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Combining three multi-agent based generalisation models : Agent, Cartacom and Gael / Cécile Duchêne (01/12/2008)
Titre : Combining three multi-agent based generalisation models : Agent, Cartacom and Gael Type de document : Article/Communication Auteurs : Cécile Duchêne , Auteur ; Julien Gaffuri , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 01/12/2008 Conférence : SDH 2008, 13th international symposium on Spatial Data Handling, Headway in spatial data handling 23/06/2008 25/06/2008 Montpellier France Proceedings Springer Importance : pp 277 - 296 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] AGENT
[Termes IGN] base de données localisées
[Termes IGN] CartACom
[Termes IGN] contrainte d'intégrité
[Termes IGN] données vectorielles
[Termes IGN] GAEL
[Termes IGN] généralisation automatique de données
[Termes IGN] objet géographique
[Termes IGN] système multi-agents
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) This paper is concerned with the automated generalisation of vector geographic databases. It studies the possible synergies between three existing, complementary models of generalisation, all based on the multi-agent paradigm. These models are respectively well adapted for the generalisation of urban spaces (AGENT model), rural spaces (CARTACOm model) and background themes (GAEL model). In these models, the geographic objects are modelled as agents that apply generalisation algorithms to themselves, guided by cartographic constraints to satisfy. The differences between them particularly lie in their constraint modelling and their agent coordination model. Three complementary ways of combining these models are proposed: separate use on separate zones, “interlaced” sequential use on the same zone, and shared use of data internal to the models. The last one is further investigated and a partial re-engineering of the models is proposed. Copyright Springer Numéro de notice : C2008-001 Affiliation des auteurs : IGN (1940-2011) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-540-68566-1_16 En ligne : https://doi.org/10.1007/978-3-540-68566-1_16 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65036
Titre : A new approach for mountain areas cartography Type de document : Article/Communication Auteurs : Loïc Gondol , Auteur ; Arnaud Le Bris , Auteur ; François Lecordix , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 01/12/2008 Conférence : SDH 2008, 13th international symposium on Spatial Data Handling, Headway in spatial data handling 23/06/2008 25/06/2008 Montpellier France Proceedings Springer Importance : pp 315 - 333 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique
[Termes IGN] BD Topo
[Termes IGN] classification automatique
[Termes IGN] données vectorielles
[Termes IGN] montagne
[Termes IGN] représentation du relief
[Termes IGN] rocherRésumé : (Auteur) From now on, the French National Mapping Agency (IGN France) is set up with the BD TOPO®. This is a topographic vector database that covers the whole national territory. IGN has decided to product base maps at 1:25k and 1:50k from this database. On topographic mountain maps, rocks areas are among the most difficult map elements to represent, dealing with digital cartography. In the past, they were drawn manually by experienced cartographers, using graphic means and working with aerial photographs. Nowadays, we need to focus on two points with a digital approach. The first one is the detection and an automated classification of concerned areas. The next one is the development of an adapted cartographic representation of rocks and screes areas. This article presents the first results on these problems. As far as possible, we aim at having automated high mountain cartography with lower production costs. Also, we would like it to be as expressive as it was in previous maps. This is to keep the same cartographic quality of the current base map at 1:25k and 1:50k. Numéro de notice : C2008-002 Affiliation des auteurs : MATIS (1993-2011) Thématique : GEOMATIQUE Nature : Communication DOI : 10.1007/978-3-540-68566-1_18 En ligne : https://doi.org/10.1007/978-3-540-68566-1_18 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65037 Documents numériques
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Titre : Accuracy assessment of the ITRF datum definition Type de document : Article/Communication Auteurs : Zuheir Altamimi , Auteur ; Xavier Collilieux , Auteur ; Claude Boucher , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2008 Collection : International Association of Geodesy Symposia, ISSN 0939-9585 num. 132 Conférence : IAG 2006, 6th Hotine-Marussi symposium on theoretical and computational geodesy 29/05/2006 02/06/2006 Wuhan Chine Proceedings Springer Importance : pp 101 - 110 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] précision du positionnementRésumé : (auteur) One of the main objectives of the International Terrestrial Reference Frame (ITRF) is to provide a standard global reference frame having the most attainable accuracy of its datum definition in terms of its origin, scale and the time evolution of its orientation. This latter should satisfy, by convention, the no net rotation condition. The accuracy of the ITRF datum specifications are obviously dependent on the quality and the internal consistency of the solutions contributing to its elaboration and definition. In this paper, we examine and review the quality of the current ITRF datum definition with an accuracy assessment based on the ITRF2005 results and by consistency evaluation with respect to ITRF2000. The availability of time series of station positions and Earth Orientation Parameters, used now as input for the current ITRF construction, will facilitate the accuracy assessment. When rigorously stacking the time series of a given technique to estimate a long-term frame solution, the 7 transformation parameters of each individual temporal set of station positions are also estimated. By applying dynamically internal constraints (equivalent to minimum constraints approach) over the time series of the 7 parameters, we then preserve some physical “natural” parameters as for instance the scale and the origin from VLBI and SLR, respectively. Our conservative evaluation of the estimated accuracy of the ITRF datum definition is that the origin and its rate are accurate at the level of 5 mm and 2 mm/yr, the scale and its rate are at the level of 1 part per billion (ppb) and 0.1 ppb/yr and the No-Net-Rotation condition implementation is at the level of 2 mm/yr. Numéro de notice : C2006-037 Affiliation des auteurs : LAREG (1991-2011) Thématique : POSITIONNEMENT Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-540-74584-6_16 En ligne : https://doi.org/10.1007/978-3-540-74584-6_16 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102736 Applied spatial data analysis with R / R.S. Bivand (2008)
