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Is deep learning the new agent for map generalization? / Guillaume Touya in International journal of cartography, vol 5 n° 2-3 (July - November 2019)  

Public [article]  inInternational journal of cartography > vol 5 n° 2-3 (July - November 2019) . - pp 142 - 157 Titre : Is deep learning the new agent for map generalization? Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Xiang Zhang, Auteur ; Imran Lokhat , Auteur Congrès : Congrès: ICC 2019, 29th International Cartographic Conference ICA Mapping everything for everyone (15 - 20 juillet 2019; Tokyo, Japon) , Commanditaire Année de publication : 2019 Projets : 1-Pas de projet / Article en page(s) : pp 142 - 157 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] système multi-agents [Vedettes matières IGN] Généralisation Résumé : (Auteur) The automation of map generalization has been keeping researchers in cartography busy for years. Particularly great progress was made in the late 90s with the use of the multi-agent paradigm. Although the current use of automatic processes in some national mapping agencies is a great achievement, there are still many unsolved issues and research seems to stagnate in the recent years. With the success of deep learning in many fields of science, including geographic information science, this paper poses the controversial question of the title: is deep learning the new agent, i.e. the technique that will make generalization research bridge the gap to fully automated generalization processes? The paper neither responds a clear yes nor a clear no but discusses what issues could be tackled with deep learning and what the promising perspectives. Some preliminary experiments with building generalization or data enrichments are presented to support the discussion. Numéro de notice : A2019-235 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2019.1613071 date de publication en ligne : 09/05/2019 En ligne : https://doi.org/10.1080/23729333.2019.1613071 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92932 [article]

Automatic derivation of on-demand tactile maps for visually impaired people: first experiments and research agenda / Guillaume Touya in International journal of cartography, vol 5 n° 1 (2019)  

Public [article]  inInternational journal of cartography > vol 5 n° 1 (2019) Titre : Automatic derivation of on-demand tactile maps for visually impaired people: first experiments and research agenda Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Sidonie Christophe , Auteur ; Jean-Marie Favreau, Auteur ; Mohamed Amine Ben Rhaiem, Auteur Année de publication : 2019 Projets : 1-Pas de projet / Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] automatisation [Termes descripteurs IGN] carte sur mesure [Termes descripteurs IGN] carte tactile [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] impression 3D [Termes descripteurs IGN] malvoyant [Termes descripteurs IGN] style cartographique [Vedettes matières IGN] Généralisation Résumé : (auteur) Tactile maps are essential tools for visually impaired people to comprehend space and to support the simple pedestrian trips made difficult by their disability. Tactile maps are created manually and printed by specialists, and it takes a large amount of time to create a new one, which prevents using them on demand for everyday use. As a consequence, researchers and cartographers try to automate this creation process, but the existing automated derivation processes do not include generalization or advanced stylization steps, which limits their effectiveness. This paper reports first experiments to include such complex automated cartography processes to provide on-demand tactile maps for visually impaired people. These first experiments were more intended to raise real research issues than solve them, and the paper discusses these issues in a research agenda to achieve automatically derived tactile maps. Numéro de notice : A2018-379 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2018.1486784 date de publication en ligne : 07/08/2018 En ligne : https://doi.org/10.1080/23729333.2018.1486784 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90797 [article]

CartAGen: an open source research platform for map generalization / Guillaume Touya (2019)    

Public Titre : CartAGen: an open source research platform for map generalization Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Imran Lokhat , Auteur ; Cécile Duchêne , Auteur Congrès : Congrès: ICC 2019, 29th International Cartographic Conference ICA Mapping everything for everyone (15 - 20 juillet 2019; Tokyo, Japon) , Commanditaire Editeur : International Cartographic Association ICA Année de publication : 2019 Autre Editeur : Göttingen : Copernicus publications Collection : Proceedings of the ICA Projets : 1-Pas de projet / Importance : 9 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme de généralisation [Termes descripteurs IGN] CartAGen (plateforme de généralisation) [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] logiciel libre [Termes descripteurs IGN] organisme cartographique national [Termes descripteurs IGN] plateforme logicielle [Termes descripteurs IGN] système multi-agents [Vedettes matières IGN] Généralisation Résumé : (Auteur) Automatic map generalization is a complex task that is still a research problem and requires the development of research prototypes before being usable in productive map processes. In the meantime, reproducible research principles are becoming a standard. Publishing reproducible research means that researchers share their code and their data so that other researchers might be able to reproduce the published experiments, in order to check them, extend them, or compare them to their own experiments. Open source software is a key tool to share code and software, and CartAGen is the first open source research platform that tackles the overall map generalization problem: not only the building blocks that are generalization algorithms, but also methods to chain them, and spatial analysis tools necessary for data enrichment. This paper presents the CartAGen platform, its architecture and its components. The main component of the platform is the implementation of several multi-agent based models of the literature such as AGENT, CartACom, GAEL, CollaGen, or DIOGEN. The paper also explains and discusses different ways, as a researcher, to use or to contribute to CartAGen. Numéro de notice : C2019-010 Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-proc-2-134-2019 date de publication en ligne : 10/07/2019 En ligne : https://doi.org/10.5194/ica-proc-2-134-2019 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93258

