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A land use/land cover change geospatial cyberinfrastructure to integrate big data and temporal topology / Jin Xing in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)
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Titre : A land use/land cover change geospatial cyberinfrastructure to integrate big data and temporal topology Type de document : Article/Communication Auteurs : Jin Xing, Auteur ; Renee E. Sieber, Auteur Année de publication : 2016 Article en page(s) : pp 573 - 593 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] changement d'occupation du sol
[Termes IGN] cyberinfrastructure
[Termes IGN] dimension temporelle
[Termes IGN] données maillées
[Termes IGN] données massives
[Termes IGN] données spatiotemporelles
[Termes IGN] optimisation (mathématiques)
[Termes IGN] relation topologique
[Termes IGN] segmentation d'imageRésumé : (Auteur) Big data have shifted spatial optimization from a purely computational-intensive problem to a data-intensive challenge. This is especially the case for spatiotemporal (ST) land use/land cover change (LUCC) research. In addition to greater variety, for example, from sensing platforms, big data offer datasets at higher spatial and temporal resolutions; these new offerings require new methods to optimize data handling and analysis. We propose a LUCC-based geospatial cyberinfrastructure (GCI) that optimizes big data handling and analysis, in this case with raster data. The GCI provides three levels of optimization. First, we employ spatial optimization with graph-based image segmentation. Second, we propose ST Atom Model to temporally optimize the image segments for LUCC. At last, the first two domain ST optimizations are supported by the computational optimization for big data analysis. The evaluation is conducted using DMTI (DMTI Spatial Inc.) Satellite StreetView imagery datasets acquired for the Greater Montreal area, Canada in 2006, 2009, and 2012 (534 GB, 60 cm spatial resolution, RGB image). Our LUCC-based GCI builds an optimization bridge among LUCC, ST modelling, and big data. Numéro de notice : A2016-204 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1104534 En ligne : https://doi.org/10.1080/13658816.2015.1104534 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79891
in International journal of geographical information science IJGIS > vol 30 n° 3-4 (March - April 2016) . - pp 573 - 593[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016021 RAB Revue Centre de documentation En réserve L003 Disponible Photogrammetric computer vision / Wolfgang Förstner (2016)
Titre : Photogrammetric computer vision : statistics, geometry, orientation and reconstruction Type de document : Guide/Manuel Auteurs : Wolfgang Förstner, Auteur ; Bernhard P. Wrobel, Auteur Editeur : Springer Nature Année de publication : 2016 Collection : Geometry and computing, ISSN 1866-6795 num. 11 Importance : 816 p. Format : 21 x 28 cm ISBN/ISSN/EAN : 978-3-319-11549-8 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] aérotriangulation numérique
[Termes IGN] compensation par faisceaux
[Termes IGN] couple stéréoscopique
[Termes IGN] données maillées
[Termes IGN] données vectorielles
[Termes IGN] estimation statistique
[Termes IGN] géométrie
[Termes IGN] géométrie projective
[Termes IGN] image 2D
[Termes IGN] image 3D
[Termes IGN] incertitude géométrique
[Termes IGN] ligne (géométrie)
[Termes IGN] modèle de Gauss-Markov
[Termes IGN] modèle géométrique de prise de vue
[Termes IGN] plan (géométrie)
[Termes IGN] point
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] rotation d'objet
[Termes IGN] semis de points
[Termes IGN] transformation géométrique
[Termes IGN] variable aléatoire
[Termes IGN] vision par ordinateur