Titre : Applied spatial data analysis with R Type de document : Monographie Auteurs : R.S. Bivand, Auteur ; Edzer J. Pebesma, Auteur ; V. Gómez-Rubio, Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2008 Collection : Use R! Importance : 374 p. Format : 15 x 23 cm ISBN/ISSN/EAN : 978-0-387-78170-9 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de données
[Termes IGN] données localisées
[Termes IGN] géostatistique
[Termes IGN] R (langage)
[Termes IGN] système d'information géographiqueRésumé : (Editeur) This book is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information systems, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where coloured figures, complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. Note de contenu : 1. Hello World: Introducing Spatial Data
1.1 Applied Spatial Data Analysis
1.2 Why Do We Use R
1.3 R and GIS
1.4 Types of Spatial Data
1.5 Storage and Display
1.6 Applied Spatial Data Analysis
1.7 R Spatial Resources
Part 1 - Handling Spatial Data in R
2. Classes for Spatial Data in R
2.1 Introduction
2.2 Classes and Methods in R
2.3 Spatial Objects
2.4 SpatialPoints
2.5 SpatialLines
2.6 SpatialPolygons
2.7 SpatialGrid and SpatialPixel Objects
3. Visualising Spatial Data
3.1 The Traditional Plot System
3.2 Trellis/Lattice Plots with spplot
3.3 Interacting with Plots
3.4 Colour Palettes and Class Intervals
4. Spatial Data Import and Export
4.1 Coordinate Reference Systems
4.2 Vector File Formats
4.3 Raster File Formats
4.4 Grass
4.5 Other Import/Export Interfaces
4.6 Installing rgdal
5. Further Methods for Handling Spatial Data
5.1 Support
5.2 Overlay
5.3 Spatial Sampling
5.4 Checking Topologies
5.5 Combining Spatial Data
5.6 Auxiliary Functions
6. Customising Spatial Data Classes and Methods
6.1 Programming with Classes and Methods
6.2 Animal Track Data in Package Trip
6.3 Multi-Point Data: SpatialMultiPoints
6.4 Hexagonal Grids
6.5 Spatio-Temporal Grids
6.6 Analysing Spatial Monte Carlo Simulations
6.7 Processing Massive Grids
Part 2 - Analysing Spatial Data
7. Spatial Point Pattern Analysis
7.1 Introduction
7.2 Packages for the Analysis of Spatial Point Patterns
7.3 Preliminary Analysis of a Point Pattern
7.4 Statistical Analysis of Spatial Point Processes
7.5 Some Applications in Spatial Epidemiology
7.6 Further Methods for the Analysis of Point Patterns
8. Interpolation and Geostatistics
8.1 Introduction
8.2 Exploratory Data Analysis
8.3 Non-Geostatistical Interpolation Methods
8.4 Estimating Spatial Correlation: The Variogram
8.5 Spatial Prediction
8.6 Model Diagnostics
8.7 Geostatistical Simulation
8.8 Model-Based Geostatistics and Bayesian Approaches
8.9 Monitoring Network Optimization
8.10 Other R Packages for Interpolation and Geostatistics
9. Areal Data and Spatial Autocorrelation
9.1 Introduction
9.2 Spatial Neighbours
9.3 Spatial Weights
9.4 Spatial Autocorrelation: Tests
10. Modelling Areal Data
10.1 Introduction
10.2 Spatial Statistics Approaches
10.3 Mixed-Effects Models
10.4 Spatial Econometrics Approaches
10.5 Other Methods
11. Disease Mapping
11.1 Introduction
11.2 Statistical Models
11.3 Spatially Structured Statistical Models
11.4 Bayesian Hierarchical Models
11.5 Detection of Clusters of Disease
11.6 Other Topics in Disease MappingNuméro de notice : 20853 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=63150 Réservation
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Titre : Data matching : a matter of belief Type de document : Article/Communication Auteurs : Ana-Maria Olteanu-Raimond , Auteur ; Sébastien Mustière , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2008 Conférence : SDH 2008, 13th international symposium on Spatial Data Handling, Headway in spatial data handling 23/06/2008 25/06/2008 Montpellier France Proceedings Springer Importance : pp 501 - 519 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] appariement de données localisées
[Termes IGN] base de données localisées
[Termes IGN] intégration de données
[Termes IGN] relation topologique
[Termes IGN] réseau routier
[Termes IGN] théorie de Dempster-ShaferRésumé : (Auteur) Nowadays, it is often that a geographic area is described by several independent geographic databases. Yet users need to fusion various information coming from these databases. In order to integrate databases, redundancy and inconsistency between data should be identified. Many steps are required to finalise the databases integration, in particular automatic data matching. In this paper, one approach of matching geographic data bearing on the belief theory is presented. This approach consists in combining criteria from knowledge such as geometry, orientation, nature of roads, names and topology. Then it is tested on heterogeneous network representing roads. Numéro de notice : C2008-003 Affiliation des auteurs : COGIT (1988-2011) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-540-68566-1_29 En ligne : https://doi.org/10.1007/978-3-540-68566-1_29 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65038 PermalinkGeometrical geodesy / M. Hooijberg (2008)PermalinkGNSS, Global Navigation Satellite Systems / Bernhard Hofmann-Wellenhof (2008)PermalinkPermalinkModélisation et statistique spatiales / Carlo Gaetan (2008)PermalinkPermalinkThe European Information Society : Taking Geoinformation Science One Step Further, AGILE 2008 / Lars Bernard (2008)PermalinkAutomatic extraction and classification of vegetation areas from high resolution images in urban areas / Corina Iovan (2007)PermalinkPermalinkPermalink