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Is the radial distance really a distance? An analysis of its properties and interest for the matching of polygon features / Yann Méneroux in International journal of geographical information science IJGIS, vol 37 n° 2 (February 2023)
Titre : Is the radial distance really a distance? An analysis of its properties and interest for the matching of polygon features Type de document : Article/Communication Auteurs : Yann Méneroux Année de publication : 2023 Projets : 3-projet - voir note / Article en page(s) : pp 438 - 475 Note générale : bibliographie
This work was supported by the French National Mapping Agency: Institut National de l’Information Géographique et Forestière (IGN) and by the University of DjiboutiLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] abaque
[Termes IGN] algorithme de Douglas-Peucker
[Termes IGN] appariement de formes
[Termes IGN] bâtiment
[Termes IGN] BD Topo
[Termes IGN] distance
[Termes IGN] généralisation
[Termes IGN] géométrie analytique
[Termes IGN] modèle analytique
[Termes IGN] polygone
[Termes IGN] propagation d'erreur
[Termes IGN] transformation rapide de FourierRésumé : (auteur) In this paper, we examine the properties of the radial distance which has been used as a tool to compare the shape of simple surfacic objects. We give a rigorous definition of the radial distance and derive its theoretical properties, and in particular under which conditions it satisfies the distance properties. We show how the computation of the radial distance can be implemented in practice and made faster by the use of an analytical formula and a Fast Fourier Transform. Finally, we conduct experiments to measure how the radial distance is impacted by perturbation and generalization and we give abacuses and thresholds to deduce when buildings are likely to be homologous or non-homologous given their radial distance. Numéro de notice : A2023-074 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2123487 Date de publication en ligne : 23/09/2022 En ligne : https://doi.org/10.1080/13658816.2022.2123487 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101671
in International journal of geographical information science IJGIS > vol 37 n° 2 (February 2023) . - pp 438 - 475[article]
Titre : Searching for an optimal hexagonal shaped enumeration unit size for effective spatial pattern recognition in choropleth maps Type de document : Article/Communication Auteurs : Izabela Karsznia, Auteur ; Izabela Golebiowska, Auteur ; Jolanta Korycka-Skorupa, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 576 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique
[Termes IGN] analyse spatiale
[Termes IGN] carte choroplèthe
[Termes IGN] carte thématique
[Termes IGN] échelle cartographique
[Termes IGN] enquête
[Termes IGN] généralisation
[Termes IGN] lecture de carte
[Termes IGN] reconnaissance de formes
[Termes IGN] répartition géographique
[Termes IGN] représentation cartographique
[Termes IGN] utilisateur
[Termes IGN] visualisation cartographiqueRésumé : (auteur) Thoughtful consideration of the enumeration unit size in choropleth map design is important to ensure the correct communication of spatial information. However, the enumeration unit size and its influence on pattern conveying in choropleth maps have not yet been the subject of in-depth empirical studies. This research aims to address this gap. We focused on the issue concerning whether the ability to recognize spatial patterns on an Equal Area Unit Map is related to the hexagonal enumeration unit size, defined by the number of pixels. The aim is to indicate the range of the enumeration unit sizes, namely, at what point the upper and lower borders of the range where the spatial patterns start, and where the end is visible and recognizable by users. To address this problem, we conducted an empirical study with 488 users. The results show that the enumeration unit size has an impact on the users’ spatial pattern recognition abilities. Choropleth maps with enumeration unit sizes of 26, 52, and 104 pixels were, in the majority, indicated by participants as those most suitable for indicating spatial patterns. This was in contrast to choropleth maps with enumeration unit sizes of 1664 and 3328 pixels, which users indicated as not being useful. However, there were some exceptions to this general finding. Thus, determining the optimal enumeration unit size is a challenging task, and requires further insightful investigations. Numéro de notice : A2021-686 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10090576 Date de publication en ligne : 25/08/2021 En ligne : https://doi.org/10.3390/ijgi10090576 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98412
in ISPRS International journal of geo-information > vol 10 n° 9 (September 2021) . - n° 576[article]
Titre : Inferring the scale and content of a map using deep learning Type de document : Article/Communication Auteurs : Guillaume Touya Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2020 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B4 Projets : ACTIVmap / Favreau, Jean-Marie Conférence : ISPRS 2020, Commission 4, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Archives Commission 4 Importance : pp 17 - 24 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] apprentissage profond
[Termes IGN] carte numérisée
[Termes IGN] carte scolaire
[Termes IGN] carte tactile
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] échelle cartographique
[Termes IGN] formation
[Termes IGN] généralisation
[Termes IGN] géographie physique
[Termes IGN] personne non-voyanteRésumé : (auteur) Visually impaired people cannot use classical maps but can learn to use tactile relief maps. These tactile maps are crucial at school to learn geography and history as well as the other students. They are produced manually by professional transcriptors in a very long and costly process. A platform able to generate tactile maps from maps scanned from geography textbooks could be extremely useful to these transcriptors, to fasten their production. As a first step towards such a platform, this paper proposes a method to infer the scale and the content of the map from its image. We used convolutional neural networks trained with a few hundred maps from French geography textbooks, and the results show promising results to infer labels about the content of the map (e.g. "there are roads, cities and administrative boundaries"), and to infer the extent of the map (e.g. a map of France or of Europe). Numéro de notice : C2020-002 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B4-2020-17-2020 Date de publication en ligne : 24/08/2020 En ligne : https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-17-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95391 Semantic aware quality evaluation of 3D building models : Modeling and simulation / Oussama Ennafii (2019)
