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Designing multi-scale maps: lessons learned from existing practices / Marion Dumont in International journal of cartography, Vol 6 n° 1 (March 2020)
[article]
Titre : Designing multi-scale maps: lessons learned from existing practices Type de document : Article/Communication Auteurs : Marion Dumont , Auteur ; Guillaume Touya , Auteur ; Cécile Duchêne , Auteur Année de publication : 2020 Projets : MapMuxing / Christophe, Sidonie Article en page(s) : pp 121 - 151 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse visuelle
[Termes IGN] carte interactive
[Termes IGN] cognition
[Termes IGN] données multiéchelles
[Termes IGN] échelle cartographique
[Termes IGN] géomatique web
[Termes IGN] niveau d'abstraction
[Termes IGN] niveau de détail
[Termes IGN] représentation multiple
[Termes IGN] Web Map Tile Service
[Termes IGN] zoom
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Mapping applications display multi-scale maps where zooming in and out triggers the display of different maps at different scales. Multi-scale maps strongly augmented the potential uses of maps, compared to the traditional single-scaled paper maps. But the exploration of the multi-scale maps can be cognitively difficult for users because the content of the maps can be very different at different scales. This paper seeks to identify the factors in the design of map content and style that increase or decrease the exploration cognitive load, in order to improve multi-scales map design. We studied sixteen existing examples of multi-scale maps to identify these factors that influence a fluid zooming interaction. Several different analyses were conducted on these sixteen multi-scale maps. We first conducted a guided visual exploration of the maps, and a detailed study of the scales of the maps, to identify general trends of good practices (e.g. the WMTS standard that defines zoom levels is widely used) and potential ways of improvement (e.g. a same map is often used at multiple successive zoom levels). Then, we focused on the visual complexity of the multi-scale maps by analyzing how it varies, continuously or not, across scales, using clutter measures, which showed a peak of complexity at zoom level 12 of the WMTS standard. Finally, we studied how buildings and roads are subject to abstraction changes across scales (e.g. at what zoom level individual buildings turn into built-up areas), which can be one of the causes of exploration difficulties. We identified some good practices to reduce the impact of abstraction changes, for instance by mixing different levels of abstraction in the same map. Numéro de notice : A2020-060 Affiliation des auteurs : LASTIG COGIT (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2020.1717832 Date de publication en ligne : 28/01/2020 En ligne : https://doi.org/10.1080/23729333.2020.1717832 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94571
in International journal of cartography > Vol 6 n° 1 (March 2020) . - pp 121 - 151[article]Spatio-temporal mobility and Twitter: 3D visualisation of mobility flows / Joaquín Osorio Arjona in Journal of maps, vol 16 n° 1 ([02/01/2020])
[article]
Titre : Spatio-temporal mobility and Twitter: 3D visualisation of mobility flows Type de document : Article/Communication Auteurs : Joaquín Osorio Arjona, Auteur ; Juan Carlos García Palomares, Auteur Année de publication : 2020 Article en page(s) : pp 153 - 160 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatio-temporelle
[Termes IGN] base de données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] espace-temps
[Termes IGN] interface de programmation
[Termes IGN] Madrid (Espagne)
[Termes IGN] migration pendulaire
[Termes IGN] mobilité urbaine
[Termes IGN] réseau social
[Termes IGN] système d'information géographique
[Termes IGN] Time-geography
[Termes IGN] Twitter
[Termes IGN] visualisation 3D
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Recent progress in computation and the spatio-temporal richness of data obtained from new sources have invigorated Time Geography. It is now possible to visualise and represent movements of people in a dual spatial–temporal dimension. In this work, we use geo-located data from the social media platform Twitter to show the value of new data sources for Time Geography. The methodology consists of visualising space–time paths in 2D and 3D in four study zones, with different land-use profiles, based on tweets compiled over the course of two years. The results provide a view of behaviours occurring in the areas of study throughout the day, with complementary data to show the population's main activity at different times. Numéro de notice : A2020-645 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17445647.2020.1778549 Date de publication en ligne : 18/06/2020 En ligne : https://doi.org/10.1080/17445647.2020.1778549 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96071
in Journal of maps > vol 16 n° 1 [02/01/2020] . - pp 153 - 160[article]Application of machine learning techniques for evidential 3D perception, in the context of autonomous driving / Edouard Capellier (2020)