[Termes IGN] visualisation 3DIndex. décimale : 33.30 Photogrammétrie numérique Résumé : (Editeur) This textbook offers a statistical view on the geometry of multiple view analysis, required for camera calibration and orientation and for geometric scene reconstruction based on geometric image features. The authors have backgrounds in geodesy and also long experience with development and research in computer vision, and this is the first book to present a joint approach from the converging fields of photogrammetry and computer vision. Part I of the book provides an introduction to estimation theory, covering aspects such as Bayesian estimation, variance components, and sequential estimation, with a focus on the statistically sound diagnostics of estimation results essential in vision metrology. Part II provides tools for 2D and 3D geometric reasoning using projective geometry. This includes oriented projective geometry and tools for statistically optimal estimation and test of geometric entities and transformations and their relations, tools that are useful also in the context of uncertain reasoning in point clouds. Part III is devoted to modelling the geometry of single and multiple cameras, addressing calibration and orientation, including statistical evaluation and reconstruction of corresponding scene features and surfaces based on geometric image features. The authors provide algorithms for various geometric computation problems in vision metrology, together with mathematical justifications and statistical analysis, thus enabling thorough evaluations. The chapters are self-contained with numerous figures and exercises, and they are supported by an appendix that explains the basic mathematical notation and a detailed index. The book can serve as the basis for undergraduate and graduate courses in photogrammetry, computer vision, and computer graphics. It is also appropriate for researchers, engineers, and software developers in the photogrammetry and GIS industries, particularly those engaged with statistically based geometric computer vision methods. Note de contenu : 1. Introduction
1.1. Tasks for Photogrammetric Computer Vision
1.2. Modelling in Photogrammetric Computer Vision
1.3. The Book
1.4. On Notation
Part One - Statistics and Estimation
2. Probability Theory and Random Variables
2.1. Notions of Probability
2.2. Axiomatic Definition of Probability
2.3. Random Variables
2.4. Distributions
2.5. Moments
2.6. Quantiles of a Distribution
2.7. Functions of Random Variables
2.8. Stochastic Processes
2.9. Generating Random Numbers
2.10. Exercises
3. Testing
3.1. Principles of Hypothesis Testing
3.2. Testability of an Alternative Hypothesis
3.3. Common Tests
3.4. Exercises
4. Estimation
4.1. Estimation Theory
4.2. The Linear Gauss–Markov Model
4.3. Gauss–Markov Model with Constraints
4.4. The Nonlinear Gauss–Markov Model
4.5. Datum or Gauge Definitions and Transformations
4.6. Evaluation
4.7. Robust Estimation and Outlier Detection
4.8. Estimation with Implicit Functional Models
4.9. Methods for Closed Form Estimations
4.10. Estimation in Autoregressive Models
4.11. Exercises
Part two - Geometry
5. Homogeneous Representations of Points, Lines and Planes
5.1. Homogeneous Vectors and Matrices
5.2. Homogeneous Representations of Points and Lines in 2D
5.3. Homogeneous Representations in IPn
5.4. Homogeneous Representations of 3D Lines
5.5. On Plücker Coordinates for Points, Lines and Planes
5.6. The Principle of Duality
5.7. Conics and Quadrics
5.8. Normalizations of Homogeneous Vectors
5.9. Canonical Elements of Coordinate Systems
5.10. Exercises
6. Transformations
6.1. Structure of Projective Collineations
6.2. Basic Transformations
6.3. Concatenation and Inversion of Transformations
6.4. Invariants of Projective Mappings
6.5. Perspective Collineations
6.6. Projective Correlations
6.7. Hierarchy of Projective Transformations and Their Characteristics
6.8. Normalizations of Transformations
6.9. Conditioning
6.10. Exercises
7. Geometric Operations
7.1. Geometric Operations in 2D Space
7.2. Geometric Operations in 3D Space
7.3. Vector and Matrix Representations for Geometric Entities
7.4. Minimal Solutions for Conics and Transformations
7.5. Exercises
8. Rotations
8.1. Rotations in 3D
8.2. Concatenation of Rotations
8.3. Relations Between the Representations for Rotations
8.4. Rotations from Corresponding Vector Pairs
8.5. Exercises
9. Oriented Projective Geometry
9.1. Oriented Entities and Constructions
9.2. Transformation of Oriented Entities
9.3. Exercises
10. Reasoning with Uncertain Geometric Entities
10.1. Motivation
10.2. Representing Uncertain Geometric Elements
10.3. Propagation of the Uncertainty of Homogeneous Entities
10.4. Evaluating Statistically Uncertain Relations
10.5. Closed Form Solutions for Estimating Geometric Entities
10.6. Iterative Solutions for Maximum Likelihood Estimation
10.7. Exercises
Part Three - Orientation and Reconstruction
11. Overview
11.1. Scene, Camera, and Image Models
11.2. The Setup of Orientation, Calibration, and Reconstruction
