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AlpineBends – A benchmark for deep learning-based generalisation / Azelle Courtial (2022)  

Public Titre : AlpineBends – A benchmark for deep learning-based generalisation Type de document : Article/Communication Auteurs : Azelle Courtial , Auteur ; Guillaume Touya , Auteur ; Xiang Zhang, Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2022 Collection : Abstracts of the ICA num. 4 Projets : 1-Pas de projet / Conférence : ICA 2021, 24th ICA Workshop on Map Generalisation and Multiple Representation 13/12/2021 13/12/2021 Florence Italie OA Proceedings Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond [Termes IGN] données maillées [Termes IGN] objet géographique [Termes IGN] test de performance [Vedettes matières IGN] Généralisation Résumé : (auteur) [début] Raster-based map generalization is nowadays anecdotal, as most generalization operations are performed using vector data. Vectors describe the shape of each object in the map using a set of coordinates; thus, the object delimitation is directly accessible, and the topology and distance-based relations are easy to compute. On the contrary, rasters represent a map as an image, a grid of pixel covers the target area, and each pixel is characterised by a value. This representation does not explicitly model the boundary/shape of geographic objects and the relations between them. However, the emergence of the image-based deep learning techniques has shown an ability to process images of geographic information. The question of their adaptation for map generalization is a trendy subject: road (Courtial et al. 2020), building (Feng et al. 2019) and coastline (Du et al. 2021) generalization have been explored in recent years. Common methods for evaluating these techniques seems to be necessary for the comparison and development of this field. Numéro de notice : C2021-067 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-abs-4-1-2022 Date de publication en ligne : 14/01/2022 En ligne : https://doi.org/10.5194/ica-abs-4-1-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99535

BasqueRoads: a benchmark for road network selection / Guillaume Touya (2022)  

Public Titre : BasqueRoads: a benchmark for road network selection Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Azelle Courtial , Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2022 Collection : Abstracts of the ICA num. 4 Projets : LostInZoom / Touya, Guillaume Conférence : ICA 2021, 24th ICA Workshop on Map Generalisation and Multiple Representation 13/12/2021 13/12/2021 Florence Italie OA Proceedings Note générale : bibliographie This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 101003012). Langues : Anglais (eng) Descripteur : [Termes IGN] objet géographique [Termes IGN] réseau routier [Termes IGN] simplification de contour [Termes IGN] test de performance [Vedettes matières IGN] Généralisation Résumé : (auteur) [début] Road network selection is one of the major issues of map generalisation, as new papers are proposed every year since the first attempts of automation in the 1990’s (Thomson & Richardson, 1995). New methods are regularly proposed because selecting roads for maps at smaller scales is a complex problem. Roads are at the same time present in maps to enable car navigation tasks, and because they are structuring elements that reveal the nature of the landscape (urban, rural, mountainous…). So road selection is not only about retaining the most important roads of the network, but the preservation of topology and connectivity is essential, as well as the preservation, or the typification of road patterns (e.g. a ring road), and the preservation of local density differences (between urban and rural areas for instance). It is rare to see comparisons of road selection techniques in the literature, because of the lack of open source in map generalisation, but also because of the lack of a common dataset to benchmark these techniques; new propositions on road selection are most of the time tied to their own dataset and use case. This is why we think that this BasqueRoads dataset could be useful to advance on this topic of road network selection. Numéro de notice : C2021-066 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-abs-4-5-2022 Date de publication en ligne : 14/01/2022 En ligne : https://doi.org/10.5194/ica-abs-4-5-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99536

Deep learning for anchor detection in multi-scale maps / Quentin Potié (2022)  