Titre : Application of machine learning techniques for evidential 3D perception, in the context of autonomous driving Type de document : Thèse/HDR Auteurs : Edouard Capellier, Auteur ; Véronique Berge-Cherfaoui, Directeur de thèse ; Franck Davoine, Directeur de thèse Editeur : Compiègne : Université de Technologie de Compiègne UTC Année de publication : 2020 Importance : 123 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse présentée pour l'obtention du grade de Docteur de l'UTC, Robotique et Sciences et Technologies de l'Information et des SystèmesLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] carte routière
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] données lidar
[Termes IGN] image RVB
[Termes IGN] intelligence artificielle
[Termes IGN] navigation autonome
[Termes IGN] segmentation sémantique
[Termes IGN] théorie de Dempster-Shafer
[Termes IGN] vision par ordinateur
[Termes IGN] visualisation 3DIndex. décimale : THESE Thèses et HDR Résumé : (auteur) The perception task is paramount for self-driving vehicles. Being able to extract accurate and significant information from sensor inputs is mandatory, so as to ensure a safe operation. The recent progresses of machine-learning techniques revolutionize the way perception modules, for autonomous driving, are being developed and evaluated, while allowing to vastly overpass previous state-of-the-art results in practically all the perception-related tasks. Therefore, efficient and accurate ways to model the knowledge that is used by a self-driving vehicle is mandatory. Indeed, self-awareness, and appropriate modeling of the doubts, are desirable properties for such system. In this work, we assumed that the evidence theory was an efficient way to finely model the information extracted from deep neural networks. Based on those intuitions, we developed three perception modules that rely on machine learning, and the evidence theory. Those modules were tested on real-life data. First, we proposed an asynchronous evidential occupancy grid mapping algorithm, that fused semantic segmentation results obtained from RGB images, and LIDAR scans. Its asynchronous nature makes it particularly efficient to handle sensor failures. The semantic information is used to define decay rates at the cell level, and handle potentially moving object. Then, we proposed an evidential classifier of LIDAR objects. This system is trained to distinguish between vehicles and vulnerable road users, that are detected via a clustering algorithm. The classifier can be reinterpreted as performing a fusion of simple evidential mass functions. Moreover, a simple statistical filtering scheme can be used to filter outputs of the classifier that are incoherent with regards to the training set, so as to allow the classifier to work in open world, and reject other types of objects. Finally, we investigated the possibility to perform road detection in LIDAR scans, from deep neural networks. We proposed two architectures that are inspired by recent state-of-the-art LIDAR processing systems. A training dataset was acquired and labeled in a semi-automatic fashion from road maps. A set of fused neural networks reaches satisfactory results, which allowed us to use them in an evidential road mapping and object detection algorithm, that manages to run at 10 Hz Note de contenu : 1- Introduction
2- Machine learning for perception in autonomous driving
3- The evidence theory, and its applications in autonomous driving
4- A synchronous evidential grid mapping from RGB images and LIDAR scans
5- Evidential LIDAR object classification
6- Road detection in LIDAR scans
7- Application of RoadSeg:evidential road surface mapping
8- ConclusionNuméro de notice : 25895 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Robotique et Sciences et Technologies de l'Information et des Systèmes : UTC : 2020 Organisme de stage : Laboratoire Heudiasyc nature-HAL : Thèse DOI : sans En ligne : https://hal.science/tel-02897810v1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96013
Titre : Co-visualization of air temperature and urban data for visual exploration Type de document : Article/Communication Auteurs : Jacques Gautier , Auteur ; Mathieu Brédif , Auteur ; Sidonie Christophe , Auteur Editeur : New-York : IEEE Computer society Année de publication : 2020 Projets : URCLIM / Masson, Valéry Conférence : IEEE VIS 2020, (VAST, INFOVIS, SCIVIS), premier forum for advances in visualization and visual analytics 25/10/2020 30/10/2020 en ligne vers VIS.org Importance : 5 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] distribution spatiale
[Termes IGN] exploration de données géographiques
[Termes IGN] ilot thermique urbain
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] morphologie urbaine
[Termes IGN] rendu (géovisualisation)
[Termes IGN] représentation graphique
[Termes IGN] température de l'air
[Termes IGN] visualisation 3D
