Détail de l'éditeur
Ecole Nationale des Ponts et Chaussées ENPC
localisé à :
Paris
|
Documents disponibles chez cet éditeur (8)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externesUsing remote sensing and modeling to monitor and understand harmful algal blooms. Application to Karaoun Reservoir (Lebanon) / Najwa Sharaf (2021)
Titre : Using remote sensing and modeling to monitor and understand harmful algal blooms. Application to Karaoun Reservoir (Lebanon) Type de document : Thèse/HDR Auteurs : Najwa Sharaf, Auteur ; Brigitte Vinçon-Leite, Directeur de thèse ; Kamal Slim, Directeur de thèse Editeur : Paris : Ecole Nationale des Ponts et Chaussées ENPC Année de publication : 2021 Importance : 132 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de Doctorat Sciences et Techniques de l’environnementLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] algue
[Termes IGN] barrage
[Termes IGN] chlorophylle
[Termes IGN] distribution spatiale
[Termes IGN] espèce exotique envahissante
[Termes IGN] hydrodynamique
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] lac
[Termes IGN] Liban
[Termes IGN] modélisation 3D
[Termes IGN] plancton
[Termes IGN] simulation hydrodynamique
[Termes IGN] température de surfaceIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Reservoirs are strategic water resources in particular for drinking water and hydropower production. Nevertheless, their physical and biogeochemical processes have been long influenced by anthropogenic pressures. A complete and regular monitoring of reservoir water quality in the context of current climate change, eutrophication and higher water demand, has become crucial for optimal management strategies. Recent progress in the satellite remote sensing field made it possible to enhance data acquisition on a synoptic scale and to perform retrospective studies. Satellite data can complement measurements however over a limited depth of the water column. In addition, three-dimensional (3D) numerical models which integrate physical, chemical and biological processes can fill temporal gaps and extend the information into the vertical domain.In this context, this PhD thesis focuses on the combined use of techniques and data derived from field monitoring, satellite remote sensing and 3D modeling. The overreaching objective of this work is to propose a combined approach for surveying the water quality of medium-sized reservoirs (~ 14 km2).The study site is Karaoun Reservoir, Lebanon (semi-arid climate, surface 12 km2, capacity 110 hm3). It mainly serves for hydropower however with possibly a future drinking water production. It is eutrophic and has been experiencing regular events of toxic cyanobacterial blooms. The following methodological approach was adopted:i) In situ measurements were regularly collected from spring to fall for the calibration and the validation of remote sensing algorithms and of the model.ii) In order to calibrate and validate remote sensing algorithms, Landsat 8 and Sentinel-2 imagery were atmospherically corrected using a single-channel algorithm and the 6SV code respectively.a. Four algorithms from literature for deriving surface temperature were validated using Landsat 8 thermal data.b. A previously calibrated and validated Sentinel-2 algorithm was applied to retrieve chlorophyll-a concentrations.c. An empirical algorithm was calibrated and validated in order to retrieve transparency from Sentinel-2 data.iii) In order to conduct a retrospective analysis of surface temperature, the validated single channel algorithm was applied to a series of Landsat images from 1984 to 2018.iv) In order to reproduce the hydrodynamics and ecological processes, including cyanobacterial biomass in space and time, the Delft3D model was configured, calibrated and validated for summer and fall. The spatial distribution of surface temperature and chlorophyll-a concentrations from the satellite and the model were investigated.The results of this study revealed that, among the four tested algorithms, the single channel algorithm dependent on atmospheric water vapor content and lake water emissivity yielded the best estimations of surface temperature. Using this validated algorithm, the retrospective analysis of surface temperature did not reveal any warming trend over the 1984-2018 period at the study site. Compared to in situ profiles, the Delft3D model represented well the evolution of the water level fluctuations, and the time and vertical distribution of temperature and phytoplankton biomass. Satellite data and model simulations showed minor spatial heterogeneities of surface temperature ( Note de contenu : General introduction
1- State of the art
2- Materials and methods
3- Field data analysis
4- Lake surface temperature retrieval from Landsat-8 and retrospective analysis
