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]

Learning to represent and reconstruct 3D deformable objects / Jan Bednarik (2022)  

Public Titre : Learning to represent and reconstruct 3D deformable objects Type de document : Thèse/HDR Auteurs : Jan Bednarik, Auteur ; Pascal Fua, Directeur de thèse ; M. Salzmann, Directeur de thèse Editeur : Lausanne : Ecole Polytechnique Fédérale de Lausanne EPFL Année de publication : 2022 Importance : 138 p. Format : 21 x 30 cm Note générale : bibliographie Thèse présentée pour l'obtention du grade de Docteur ès Sciences, Ecole Polytechnique Fédérale de Lausanne Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement de formes [Termes IGN] apprentissage profond [Termes IGN] cohérence temporelle [Termes IGN] déformation de surface [Termes IGN] distorsion d'image [Termes IGN] géométrie de Riemann [Termes IGN] image 3D [Termes IGN] reconstruction d'objet [Termes IGN] semis de points [Termes IGN] vision par ordinateur Index. décimale : THESE Thèses et HDR Résumé : (auteur) Representing and reconstructing 3D deformable shapes are two tightly linked problems that have long been studied within the computer vision field. Deformable shapes are truly ubiquitous in the real world, whether be it specific object classes such as humans, garments and animals or more abstract ones such as generic materials deforming under stress caused by an external force. Truly practical computer vision algorithms must be able to understand the shapes of objects in the observed scenes to unlock the wide spectrum of much sought after applications ranging from virtual try-on to automated surgeries. Automatic shape reconstruction, however, is known to be an ill-posed problem, especially in the common scenario of a single image input. Therefore, the modern approaches rely on deep learning paradigm which has proven to be extremely effective even for the severely under-constrained computer vision problems. We, too, exploit the success of data-driven approaches, however, we also show that generic deep learning models can greatly benefit from being combined with explicit knowledge originating in traditional computational geometry. We analyze the use of various 3D shape representations for deformable object reconstruction and we distinctly focus on one of them, the atlas-based representation, which turns out to be especially suitable for modeling deformable shapes and which we further improve and extend to yield higher quality reconstructions. The atlas-based representation models the surfaces as an ensemble of continuous functions and thus allows for arbitrary resolution and analytical surface analysis. We identify major shortcomings of the base formulation, namely the infamous phenomena of patch collapse, patch overlap and arbitrarily strong mapping distortions, and we propose novel regularizers based on analytically computed properties of the reconstructed surfaces. Our approach counteracts the aforementioned drawbacks while yielding higher reconstruction accuracy in terms of surface normals on the tasks of single view-reconstruction, shape completion and point cloud auto-encoding. We dive into the problematics of atlas-based shape representation even deeper and focus on another pressing design flaw, the global inconsistency among the individual mappings. While the inconsistency is not reflected in the traditional reconstruction accuracy quantitative metrics, it is detrimental to the visual quality of the reconstructed surfaces. Specifically, we design loss functions encouraging intercommunication among the individual mappings which pushes the resulting surface towards a C1 smooth function. Our experiments on the tasks of single-view reconstruction and point cloud auto-encoding reveal that our method significantly improves the visual quality when compared to the baselines. Furthermore, we adapt the atlas-based representation and the related training procedure so that it could model a full sequence of a deforming object in a temporally-consistent way. In other words, the goal is to produce such reconstruction where each surface point always represents the same semantic point on the target ground-truth surface. To achieve such behavior, we note that if each surface point deforms close-to-isometrically, its semantic location likely remains unchanged. Practically, we make use of the Riemannian metric which is computed analytically on the surfaces, and force it to remain point-wise constant throughout the sequence. Our experimental results reveal that our method yields state-of-the-art results on the task of unsupervised dense shape correspondence estimation, while also improving the visual reconstruction quality. Finally, we look into a particular problem of monocular texture-less deformable shape reconstruction, an instance of the Shape-from-Shading problem. We propose a multi-task learning approach which takes an RGB image of an unknown object as the input and jointly produces a normal map, a depth map and a mesh corresponding to the observed part of the surface. We show that forcing the model to produce multiple different 3D representations of the same objects results in higher reconstruction quality. To train the network, we acquire a large real-world annotated dataset of texture-less deforming objects and we release it for public use. Finally, we prove through experiments that our approach outperforms a previous optimization based method on the single-view-reconstruction task. Note de contenu : 1- Introduction 2- Related work 3- Atlas-based representation for deformable shape reconstruction 4- Shape reconstruction by learning differentiable surface representations 5- Better patch stitching for parametric surface reconstruction 6- Temporally-consistent surface reconstruction using metrically-consistent atlases 7- Learning to reconstruct texture-less deformable surfaces from a single view 8- Conclusion Numéro de notice : 15761 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : Thèse de Doctorat : Sciences : Lausanne, EPFL : 2022 DOI : 10.5075/epfl-thesis-7974 En ligne : https://doi.org/10.5075/epfl-thesis-7974 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100958

