geodesy > vol 96 n° 7 (July 2022) . - n° 47 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 temporelle Résumé : (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 [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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 186 (April 2022) . - pp 123 - 139 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 points Résumé : (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 [article]

Réservation

Réserver ce document

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)  

Permalink

Land 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])  

Permalink

Persistent 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)  

Permalink

Evaluation 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)  

Permalink

Investigation 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)  

Permalink

Orbit 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)  

Permalink

Estimation of surface deformation due to Pasni earthquake using RADAR interferometry / Muhammad Ali in Geocarto international, vol 36 n° 14 ([01/08/2021])  

Permalink

Glacier 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])  

Permalink

Refinement 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)  

Permalink

Detecting 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)  

Permalink