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Abstracting geographic information in a data rich world / Dirk Burghardt (2014)
Titre : Abstracting geographic information in a data rich world : Methodologies and applications of map generalisation Type de document : Monographie Auteurs : Dirk Burghardt, Éditeur scientifique ; Cécile Duchêne , Éditeur scientifique ; William A Mackaness, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2014 Collection : Lecture notes in Geoinformation and Cartography, ISSN 1863-2246 Importance : 408 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-319-00202-6 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] généralisation cartographique automatisée
[Termes IGN] généralisation de base de données
[Termes IGN] intégration de données
[Termes IGN] spécification de contenu
[Termes IGN] structure de données localisées
[Termes IGN] système d'information géographique
[Vedettes matières IGN] GénéralisationRésumé : (Editeur) Research in the field of automated generalisation has faced new challenges in recent years as a result of technological developments in web-based processing, new visualisation paradigms and access to very large volumes of multi-source data generated by sensors and humans. In these contexts, map generalisation needs to underpin ‘on-demand mapping’, a form of mapping that responds to individual user requirements in the thematic selection and visualisation of geographic information. It is this new impetus that drives the research of the ICA Commission on Generalisation and Multiple Representation (for example through its annual workshops, biannual tutorials and publications in international journals). This book has a coherent structure, each chapter focusing on core concepts and tasks in the map generalisation towards on-demand mapping. Each chapter presents a state-of-the-art review, together with case studies that illustrate the application of pertinent generalisation methodologies. The book addresses issues from data gathering to multi scaled outputs. Thus there are chapters devoted to defining user requirements in handling specifications, and in the application and evaluation of map generalisation algorithms. It explores the application of generalisation methodologies in the context of growing volumes of data and the increasing popularity of user generated content. Note de contenu : 1. Map Generalisation: Fundamental to the Modelling and Understanding of Geographic Space.
2. Map Specifications and User Requirements.
3. Modelling Geographic Relationships in Automated Environments
4. Data Structures for Continuous Generalisation: tGAP and SSC.
5. Integrating and Generalising Volunteered Geographic Information
6. Generalisation Operators
7. Process Modelling, Web Services and Geoprocessing.
8. Terrain Generalisation.
9. Evaluation in Generalisation
10. Generalisation in the Context of Schematised Maps
11. Generalisation in Practice Within National Mapping Agencies
12. Conclusion: Major Achievements and Research Challenges in GeneralisationNuméro de notice : 22152 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Recueil / ouvrage collectif nature-HAL : DirectOuvrColl/Actes DOI : 10.1007/978-3-319-00203-3 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73835 Contient
- Abstracting geographic information in a data rich world, ch. 1. Map generalisation: fundamental to the modelling and understanding of geographic space / William A Mackaness (2014)
- Abstracting geographic information in a data rich world, ch. 2. Map specifications and user requirements / Sandrine Balley (2014)
- Abstracting geographic information in a data rich world, ch. 3. Modelling geographic relationships in automated environments / Guillaume Touya (2014)
- Abstracting geographic information in a data rich world, ch. 7. Process modelling, web services and geoprocessing / Nicolas Regnauld (2014)
- Abstracting geographic information in a data rich world, ch. 11. Generalisation in practice within national mapping agencies / Cécile Duchêne (2014)
- Abstracting geographic information in a data rich world, ch. 12. Conclusion: major achievements and research challenges in generalisation / Dirk Burghardt (2014)
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Code-barres Cote Support Localisation Section Disponibilité 22152-01 37.10 Livre Centre de documentation Géomatique Disponible 22152-02 37.10 Livre Centre de documentation Géomatique Disponible
Titre : Cartographic generalisation aware of multiple representations Type de document : Article/Communication Auteurs : Jean-François Girres , Auteur ; Guillaume Touya , Auteur Editeur : Vienne [Autriche] : Vienna University of Technology Année de publication : 2014 Collection : GeoInfo series num. 40 Conférence : GIScience 2014, 8th international conference on geographic information science 23/09/2014 26/09/2014 Vienne Autriche Proceedings Springer Importance : pp 286 - 291 Langues : Anglais (eng) Descripteur : [Termes IGN] généralisation cartographique automatisée
[Termes IGN] représentation multiple
[Vedettes matières IGN] GénéralisationMots-clés libres : mr-aware Numéro de notice : C2014-008 Affiliation des auteurs : LASTIG COGIT (2012-2019) Thématique : GEOMATIQUE Nature : Poster nature-HAL : Poster-avec-CL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78484 Documents numériques
en open access
Cartographic generalisation awareAdobe Acrobat PDF
Titre : Collaboration on an ontology for generalisation Type de document : Article/Communication Auteurs : Nick Gould, Auteur ; William A Mackaness, Auteur ; Guillaume Touya , Auteur ; Glen Hart, Auteur Editeur : ICA Commission on Generalisation and Multiple Representation Année de publication : 2014 Conférence : ICA 2014, 17th workshop on Generalisation and Multiple Representation 22/09/2014 26/09/2014 Vienne Autriche Open access proceedings Importance : 9 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de généralisation
[Termes IGN] base de connaissances
[Termes IGN] cartographie collaborative
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] ontologie