A prediction model for surface deformation caused by underground mining based on spatio-temporal associations / Min Ren in Geomatics, Natural Hazards and Risk, vol 13 n° 1 (2022)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 13 n° 1 (2022) . - pp 94 - 122 Titre : A prediction model for surface deformation caused by underground mining based on spatio-temporal associations Type de document : Article/Communication Auteurs : Min Ren, Auteur ; Guanwen Cheng, Auteur ; Wancheng Zhu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 94 - 122 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse des risques [Termes IGN] analyse spatio-temporelle [Termes IGN] Chine [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] déformation de la croute terrestre [Termes IGN] déformation de surface [Termes IGN] mine de fer [Termes IGN] modèle de simulation [Termes IGN] règle d'association Mots-clés libres : spatio-temporal association rule mining (STARM) Résumé : (auteur) Accurate predictions of the surface deformation caused by underground mining are crucial for the safe development of underground resources. Although surface deformation has been predicted by artificial intelligence (AI) methods, most AI models are established based on the relationships between surface deformation and influential factors. The lack of consideration of the deformation state transition often leads to errors in the prediction results of catastrophic deformation by conventional AI methods. In this respect, this study introduces a surface deformation prediction model based on spatio-temporal association rule mining (STARM). Surface deformation is classified as excessive deformation zone (EDZ) and hysteretic deformation zone (HDZ), representing different surface deformation stage or state. The spatio-temporal association rules between the monitored EDZ and HDZ data are then mined. A surface deformation prediction model is established according to the spatio-temporal relationship between monitored EDZ and HDZ data. The proposed model is verified based on a practical case study of the Chengchao Iron Mine in China. The data collection of the influential factors is not requisite for the proposed model. It can achieve accurate prediction of the catastrophic deformation that was characterized by deformation state transition. Numéro de notice : A2022-035 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1080/19475705.2021.2015460 Date de publication en ligne : 21/12/2021 En ligne : https://doi.org/10.1080/19475705.2021.2015460 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99359 [article]

Les journées de la Recherche IGN 2021 / Anonyme in Géomatique expert, n° 135 (septembre 2021)

Public [article]  inGéomatique expert > n° 135 (septembre 2021) . - pp 36 - 47 Titre : Les journées de la Recherche IGN 2021 Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2021 Conférence : Journées Recherche de l'IGN 2021, 30es Journées 25/05/2021 28/05/2021 en ligne France vidéos des journées Article en page(s) : pp 36 - 47 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Information géographique [Termes IGN] appariement d'images [Termes IGN] BD Topo [Termes IGN] chronométrie [Termes IGN] Copernicus (programme européen) [Termes IGN] correction radiométrique [Termes IGN] déformation de surface [Termes IGN] données GRACE [Termes IGN] éclairement lumineux [Termes IGN] extraction de données [Termes IGN] fonte des glaces [Termes IGN] horloge atomique [Termes IGN] ilot thermique urbain [Termes IGN] image aérienne [Termes IGN] intelligence artificielle [Termes IGN] MicMac [Termes IGN] modèle numérique de surface [Termes IGN] recherche scientifique [Termes IGN] série temporelle [Termes IGN] surveillance sanitaire [Termes IGN] visualisation de données Résumé : (Auteur) L’édition 2021 des Journées de la Recherche à l’IGN s’est déroulée, cette année encore, « en ligne ». C’était, malgré tout, l’occasion de marquer la trentième édition de l’événement. Numéro de notice : A2021-661 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/09/2021 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98481 [article]

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
IFN-001-P002273	PER	Revue	Nogent-sur-Vernisson	Salle périodiques	Exclu du prêt

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

Public [article]  inGeocarto international > vol 36 n° 14 [01/08/2021] . - pp 1630 - 1645 Titre : Estimation of surface deformation due to Pasni earthquake using RADAR interferometry Type de document : Article/Communication Auteurs : Muhammad Ali, Auteur ; Muhammad Shahzad, Auteur ; Majir Nazeer, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1630 - 1645 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] déformation de surface [Termes IGN] déformation verticale de la croute terrestre [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] Pakistan [Termes IGN] polarisation [Termes IGN] rapport signal sur bruit [Termes IGN] séisme [Termes IGN] série temporelle Résumé : (auteur) This study analyzed the land deformation associated with Mw 6.3 earthquake along Pasni coast, Pakistan. Post-earthquake widespread surface displacements were found using Sentinel-1 data. Pre, Co and Post-seismic images were used to investigate the deformation trends. Before the earthquake, 89.65% of Pasni land mass showed uplifting from 0.0 to 3.0 cm at 1.00 mm/day while 3.0 cm subsidence was noted in 86.36% of the land mass after the earthquake at 2.5 mm/day. However, two weeks after the earthquake, 72.9% Pasni land mass showed uplifting at an unprecedented rate of 3.3 mm/day. The maximum deformation along the Line Of Sight (LOS) direction in co-seismic time was about -4.0 cm. Azimuthal interferogram showed more complex displacement pattern with both negative and positive displacements between ±5.0 cm. Pasni is already facing many problems due to increased sea water intrusion under prevailing climatic changes and land deformation due to strong earthquakes. Numéro de notice : A2021-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1661031 Date de publication en ligne : 09/09/2019 En ligne : https://doi.org/10.1080/10106049.2019.1661031 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98110 [article]

Spatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images / Bin Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)  

Permalink

Saline-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)  

Permalink

Reclaimed-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)  

Permalink

Study 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)  

Permalink

Local terrain modification method considering physical feature constraints for vector elements / Jiangfeng She in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)  

Permalink

Landslide displacement mapping based on ALOS-2/PALSAR-2 data using image correlation techniques and SAR interferometry: application to the Hell-Bourg landslide (Salazie Circle, La Réunion Island) / Daniel Raucoules in Geocarto international, vol 35 n° 2 ([01/02/2020])  

Permalink

A spatio-temporal deformation model for laser scanning point clouds / Corinna Harmening in Journal of geodesy, vol 94 n°2 (February 2020)  

Permalink

Learning 3D generation and matching / Thibault Groueix (2020)  

Permalink

Système de traitement d’images temps réel dédié à la mesure de champs denses de déplacements et de déformations / Seyfeddine Boukhtache (2020)  

Permalink

Analyse de la déformation récente dans le Grand Tunis par interférométrie radar SAR / Anis Chaabani (2019)  

Permalink