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Titre : Spatial dataset search: Building a dedicated knowledge graph Type de document : Article/Communication Auteurs : Mehdi Zrhal , Auteur ; Bénédicte Bucher , Auteur ; Marie-Dominique Van Damme , Auteur ; Fayçal Hamdi , Auteur Editeur : AGILE Alliance Année de publication : 2021 Projets : 1-Pas de projet / Conférence : AGILE 2021, 24th AGILE Conference on Geographic Information Science 19/07/2021 22/07/2021 Aurora Colorado - Etats-Unis OA Proceedings Importance : 5 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] découverte de connaissances
[Termes IGN] données massives
[Termes IGN] données ouvertes
[Termes IGN] graphe
[Termes IGN] INSPIRE
[Termes IGN] jeu de données localisées
[Termes IGN] précision sémantique
[Termes IGN] recherche d'information géographique
[Termes IGN] requête spatiale
[Termes IGN] réseau sémantique
[Termes IGN] ressources web
[Termes IGN] service web géographique
[Termes IGN] terminologie
[Termes IGN] web des données
[Termes IGN] web sémantique géolocaliséRésumé : (auteur) A growing number of spatial datasets are published every year. These can usually be found in dedicated web portals with different structures and specificities. However, finding the dataset that fits user needs is a real challenge as prior knowledge of these portals is needed to retrieve it efficiently. In this article, we present the problem of spatial dataset search and how the use of a geographic Knowledge Graph could improve it. A proposed direction for future work, ex-tending these contributions, is then presented. Numéro de notice : C2021-008 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/agile-giss-2-43-2021 En ligne : https://doi.org/10.5194/agile-giss-2-43-2021 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97855 Streets of London: Using Flickr and OpenStreetMap to build an interactive image of the city / Azam Raha Bahrehdar in Computers, Environment and Urban Systems, vol 84 (November 2020)
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Titre : Streets of London: Using Flickr and OpenStreetMap to build an interactive image of the city Type de document : Article/Communication Auteurs : Azam Raha Bahrehdar, Auteur ; Benjamin Adams, Auteur ; Ross S. Purves, Auteur Année de publication : 2020 Article en page(s) : n° 101524 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] autocorrélation spatiale
[Termes IGN] collecte de données
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées des bénévoles
[Termes IGN] exploration de données
[Termes IGN] image Flickr
[Termes IGN] Londres
[Termes IGN] mesure de similitude
[Termes IGN] métadonnées
[Termes IGN] OpenStreetMap
[Termes IGN] orthoimage géoréférencée
[Termes IGN] perception
[Termes IGN] segmentation sémantiqueRésumé : (auteur) In his classic book “The Image of the City” Kevin Lynch used empirical work to show how different elements of the city were perceived: such as paths, landmarks, districts, edges, and nodes. Streets, by providing paths from which cities can be experienced, were argued to be one of the key elements of cities. Despite this long standing empirical basis, and the importance of Lynch's model in policy associated areas such as planning, work with user generated content has largely ignored these ideas. In this paper, we address this gap, using streets to aggregate filtered user generated content related to more than 1 million images and 60,000 individuals and explore similarity between more than 3000 streets in London across three dimensions: user behaviour, time and semantics. To perform our study we used two different sources of user generated content: (1) a collection of metadata attached to Flickr images and (2) street network of London from OpenStreetMap. We first explore global patterns in the distinctiveness and spatial autocorrelation of similarity using our three dimensions, establishing that the semantic and user dimensions in particular allow us to explore the city in different ways. We then used a Processing tool to interactively explore individual patterns of similarity across these four dimensions simultaneously, presenting results here for four selected and contrasting locations in London. Before drilling into the data to interpret in more detail, the identified patterns demonstrate that streets are natural units capturing perception of cities not only as paths but also through the emergence of other elements of the city proposed by Lynch including districts, landmarks and edges. Our approach also demonstrates how user generated content can be captured, allowing bottom-up perception from citizens to flow into a representation. Numéro de notice : A2020-710 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2020.101524 Date de publication en ligne : 05/08/2020 En ligne : https://doi.org/10.1016/j.compenvurbsys.2020.101524 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96255
in Computers, Environment and Urban Systems > vol 84 (November 2020) . - n° 101524[article]GNSS scale determination using calibrated receiver and Galileo satellite antenna patterns / Arturo Villiger in Journal of geodesy, vol 94 n° 9 (September 2020)
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Titre : GNSS scale determination using calibrated receiver and Galileo satellite antenna patterns Type de document : Article/Communication Auteurs : Arturo Villiger, Auteur ; Rolf Dach, Auteur ; Stefan Schaer, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 93 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] antenne Galileo