[Vedettes matières IGN] GénéralisationRésumé : (auteur) To move beyond the current plateau in automated cartography, we need greater sophistication in the process of selecting generalisation algorithms. This is particularly so in the context of machine comprehension. We also need to build on existing algorithm development instead of duplication. More broadly, we need to model the geographical context that drives the selection, sequencing and degree of application of generalisation algorithms. We argue that a collaborative effort is required to create and share an ontology for cartographic generalisation focused on supporting the algorithm selection process. The benefits of developing a collective ontology will be the increased sharing of algorithms and support for on-demand mapping and generalisation web services. Numéro de notice : C2014-011 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : http://generalisation.icaci.org/index.php/prevevents/11-previous-events-details/ [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78486 Documents numériques
en open access
Collaboration on an Ontology for GeneralisationAdobe Acrobat PDF Fully automated generalization of a 1:50k map from 1:10k data / Jantien E. Stoter in Cartography and Geographic Information Science, vol 41 n° 1 (January 2014)
[article]
Titre : Fully automated generalization of a 1:50k map from 1:10k data Type de document : Article/Communication Auteurs : Jantien E. Stoter, Auteur ; Marc Post, Auteur ; Vincent Van Altena, Auteur ; Ron Nijhuis, Auteur ; Ben Bruns, Auteur Année de publication : 2014 Article en page(s) : pp 1 - 13 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] 1:10.000
[Termes IGN] 1:50.000
[Termes IGN] carte topographique
[Termes IGN] chaîne de production
[Termes IGN] données multiéchelles
[Termes IGN] données topographiques
[Termes IGN] généralisation automatique de données
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] Pays-Bas
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) This article presents research that implements a fully automated workflow to generalize a 1:50k map from 1:10k data. This is the first time that a complete topographic map has been generalized without any human interaction. More noteworthy is that the resulting map is good enough to replace the existing map. Specifications for the automated process were established as part of this research. Replication of the existing map was not the aim, because feasibility of automated generalization is better when compliance with traditional generalizations rules is loosened and alternate approaches are acceptable. Indeed, users valued the currency and relevancy of geographical information more than complying with all existing cartographic guidelines. The development of the workflow thus started with the creation of a test map with automated generalization operations. The reason for the test map was to show what is technologically possible and to refine the results based on iterative users’ evaluation. The generalization operations (200 in total) containing the relevant algorithms and parameter values were developed and implemented in one model. Particular effort was made to enrich the source data in order to improve the results. The model is context aware which means it is able to apply different algorithms or adjust parameter values in accordance with a specific area. The result of the research is a fully automated generalization workflow that produces a countrywide map at scale 1:50k from 1:10k data in 50 hours. A fully automated workflow may be the only way to produce flexible and on-demand products; consequently, the results were implemented as a new production line in 2013. Issues for further research have been identified. Numéro de notice : A2014-183 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/15230406.2013.824637 En ligne : https://doi.org/10.1080/15230406.2013.824637 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33088
in Cartography and Geographic Information Science > vol 41 n° 1 (January 2014) . - pp 1 - 13[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Individual road generalisation in the 1997-2000 AGENT European project / Cécile Duchêne (August 2014)
Titre : Individual road generalisation in the 1997-2000 AGENT European project Type de document : Rapport Auteurs : Cécile Duchêne , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : August 2014 Importance : 20 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] AGENT
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] réseau routier
[Vedettes matières IGN] GénéralisationRésumé : (auteur) This paper explores the application of an agent based methodology to the problem of automated road generalisation. It focuses on the generalisation of one single road feature in the case of winding mountain roads, and its implications on the surrounding road network. The aim is to ensure legibility of the road symbol under scale changes, i.e. mainly to avoid coalescence. The solution proposed here is based on the multi-agent framework developed as part of the European AGENT project. It uses a previous approach in automated road generalisation that consists of decomposing the road into parts in order to isolate the coalesced portions, and then handle those portions individually with tailored algorithms. The paper presents the decomposition process in terms of agent modelling. A worked example of the process is presented. A discussion of the results includes comparison with other possible approaches to automated road generalisation. Numéro de notice : 17696 Affiliation des auteurs : LASTIG COGIT (2012-2019) Thématique : GEOMATIQUE Nature : Rapport de recherche nature-HAL : RappRech DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78527 Documents numériques
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RapportAdobe Acrobat PDF PermalinkUne expérience de généralisation de réseau routier dans un dispositif de production / Jérémy Renard in Cartes & Géomatique, n° 217 (septembre 2013)PermalinkBuilding pattern recognition in topographic data: examples on collinear and curvilinear alignments / Xiang Zhang in Geoinformatica, vol 17 n° 1 (January 2013)PermalinkPermalinkImproving multi-level interactions modelling in a multi-agent generalisation model: first experiments / Adrien Maudet (2013)PermalinkPermalinkPermalinkA symmetry detector for map generalization and urban-space analysis / Jan‐Henrik Haunert in ISPRS Journal of photogrammetry and remote sensing, vol 74 (Novembrer 2012)PermalinkThe CARTACOM model : transforming cartographic features into communicating agents for cartographic generalization / Cécile Duchêne in International journal of geographical information science IJGIS, vol 26 n° 9-10 (September - october 2012)PermalinkImproving map generalisation with new pruning heuristics / Patrick Taillandier in International journal of geographical information science IJGIS, vol 26 n° 7-8 (july - august 2012)Permalink