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Cartographies en mouvement : parcours sensible, narration et participation, ch. 10. Conception de cartes en relief pour les personnes déficientes visuelles / Gauthier Fillières-Riveau (2021)
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Titre de série : Cartographies en mouvement : parcours sensible, narration et participation, ch. 10 Titre : Conception de cartes en relief pour les personnes déficientes visuelles Type de document : Chapitre/Contribution Auteurs : Gauthier Fillières-Riveau , Auteur ; Jean-Marie Favreau, Auteur ; Vincent Barra, Auteur ; Guillaume Touya
, Auteur
Editeur : Clermont-Ferrand : Presses universitaires Blaise Pascal Année de publication : 2021 Collection : Territoires Projets : ACTIVmap / Favreau, Jean-Marie Importance : pp Note générale : bibliographie
ouvrage sous la coordination de Mauricette Fournier et Florence Troin
SIGNALEMENT - PAS DE DOCUMENTLangues : Français (fre) Descripteur : [Vedettes matières IGN] Cartographie
[Termes IGN] carte en relief
[Termes IGN] conception cartographique
[Termes IGN] personne malvoyanteNuméro de notice : H2021-003 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Chapître / contribution nature-HAL : ChOuvrScient DOI : sans Date de publication en ligne : 14/10/2021 En ligne : https://hal.science/hal-03401368v1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98939 Combining deep learning and mathematical morphology for historical map segmentation / Yizi Chen (2021)
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Titre : Combining deep learning and mathematical morphology for historical map segmentation Type de document : Chapitre/Contribution Auteurs : Yizi Chen , Auteur ; Edwin Carlinet, Auteur ; Joseph Chazalon, Auteur ; Clément Mallet
, Auteur ; Bertrand Duménieu
, Auteur ; Julien Perret
, Auteur
Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2021 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 12708 Projets : SODUCO / Perret, Julien Conférence : DGMM 2021, 1st International Joint Conference on Discrete Geometry and Mathematical Morphology 24/05/2021 27/05/2021 Uppsala Suède Proceedings Springer Importance : pp 79 - 92 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse diachronique
[Termes IGN] apprentissage profond
[Termes IGN] carte ancienne
[Termes IGN] chaîne de traitement
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] données maillées
[Termes IGN] morphologie mathématique
[Termes IGN] vectorisationRésumé : (auteur) The digitization of historical maps enables the study of ancient, fragile, unique, and hardly accessible information sources. Main map features can be retrieved and tracked through the time for subsequent thematic analysis. The goal of this work is the vectorization step, i.e., the extraction of vector shapes of the objects of interest from raster images of maps. We are particularly interested in closed shape detection such as buildings, building blocks, gardens, rivers, etc. in order to monitor their temporal evolution. Historical map images present significant pattern recognition challenges. The extraction of closed shapes by using traditional Mathematical Morphology (MM) is highly challenging due to the overlapping of multiple map features and texts. Moreover, state-of-the-art Convolutional Neural Networks (CNN) are perfectly designed for content image filtering but provide no guarantee about closed shape detection. Also, the lack of textural and color information of historical maps makes it hard for CNN to detect shapes that are represented by only their boundaries. Our contribution is a pipeline that combines the strengths of CNN (efficient edge detection and filtering) and MM (guaranteed extraction of closed shapes) in order to achieve such a task. The evaluation of our approach on a public dataset shows its effectiveness for extracting the closed boundaries of objects in historical maps. Numéro de notice : H2021-001 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Chapître / contribution nature-HAL : ChOuvrScient DOI : 10.1007/978-3-030-76657-3_5 Date de publication en ligne : 16/05/2021 En ligne : https://hal.science/hal-03101578v1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96739
Titre : Content-based image retrieval for map georeferencing Type de document : Article/Communication Auteurs : Jonas Luft, Auteur ; Jochen Schiewe, Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2021 Collection : Proceedings of the ICA num. 4 Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie Proceedings Springer Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] appariement d'images
[Termes IGN] carte ancienne
[Termes IGN] carte numérisée
[Termes IGN] carte topographique
[Termes IGN] données localisées des bénévoles
[Termes IGN] géoréférencement indirect
[Termes IGN] mesure de similitude
[Termes IGN] recherche d'image basée sur le contenuRésumé : (auteur) In recent years, libraries have made great progress in digitising troves of historical maps with high-resolution scanners. Providing user-friendly information access for cultural heritage through spatial search and webGIS requires georeferencing of the hundreds of thousands of digitised maps. Georeferencing is usually done manually by finding “ground control points”, locations in the digital map image, whose identity is unambiguous and can easily be found in modern-day reference geodata/mapping data. To decide whether two symbols from different maps describe the same object, their semantic and spatial relations need to be matched. Automating this process is the only feasible way to georeference the immense quantities of maps in conceivable time. However, automated solutions for spatial matching quickly fail when faced with incomplete data – which is the greatest challenge when comparing maps of different ages or scales. These