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Urban climate data remain complex to analyze regarding their spatial distribution. The co-visualization of simulated air temperature into urban models could help experts to analyze horizontal and vertical spatial distributions. We design a co-visualization framework enabling simulated air temperature data exploration, based on the graphic representation of three types of geometric proxies, and their co-visualization with a 3D urban model with various possible rendering styles. Through this framework, we aim at allowing meteorological researchers to visually analyze and interpret the relationships between simulated air temperature data and urban morphology. Numéro de notice : C2020-005 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : VIS 2020 Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/VIS47514.2020.00021 Date de publication en ligne : 01/02/2021 En ligne : https://doi.org/10.1109/VIS47514.2020.00021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96161 Documents numériques
en open access
Co-visualization... - pdf auteur -Adobe Acrobat PDF
Titre : Multi-scale point cloud analysis Titre original : Analyse multi-échelle de nuage de points Type de document : Thèse/HDR Auteurs : Thibault Lejemble, Auteur ; Loïc Barthe, Directeur de thèse Editeur : Toulouse : Université de Toulouse 3 Paul Sabatier Année de publication : 2020 Importance : 142 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse en vue du Doctorat de l'Université de Toulouse en Informatique et TélécommunicationsLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse multiéchelle
[Termes IGN] analyse multirésolution
[Termes IGN] anisotropie
[Termes IGN] approche hiérarchique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction automatique
[Termes IGN] géométrie différentielle
[Termes IGN] graphe
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation en plan
[Termes IGN] segmentation en régions
[Termes IGN] semis de points
[Termes IGN] visualisation 3DIndex. décimale : THESE Thèses et HDR Résumé : (auteur) 3D acquisition techniques like photogrammetry and laser scanning are commonly used in numerous fields such as reverse engineering, archeology, robotics and urban planning. The main objective is to get virtual versions of real objects in order to visualize, analyze and process them easily. Acquisition techniques become more and more powerful and affordable which creates important needs to process efficiently the resulting various and massive3D data. Data are usually obtained in the form of unstructured 3D point cloud sampling the scanned surface. Traditional signal processing methods cannot be directly applied due to the lack of spatial parametrization. Points are only represented by their 3D coordinates without any particular order. This thesis focuses on the notion of scale of analysis defined by the size of the neighborhood used to locally characterize the point-sampled surface. The analysis at different scales enables to consider various shapes which increases the analysis pertinence and the robustness to acquired data imperfections. We first present some theoretical and practical results on curvature estimation adapted to a multi-scale and multi-resolution representation of point clouds. They are used to develop multi-scale algorithms for the recognition of planar and anisotropic shapes such as cylinder sand feature curves. Finally, we propose to compute a global 2D parametrization of the underlying surface directly from the 3D unstructured point cloud. Note de contenu : Introduction
1- Multi-scale differential analysis of point clouds
2- Plane detection using persistence analysis of graph
3- An isotropic features detection using curvature lines
4- Point cloud parametrization
ConclusionNuméro de notice : 28583 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique et Télécommunications : Toulouse 3 : 2020 Organisme de stage : Institut de recherche en informatique de Toulouse En ligne : https://tel.archives-ouvertes.fr/tel-03170824/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97923 PermalinkPermalinkNumérisation, restitution et visualisation en 3D de sites patrimoniaux / Jonathan Chemla in XYZ, n° 161 (décembre 2019)PermalinkLes nouveautés de QGis 3.10 / Anonyme in Géomatique expert, n° 130-131 (octobre - décembre 2019)PermalinkReprésentation des éléments juridiques dans une maquette BIM / Bamba Ngom in Géomatique expert, n° 128 (juin - juillet 2019)PermalinkAn artificial bee colony-based algorithm to automatically create colour schemes for geovisualizations / Mingguang Wu in Cartographic journal (the), Vol 56 n° 2 (May 2019)PermalinkiTowns, le nouveau moteur de visualisation 3D de données géospatiales du Géoportail / Mirela Konini in Responsabilité et environnement, n° 94 (Avril 2019)PermalinkOrléans monte sa maquette virtuelle / Anonyme in Géomatique expert, n° 127 (avril - mai 2019)PermalinkUtilizing a discrete global grid system for handling point clouds with varying locations, times, and levels of detail / Neeraj Sirdeshmukh in Cartographica, vol 54 n° 1 (Spring 2019)PermalinkPermalink