5- Thermal regime of reservoirs: A satellite and 3D modeling approach
6- 3D ecological modeling at Karaoun Reservoir
7- Conclusions and perspectivesNuméro de notice : 28499 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Sciences et Techniques de l’environnement : Ponts ParisTech : 2021 Organisme de stage : Laboratoire Eau Environnement et Systèmes Urbains DOI : sans En ligne : https://pastel.archives-ouvertes.fr/tel-03404563 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99311
Titre : Learning 3D generation and matching Type de document : Thèse/HDR Auteurs : Thibault Groueix, Auteur ; Mathieu Aubry, Directeur de thèse Editeur : Paris : Ecole Nationale des Ponts et Chaussées ENPC Année de publication : 2020 Importance : 169 p. Format : 21 x 30 cm Note générale : bibliographie
A doctoral thesis in the domain of automated signal and image processing submitted to École Doctorale Paris-Est
Mathématiques et Sciences et Technologies de l’Information et de la CommunicationLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement de formes
[Termes IGN] appariement dense
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] déformation de surface
[Termes IGN] isométrie
[Termes IGN] maillage
[Termes IGN] modélisation 3D
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'image
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] voxelIndex. décimale : THESE Thèses et HDR Résumé : (auteur) The goal of this thesis is to develop deep learning approaches to model and analyse 3D shapes. Progress in this field could democratize artistic creation of 3D assets which currently requires time and expert skills with technical software. We focus on the design of deep learning solutions for two particular tasks, key to many 3D modeling applications: single-view reconstruction and shape matching. A single-view reconstruction (SVR) method takes as input a single image and predicts the physical world which produced that image. SVR dates back to the early days of computer vision. In particular, in the 1960s, Lawrence G. Roberts proposed to align simple 3D primitives to the input image under the assumption that the physical world is made of cuboids. Another approach proposed by Berthold Horn in the 1970s is to decompose the input image in intrinsic images and use those to predict the depth of every input pixel. Since several configurations of shapes, texture and illumination can explain the same image, both approaches need to form assumptions on the distribution of images and 3D shapes to resolve the ambiguity. In this thesis, we learn these assumptions from large-scale datasets instead of manually designing them. Learning allows us to perform complete object reconstruction, including parts which are not visible in the input image. Shape matching aims at finding correspondences between 3D objects. Solving this task requires both a local and global understanding of 3D shapes which is hard to achieve explicitly. Instead we train neural networks on large-scale datasets to solve this task and capture this knowledge implicitly through their internal parameters.Shape matching supports many 3D modeling applications such as attribute transfer, automatic rigging for animation, or mesh editing.The first technical contribution of this thesis is a new parametric representation of 3D surfaces modeled by neural networks.The choice of data representation is a critical aspect of any 3D reconstruction algorithm. Until recently, most of the approaches in deep 3D model generation were predicting volumetric voxel grids or point clouds, which are discrete representations. Instead, we present an alternative approach that predicts a parametric surface deformation ie a mapping from a template to a target geometry. To demonstrate the benefits of such a representation, we train a deep encoder-decoder for single-view reconstruction using our new representation. Our approach, dubbed AtlasNet, is the first deep single-view reconstruction approach able to reconstruct meshes from images without relying on an independent post-processing, and can do it at arbitrary resolution without memory issues. A more detailed analysis of AtlasNet reveals it also generalizes better to categories it has not been trained on than other deep 3D generation approaches.Our second main contribution is a novel shape matching approach purely based on reconstruction via deformations. We show that the quality of the shape reconstructions is critical to obtain good correspondences, and therefore introduce a test-time optimization scheme to refine the learned deformations. For humans and other deformable shape categories deviating by a near-isometry, our approach can leverage a shape template and isometric regularization of the surface deformations. As category exhibiting non-isometric variations, such as chairs, do not have a clear template, we learn how to deform any shape into any other and leverage cycle-consistency constraints to learn meaningful correspondences. Our reconstruction-for-matching strategy operates directly on point clouds, is robust to many types of perturbations, and outperforms the state of the art by 15% on dense matching of real human scans. Note de contenu : 1- Introduction