problems can be overcome by computing map similarity in the image domain. Treating maps as a special case of image processing allows efficient and robust matching and thus identification of geographical regions without the need to explicitly model semantics. We propose a method to encode worldwide reference VGI mapping data as image features, allowing the construction of an efficient lookup index. With this index, content-based image retrieval can be used for both geolocating a given map for georeferencing with high accuracy. We demonstrate our approach on hundreds of map sheets of different historical topographical survey map series, successfully georeferencing most of them within mere seconds. Numéro de notice : C2021-073 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Communication DOI : 10.5194/ica-proc-4-69-2021 Date de publication en ligne : 03/12/2021 En ligne : https://doi.org/10.5194/ica-proc-4-69-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100007
Titre : Contextual land-cover map translation with semantic segmentation Type de document : Article/Communication Auteurs : Luc Baudoux , Auteur ; Jordi Inglada, Auteur ; Clément Mallet
, Auteur
Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2021 Projets : MAESTRIA / Mallet, Clément Conférence : IGARSS 2021, IEEE International Geoscience And Remote Sensing Symposium 11/07/2021 16/07/2021 Bruxelles Belgique Proceedings IEEE Importance : pp 2488 - 2491 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] base de données d'occupation du sol
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] Corine Land Cover
[Termes IGN] France (administrative)
[Termes IGN] segmentation sémantique
[Termes IGN] transformation géométrique
[Termes IGN] translationRésumé : (auteur) This paper presents a framework for translating a land-cover map into another one in a supervised way. This links to numerous applications (updating, completion, etc.). Conversely to existing approaches, we jointly perform spatial and semantic transformation without any prior knowledge. The proposed method assumes that: i) examples of the source and target maps already exist, ii) the spatial resolution of the source map is equal or higher than the target one. The translation is performed using an asymmetric Convolutional Neural Network with positional encoding. Experimental results show the effectiveness of the method in retrieving a yearly version of Corine Land Cover (CLC) at country-scale (France) using an existing high-resolution map and with similar accuracy than existing CLC maps (~80%). Numéro de notice : C2021-049 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS47720.2021.9553693 Date de publication en ligne : 12/10/2021 En ligne : https://doi.org/10.1109/IGARSS47720.2021.9553693 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99414
Titre : Definition of the map Type de document : Article/Communication Auteurs : Miljenko Lapaine, Auteur ; Terje Midtbo, Auteur ; Georg Gartner, Auteur ; Temenoujka Bandrova, Auteur ; Tao Wang, Auteur ; Jie Shen, Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2021 Collection : Advances in cartography and GIScience num. 3 Importance : 6 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte
[Termes IGN] cartographe
[Termes IGN] cartographie
[Termes IGN] terminologie
[Vedettes matières IGN] CartologieRésumé : (auteur) Cartography has undergone great changes in the last 40 years. Many web platforms and location-based services are offering increasing opportunities, paper maps have been largely supplemented by multimedia and digital maps, and spatial databases. The definition of a map has changed throughout history and the differences in their definitions are presented. This paper aims for new central cartographic definitions, corresponding to contemporary cartographic development after presenting the current situation of the topic. Definitions of cartographic mapping, cartography and cartographer are proposed, as well as a new definition of the map. All they are made on the base of logical analyses including different types of maps from traditional and real to virtual, 3D, animation, and digital. Numéro de notice : C2021-050 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Communication DOI : 10.5194/ica-adv-3-9-2021 Date de publication en ligne : 29/11/2021 En ligne : https://doi.org/10.5194/ica-adv-3-9-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99436 Development and analysis of land-use/land-cover spatio-temporal metrics in urban environments: Exploring urban growth patterns and linkages to socio-economic factors / Marta Sapena Moll (2021)
PermalinkDiurnal cycles of C-band temporal coherence and backscattering coefficient over an olive orchard in a semi-arid area: Comparison of in situ and Sentinel-1 radar observations / Adnane Chakir (2021)
PermalinkDiurnal cycles of C-band temporal coherence and backscattering coefficient over a wheat field in a semi-arid area / Nadia Ouaadi (2021)
PermalinkDrought propagation and its impact on groundwater hydrology of wetlands: a case study on the Doode Bemde nature reserve (Belgium) / Buruk Kitachew Wossenyeleh in Natural Hazards and Earth System Sciences, vol 21 n° 1 (January 2021)
PermalinkPermalinkExamining the effectiveness of Sentinel-1 and 2 imagery for commercial forest species mapping / Mthembeni Mngadi in Geocarto international, vol 36 n° 1 ([01/01/2021])
PermalinkExtraction of street pole-like objects based on plane filtering from mobile LiDAR data / Jingming Tu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)
PermalinkFrom local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 / Yousra Hamrouni in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)
PermalinkGenerative adversarial networks to generalise urban areas in topographic maps / Azelle Courtial (2021)
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