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Finding the oasis in the desert fog? Understanding multi-scale map reading / Guillaume Touya (2019)    

Public Titre : Finding the oasis in the desert fog? Understanding multi-scale map reading Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur Congrès : ICC 2019 Workshop on Abstraction, Scale and Perception (15 - 20 juillet 2019; Tokyo, Japon), Commanditaire Editeur : International Cartographic Association ICA Année de publication : 2019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] échelle cartographique [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] représentation mentale spatiale [Termes descripteurs IGN] représentation multiple [Termes descripteurs IGN] zoom [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Fluid interactions of complex information visualizations promote flow by giving “a sense of control” and a loss of self-consciousness” during the interaction (Elmqvist et al., 2011).In the context of multi-scale geovisualization with different maps rendered at different zoom levels, fluid interactions mainly consist in smoothly zooming in the scales/zoom levels, while keeping a constant sense of place. User experience shows that current multi-scale maps are not provided with fluid interactions. Despite recent improvements, zooming in and out of multi-scale maps such as GoogleMaps, OSM, or National Mapping Agencies’ geoportals still causes a desert fog effect (Jul & Furnas, 1998) when the map changes. Desert fog can be defined as “a condition wherein a view of an information world contains no information on which to base navigational decisions.” In a multi-scale map, it means that the abstraction, content and style changes between two maps at different scales make the user lose his sense of place for a short moment wondering where his previous position (i.e. where he was looking at, or where his cursor was) is in the newly rendered map (Dumont et al., 2016). Contributions on continuous generalisation (van Oosterom et al., 2014), or on progressive generalisation (Dumont et al., 2017; Touya & Dumont, 2017) try to provide more continuous or progressive abstractions of map features across scales. [...] Numéro de notice : C2019-019 Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans date de publication en ligne : 14/08/2019 En ligne : https://hal.archives-ouvertes.fr/hal-02266373 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93598

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On the spatial distribution of buildings for map generalization / Zhiwei Wei in Cartography and Geographic Information Science, Vol 45 n° 6 (November 2018)  

Public [article]  inCartography and Geographic Information Science > Vol 45 n° 6 (November 2018) . - pp 539 - 555 Titre : On the spatial distribution of buildings for map generalization Type de document : Article/Communication Auteurs : Zhiwei Wei, Auteur ; Qingsheng Guo, Auteur ; Lin Wang, Auteur ; Fen Yan, Auteur Année de publication : 2018 Article en page(s) : pp 539 - 555 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse en composantes principales [Termes descripteurs IGN] arbre aléatoire minimum [Termes descripteurs IGN] bati [Termes descripteurs IGN] distribution spatiale [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] OpenStreetMap [Vedettes matières IGN] Généralisation Résumé : (Auteur) Information on spatial distribution of buildings must be explored as part of the process of map generalization. A new approach is proposed in this article, which combines building classification and clustering to enable the detection of class differences within a pattern, as well as patterns within a class. To do this, an analysis of existing parameters describing building characteristics is performed via principal component analysis (PCA), and four major parameters (i.e. convex hull area, IPQ compactness, number of edges, and smallest minimum bounding rectangle orientation) are selected for further classification based on similarities between building characteristics. A building clustering method based on minimum spanning tree (MST) considering rivers and roads is then applied. Theory and experiments show that use of a relative neighbor graph (RNG) is more effective in detecting linear building patterns than either a nearest neighbor graph (NNG), an MST, or a Gabriel graph (GssG). Building classification and clustering are therefore conducted separately using experimental data extracted from OpenStreetMap (OSM), and linear patterns are then recognized within resultant clusters. Experimental results show that the approach proposed in this article is both reasonable and efficient for mining information on the spatial distribution of buildings for map generalization. Numéro de notice : A2018-480 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1433068 date de publication en ligne : 15/02/2018 En ligne : https://doi.org/10.1080/15230406.2018.1433068 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91258 [article]

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Recognizing building groups for generalization : a comparative study / Min Deng in Cartography and Geographic Information Science, Vol 45 n° 3 (May 2018)  

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Labelling hierarchy for street maps using centrality measures / Wasim Shoman in Cartographic journal (the), vol 55 n° 1 (February 2018)  

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Multi-agents systems for cartographic generalization: Feedback from past and on-going research / Cécile Duchêne (2018) 

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BinSq : visualizing geographic dot density patterns with gridded maps / Alvin Chua in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)  

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DIOGEN, a multi-level oriented model for cartographic generalization / Adrien Maudet in International journal of cartography, vol 3 n° 1 (June 2017)  

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The bounds of distortion : truth, meaning and efficacy in digital geographic representation / Lucas Godfrey in International journal of cartography, vol 3 n° 1 (June 2017)  

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Variable-scale maps in real-time generalisation using a quadtree data structure and space deforming algorithms / Pia Bereuter in International journal of cartography, vol 3 n° 1 (June 2017)  

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