Public Titre : Deep learning for anchor detection in multi-scale maps Type de document : Article/Communication Auteurs : Quentin Potié , Auteur ; Guillaume Touya , Auteur ; Chaimaa Beladraoui, Auteur ; Amina El-Moutaouakkil, Auteur ; William A Mackaness, Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2022 Collection : Abstracts of the ICA num. 5 Projets : LostInZoom / Touya, Guillaume Conférence : EuroCarto 2022, European Cartographic Conference 19/09/2022 21/09/2022 Vienne Autriche OA Proceedings Note générale : bibliographie This project has received funding from the European Research Council (ERC) under the European Union‟s Horizon 2020 research and innovation programme (grant agreement No. 101003012) Langues : Anglais (eng) Descripteur : [Termes IGN] ancre [Termes IGN] apprentissage profond [Termes IGN] point de repère [Termes IGN] reconnaissance de formes [Termes IGN] visualisation multiéchelle [Vedettes matières IGN] Généralisation Numéro de notice : C2022-037 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-abs-5-82-2022 Date de publication en ligne : 14/09/2022 En ligne : http://dx.doi.org/10.5194/ica-abs-5-82-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101622

A web GIS to generate audio-tactile maps for visually impaired people / Guillaume Touya (2022)  

Public Titre : A web GIS to generate audio-tactile maps for visually impaired people Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Samuel Braikeh, Auteur ; Ridley Campbell, Auteur ; Jean-Marie Favreau, Auteur ; Jérémy Kalsron, Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2022 Collection : Abstracts of the ICA num. 5 Projets : ACTIVmap / Favreau, Jean-Marie Conférence : EuroCarto 2022, European Cartographic Conference 19/09/2022 21/09/2022 Vienne Autriche OA Proceedings Langues : Anglais (eng) Descripteur : [Termes IGN] carte tactile [Termes IGN] personne malvoyante [Termes IGN] WebSIG [Vedettes matières IGN] Généralisation Numéro de notice : C2022-038 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-abs-5-115-2022 Date de publication en ligne : 14/09/2022 En ligne : http://dx.doi.org/10.5194/ica-abs-5-115-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101621

L’Alpe d’Huez: A benchmark for topographic map generalisation / Guillaume Touya (2021)  

Public Titre : L’Alpe d’Huez: A benchmark for topographic map generalisation Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2021 Conférence : ICA 2021, 24th ICA Workshop on Map Generalisation and Multiple Representation 13/12/2021 13/12/2021 Florence Italie OA Proceedings Importance : 2 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Français (fre) Descripteur : [Termes IGN] bâtiment [Termes IGN] CartAGen (plateforme de généralisation) [Termes IGN] carte topographique [Termes IGN] généralisation cartographique [Termes IGN] Institut national de l'information géographique et forestière (France) [Termes IGN] test de performance [Vedettes matières IGN] Généralisation Résumé : (auteur) L’Alpe d’Huez is a ski resort in the French Alps, and it is also famous among cyclists for the number of bends in the road to the ski resort. It is a good location to evaluate the capabilities of map generalisation tools, as the surroundings contain urban, rural and mountainous areas, and it was chosen 15 years ago as one of the four datasets to benchmark map generalisation software (Stoter et al., 2009). The EuroSDR benchmark used data from IGN France, the French National Mapping Agency (NMA). At that time, open science policies were not popular in NMAs, but now they release their dataset with open licenses, so it is a good opportunity to create an open benchmark for topographic map generalisation. Numéro de notice : C2021-065 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://hal.science/hal-03522475/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99524

An attempt to define perceptive and sensitive mapping through lived space experiments / Catherine Dominguès (2021)  

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Can graph convolution networks learn spatial relations? / Azelle Courtial (2021)  

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Cluttering reduction for interactive navigation and visualization of historical Images / Evelyn Paiz-Reyes (2021)  

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Content-based image retrieval for map georeferencing / Jonas Luft (2021)  

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COVID-19 geoviz for spatio-temporal structures detection / Jacques Gautier (2021)  

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Definition of the map / Miljenko Lapaine (2021)  

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How do users interact with Virtual Geographic Environments? Users’ behavior evaluation in urban participatory planning / Thibaud Chassin (2021)  

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Lessons learned from a VGI initiative for Land Use monitoring / Ana-Maria Olteanu-Raimond (2021)  

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Lived and perceived space during lock-down in a sensitive map approach / Laurence Jolivet (2021)  

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Mapping and characterizing animals’ places of interest in forest environment / Laurence Jolivet (2021)  

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