11.3. Exercises
12. Geometry and Orientation of the Single Image
12.1. Geometry of the Single Image
12.2. Orientation of the Single Image
12.3. Inverse Perspective and 3D Information from a Single Image
12.4. Exercises
13. Geometry and Orientation of the Image Pair
13.1. Motivation
13.2 The Geometry of the Image Pair
13.3 Relative Orientation of the Image Pair
13.4. Triangulation
13.5. Absolute Orientation and Spatial Similarity Transformation
13.6. Orientation of the Image Pair and Its Quality
13.7. Exercises
14. Geometry and Orientation of the Image Triplet
14.1. Geometry of the Image Triplet
14.2. Relative Orientation of the Image Triplet
14.3. Exercises
15. Bundle Adjustment
15.1. Motivation for Bundle Adjustment and Its Tasks
15.2. Block Adjustment
15.3. Sparsity of Matrices, Free Adjustment and Theoretical Precision
15.4. Self-calibrating Bundle Adjustment
15.5. Camera Calibration
15.6. Outlier Detection and Approximate Values
15.7. View Planning
15.8. Exercises
16. Surface Reconstruction
16.1. Introduction
16.2. Parametric 21/2D Surfaces
16.3. Models for Reconstructing One-Dimensional Surface Profiles
16.4. Reconstruction of 21/2D Surfaces from 3D Point Clouds
16.5. Examples for Surface Reconstruction
16.6. Exercises
Appendix: Basics and Useful Relations from Linear AlgebraNuméro de notice : 22610 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Manuel Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82915 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 22610-01 33.30 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible 22610-02 DEP-ECP Livre Marne-la-Vallée Dépôt en unité Exclu du prêt 22610-03 DEP-ELZ Livre Marne-la-Vallée Dépôt en unité Exclu du prêt QGIS 2 cookbook / Alex Mandel (2016)
Titre : QGIS 2 cookbook : become a QGIS power user and master QGIS data management, visualization, and spatial analysis techniques [Quick answers to common problems] Type de document : Guide/Manuel Auteurs : Alex Mandel, Auteur ; Victor Olaya Ferrero, Auteur ; Anita Graser, Auteur ; Alexander Bruy, Auteur Editeur : Birmingham : Packt Publishing Année de publication : 2016 Importance : 368 p. Format : 19 x 24 cm ISBN/ISSN/EAN : 978-1-78398-496-1 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] analyse vectorielle
[Termes IGN] données lidar
[Termes IGN] données maillées
[Termes IGN] données spatiotemporelles
[Termes IGN] exploration de données géographiques
[Termes IGN] PostGIS
[Termes IGN] QGISIndex. décimale : 37.35 Logiciels SIG Résumé : (Editeur) QGIS is a user-friendly, cross-platform desktop geographic information system used to make maps and analyze spatial data. QGIS allows users to understand, question, interpret, and visualize spatial data in many ways that reveal relationships, patterns, and trends in the form of maps. This book is a collection of simple to advanced techniques that are needed in everyday geospatial work, and shows how to accomplish them with QGIS. You will begin by understanding the different types of data management techniques, as well as how data exploration works. You will then learn how to perform classic vector and raster analysis with QGIS, apart from creating time-based visualizations. Finally, you will learn how to create interactive and visually appealing maps with custom cartography. By the end of this book, you will have all the necessary knowledge to handle spatial data management, exploration, and visualization tasks in QGIS. Note de contenu : Chapter 1 - Data Input and Output
Chapter 2 - Data Management
Chapter 3 - Common Data Preprocessing Steps
Chapter 4 - Data Exploration
Chapter 5 - Classic Vector Analysis
Chapter 6 - Network Analysis
Chapter 7 - Raster Analysis I
Chapter 8 - Raster Analysis II
Chapter 9 - QGIS and the Web
Chapter 10 - Cartography Tips
Chapter 11 - Extending QGIS
Chapter 12 - Up and ComingNuméro de notice : 22764 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Manuel informatique Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86651 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 22764-01 37.35 Manuel Informatique Centre de documentation Géomatique Disponible 22764-02 37.35 Manuel Informatique Centre de documentation Géomatique Disponible Realtime projective multi-texturing of pointclouds and meshes for a realistic street-view web navigation / Alexandre Devaux (2016)