2 Related Work
3 AtlasNet: A Papier-Mache Approach to Learning 3D Surface Generation
4 3D-CODED : 3D Correspondences by Deep Deformation
5 Unsupervised cycle-consistent deformation for shape matching
6 ConclusionNuméro de notice : 28310 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Automated signal and image processing : Paris-Est : 2020 Organisme de stage : LIGM DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-03127055v2/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98201 Combining meshes and geometric primitives for accurate and semantic modeling / Florent Lafarge (2009)
Titre : Combining meshes and geometric primitives for accurate and semantic modeling Type de document : Article/Communication Auteurs : Florent Lafarge, Auteur ; Renaud Keriven, Auteur ; Mathieu Brédif Editeur : Paris : Ecole Nationale des Ponts et Chaussées ENPC Année de publication : 2009 Conférence : BMVC 2009, British Machine Vision Conference 07/09/2009 10/09/2009 Londres Royaume-Uni OA Proceedings Importance : 11 p. Format : 21 X 30 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] maillage par triangles
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modélisation 3D
[Termes IGN] primitive géométrique
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] vision par ordinateurRésumé : (Auteur) 3D-models of urban scenes are very useful for many applications such as urban planning, virtual reality, disaster recovery or computer games. The reconstruction of such scenes is a well known computer vision problem which has been addressed by various approaches providing integral building representations but remains an open issue. We propose an hybrid representation of noisy 3D models such as buildings obtained by multi-view stereo. This representation merges meshes and 3D-primitives. It provides high compression rates while keeping details, introduces semantic knowledge despites noise corruption, and even improves accuracy of the original reconstruction. Numéro de notice : C2009-045 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Poster nature-HAL : Poster-avec-CL DOI : 10.5244/C.23.38 En ligne : https://hal.inria.fr/hal-00781776/file/2009_bmvc.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64297 Documents numériques
en open access
Combining meshes and geometric primitives - pdfAdobe Acrobat PDFRapport Quadriennal 2003-2006 [du] CNFGG [à la] 24e assemblée générale de l'Union Géodésique et Géophysique Internationale / D. Schertzer (2007)
Titre : Rapport Quadriennal 2003-2006 [du] CNFGG [à la] 24e assemblée générale de l'Union Géodésique et Géophysique Internationale Type de document : Rapport Auteurs : D. Schertzer, Éditeur scientifique ; L. Tchiguirinskaia, Éditeur scientifique ; Comité national français de géodésie et géophysique Editeur : Paris : Ecole Nationale des Ponts et Chaussées ENPC Année de publication : 2007 Conférence : IUGG 2007, 24th general assembly UGGI 02/07/2007 13/07/2007 Pérouse Italie OA Proceedings Importance : 408 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Français (fre) Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie
[Termes IGN] géodésie
[Termes IGN] géomagnétisme
[Termes IGN] géophysique
[Termes IGN] géosciences
[Termes IGN] hydrologie
[Termes IGN] météorologie
[Termes IGN] océanographie
[Termes IGN] sismologie
[Termes IGN] volcanologieNuméro de notice : 33995 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Rapport d'activité DOI : sans En ligne : https://iag.dgfi.tum.de/fileadmin/IAG-docs/NationalReports2007/France.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102818
- Rapport Quadriennal 2003-2006 [du] CNFGG, ch. French activities in ground gravimetry during the period 2003-2006 / Martine Amalvict (2007)
- Rapport Quadriennal 2003-2006 [du] CNFGG, ch. Geodetic Reference Frames in France : Highlights 2004-2007 / Claude Boucher (2007)
- Rapport Quadriennal 2003-2006 [du] CNFGG, ch. DORIS applications for Earth and atmospheric sciences / Pascal Willis (2007)
Documents numériques
![Rapport Quadriennal 2003-2006 [du] CNFGG - application/pdf](./vig_num.php?explnum_id=10264 "Rapport Quadriennal 2003-2006 [du] CNFGG - application/pdf")
en open access
Rapport Quadriennal 2003-2006 [du] CNFGGAdobe Acrobat PDFRapport Quadriennal 2003-2006 [du] CNFGG, ch. French activities in ground gravimetry during the period 2003-2006 / Martine Amalvict (2007)
Documents numériques
peut être téléchargé
French activities ... - pdf éditeurAdobe Acrobat PDF