Titre : Semantic aware quality evaluation of 3D building models : Modeling and simulation Titre original : Evaluation de la qualité des modèles 3D de bâtiments Type de document : Thèse/HDR Auteurs : Oussama Ennafii Editeur : Champs/Marne : Université Paris-Est Année de publication : 2019 Importance : 238 p. Format : 21 x 30 cm Note générale : bibliographie
Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy delivered by Université Paris-Est, Speciality Geographical Information Sciences and Technologies
Thèse récompensée par le prix 2020 EuroSDR PhD Award.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection d'erreur
[Termes IGN] généralisation
[Termes IGN] image à très haute résolution
[Termes IGN] information sémantique
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle numérique de surface
[Termes IGN] modélisation 3D
[Termes IGN] modélisation du bâti
[Termes IGN] scène urbaine
[Termes IGN] taxinomieIndex. décimale : THESE Thèses et HDR Résumé : (auteur) The automatic generation of 3D building models from geospatial data is now a standard procedure. An abundant literature covers the last two decades and several softwares are now available. However, urban areas are very complex environments. Inevitably, practitioners still have to visually assess, at city-scale, the correctness of these models and detect frequent reconstruction errors. Such a process relies on experts, and is highly time-consuming with approximately two hours/km² per expert. This work proposes an approach for automatically evaluating the quality of 3D building models. Potential errors are compiled in a novel hierarchical and modular taxonomy. This allows, for the first time, to disentangle fidelity and modeling errors, whatever the level of details of the modeled buildings. The quality of models is predicted using the geometric properties of buildings and, when available, Very High Resolution images and Digital Surface Models. A baseline of handcrafted, yet generic, features is fed into a Random Forest or Support Vector Machine classifiers. Richer features, relying on graph kernels as well as Scattering Networks, were proposed to better take into consideration structure. Both multi-class and multi-label cases are studied: due to the interdependence between classes of errors, it is possible to retrieve all errors at the same time while simply predicting correct and erroneous buildings. The proposed framework was tested on three distinct urban areas in France with more than 3,000 buildings. 80%-99% F-score values are attained for the most frequent errors. For scalability purposes, the impact of the urban area composition on the error prediction was also studied, in terms of transferability, generalization, and representativeness of the classifiers. It shows the necessity of multi-modal remote sensing data and mixing training samples from various cities to ensure a stability of the detection ratios, even with very limited training set sizes. Note de contenu : 1- Introduction
2- State of the art
3- Semantic evaluation of 3D models
4- A learning approach for quality evaluation
5- Assessing the learned approach
6- Computing a better representation
7- Assessing the advanced features
8- ConclusionNuméro de notice : 25860 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Spécialité : Sciences et Technologies de l'Information Géographique : Paris-Est, 2019 Organisme de stage : Lastig (IGN) nature-HAL : Thèse DOI : sans En ligne : https://hal.science/tel-02879809 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95395 Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 25860-02 THESE Livre Centre de documentation Thèses Disponible 25860-01 THESE Livre Centre de documentation Thèses Disponible 25860-03 THESE Livre Centre de documentation Thèses Disponible vol 3 n° 1 - June 2017 - Special issue: International Cartographic Conference 2017 (Bulletin de International journal of cartography) / William Cartwright
est un bulletin de International journal of cartography / Association cartographique internationale (2015 -)
Titre : vol 3 n° 1 - June 2017 - Special issue: International Cartographic Conference 2017 Type de document : Périodique Auteurs : William Cartwright, Éditeur scientifique ; Anne Ruas Année de publication : 2017 Conférence : ICC 2017, 28th International Cartographic Conference ICA 02/07/2017 07/07/2017 Washington DC Etats-Unis OA Proceedings of the ICA Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie
[Termes IGN] cartographie 3D
[Termes IGN] données localisées des bénévoles
[Termes IGN] généralisation
[Termes IGN] géovisualisationNuméro de notice : sans Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Numéro de périodique En ligne : http://www.tandfonline.com/toc/tica20/3/1?nav=tocList Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=28302 [n° ou bulletin]
- An investigation into challenges experienced when route planning, navigating and wayfinding / Erin Koletsis in International journal of cartography, vol 3 n° 1 (June 2017)
- 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)
- Multivariate label-based thematic maps / Richard Brath in International journal of cartography, vol 3 n° 1 (June 2017)
- Fictional volunteered geographic information in Dream Cartography / Cristina M. Iosifescu Enescu in International journal of cartography, vol 3 n° 1 (June 2017)
- User testing of dynamic geovisualizations : lessons learned and possible improvements for cartographic experiments / Cécile Saint-Marc in International journal of cartography, vol 3 n° 1 (June 2017)
- DIOGEN, a multi-level oriented model for cartographic generalization / Adrien Maudet in International journal of cartography, vol 3 n° 1 (June 2017)
- 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)
OpenStreetMap in GIScience : experiences, research, and applications. Inferring the Scale of OpenStreetMap Features / Guillaume Touya (2015)
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