Titre : Realtime projective multi-texturing of pointclouds and meshes for a realistic street-view web navigation Type de document : Article/Communication Auteurs : Alexandre Devaux , Auteur ; Mathieu Brédif , Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2016 Conférence : ACM Web3D 2016 22/07/2016 24/07/2016 Anaheim Californie - Etats-Unis Proceedings ACM Importance : pp 105 - 108 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données maillées
[Termes IGN] globe virtuel
[Termes IGN] rendu réaliste
[Termes IGN] semis de points
[Termes IGN] temps réel
[Termes IGN] texturage
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Street-view web applications have now gained widespread popularity. Targeting the general public, they offer ease of use, but while they allow efficient navigation from a pedestrian level, the immersive quality of such renderings is still low. The user is usually stuck at specific positions and transitions bring out artefacts, in particular parallax and aliasing. We propose a method to enhance the realism of street view navigation systems using a hybrid rendering based on realtime projective texturing on meshes and pointclouds with occlusion handling, requiring extremely minimized pre-processing steps allowing fast data update, progressive streaming (mesh-based approximation, with point cloud details) and unaltered raw data precise visualization. Numéro de notice : C2016-057 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1145/2945292.2945311 En ligne : https://doi.org/10.1145/2945292.2945311 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91911 Documents numériques
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Realtime projective multi-texturing... - pdf auteurAdobe Acrobat PDF Open source geospatial tools / Daniel McInerney (2015)
Titre : Open source geospatial tools : applications in Earth observation Type de document : Monographie Auteurs : Daniel McInerney, Éditeur scientifique ; Pieter Kempeneers, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2015 Collection : Earth systems data and models Importance : 358 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-319-01823-2 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] analyse de données
[Termes IGN] classification multibande
[Termes IGN] données localisées 3D
[Termes IGN] données maillées
[Termes IGN] données vectorielles
[Termes IGN] Geospatial data abstraction library
[Termes IGN] interface de programmation
[Termes IGN] lasergrammétrie
[Termes IGN] logiciel libre
[Termes IGN] Orfeo Tool Box
[Termes IGN] outil logiciel
[Termes IGN] traitement d'image
[Termes IGN] traitement de données localiséesIndex. décimale : 37.35 Logiciels SIG Résumé : (Editeur) This book focuses on the use of open source software for geospatial analysis. It demonstrates the effectiveness of the command line interface for handling both vector, raster and 3D geospatial data. Appropriate open-source tools for data processing are clearly explained and discusses how they can be used to solve everyday tasks. A series of fully worked case studies are presented including vector spatial analysis, remote sensing data analysis, landcover classification and LiDAR processing. A hands-on introduction to the application programming interface (API) of GDAL/OGR in Python/C++ is provided for readers who want to extend existing tools and/or develop their own software. Note de contenu : Part - I Geospatial Data Processing with GDAL/OGR
1. Introduction
2. Vector Data Processing
3. Raster Data Explained
4. Introduction to GDAL Utilities
5. Manipulating Raster Data
6. Indexed Color Images
7. Image Overviews, Tiling and Pyramids
8. Image (Re-)projections and Merging
9. Raster Meets Vector Data
10. Raster Meets Point Data
11. Virtual Rasters and Raster Calculations
Part - II Third Party Open Source Geospatial Utilities
12. Pktools
13. Orfeo Toolbox
14. Write Your Own Geospatial Utilities
15. 3D Point Cloud Data Processing
Part - III Case Studies
16. Case Study on Vector Spatial Analysis
17. Case Study on Multispectral Land Cover Classification
18. Case Study on Point Data
19. Conclusions and Future Outlook
Appendix A: Data Covered in the Book
Appendix B: Installation of Software
GlossaryNuméro de notice : 22219 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Recueil / ouvrage collectif Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75218 Réservation
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