[Termes IGN] centre de phase
[Termes IGN] chambre anéchoïque
[Termes IGN] étalonnage d'instrument
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] métadonnées
[Termes IGN] positionnement par ITGB
[Termes IGN] positionnement par télémétrie laser sur satellite
[Termes IGN] réseau géodésique terrestre
[Termes IGN] robotRésumé : (auteur) The reference frame of a global terrestrial network is defined by the origin, the orientation and the scale. The origin of the ITRF2014 is defined by the ILRS long-term solution, the orientation by no-net rotation conditions w.r.t. the previous reference frame (ITRF2008), and the scale by the mean values from global VLBI and SLR solution series (Altamimi et al. in J Geophys Res Solid Earth 121:6109–6131, 2016). With the release of the Galileo satellite antenna phase center offsets (PCO) w.r.t. the satellites center of mass (GSA in Galileo IOV and FOC satellite metadata, 2019) and the availability of new ground antenna calibrations for GNSS receivers, based on anechoic chamber measurements or on robot calibrations, GNSS global network solutions qualify to contribute to the scale determination of terrestrial networks, as well. Our analysis is based on global multi-GNSS solutions of the years 2017 and 2018 and may be seen as “proof of concept” for the contribution of GNSS data to the scale determination of the terrestrial reference frame. In a first step, the currently used Galileo PCO estimations (Steigenberger et al. in J Geod 90:773–785, 2016) are compared to the released PCO values, which show discrepancies on the decimeter-level. Eventually, the published Galileo PCOs are used in an experimental solution as known values. GNSS-specific PCOs are estimated, as well, for GPS and GLONASS, together with the “standard” parameters set up in global GNSS solutions. From the estimated network coordinates, a time series of daily scale parameters of the terrestrial network is extracted, which shows an offset of the order of 1 ppb (parts per billion, corresponding to a height difference of 6.4 mm on the Earth’s surface) w.r.t. to the ITRF2014 network and an annual variation with an amplitude of about 0.3 ppb. Numéro de notice : A2020-539 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01417-0 Date de publication en ligne : 05/09/2020 En ligne : https://doi.org/10.1007/s00190-020-01417-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95739
in Journal of geodesy > vol 94 n° 9 (September 2020) . - n° 93[article]Data scale as cartography: a semi-automatic approach for thematic web map creation / Auriol Degbelo in Cartography and Geographic Information Science, vol 47 n° 2 (February 2020)
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Titre : Data scale as cartography: a semi-automatic approach for thematic web map creation Type de document : Article/Communication Auteurs : Auriol Degbelo, Auteur ; Saad Sarfraz, Auteur ; Christian Kray, Auteur Année de publication : 2020 Article en page(s) : pp 153 - 170 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] accès aux données localisées
[Termes IGN] carte thématique
[Termes IGN] cartographie numérique
[Termes IGN] données ouvertes
[Termes IGN] échelle des données
[Termes IGN] géovisualisation
[Termes IGN] test statistique
[Termes IGN] web mappingRésumé : (auteur) Open government promises increased transparency by providing its citizens datasets about city processes. Open data portals have been emerging all over the world as mines of open geographic datasets. Thematic web maps are key to understanding these open geographic datasets. Current thematic web maps are created by programmers and/or cartographers, and thus are not designed to be easily reused with new geographic datasets. As a result, they pose several challenges to non-experts wanting to adapt them to new scenarios. This article introduces a semi-automatic approach for the creation of thematic web maps by and for users with no prior training in cartography. The approach relies on the mapping between Stevens’ data types and Bertin’s visual variables, to suggest (meaningful) thematic map visualizations for a given input geographic dataset. It was implemented as a web prototype in AngularJS and evaluated with 19 participants. Results from the user study suggest that despite facing a few challenges in accurately identifying Stevens’ data types, participants managed to successfully create web maps and correctly answer spatial questions. The prototype and insights gathered from the user study are relevant to making cartographic products more accessible to a broader population, and open geographic data more usable in the context of an open government. Numéro de notice : A2020-059 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1677176 Date de publication en ligne : 05/11/2019 En ligne : https://doi.org/10.1080/15230406.2019.1677176 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94576
in Cartography and Geographic Information Science > vol 47 n° 2 (February 2020) . - pp 153 - 170[article]
Titre : Artificial intelligence applications to smart city and smart enterprise Type de document : Monographie Auteurs : Donato Impedovo, Éditeur scientifique ; Giuseppe Pirlo, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2020 Importance : 374 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-03936-438-1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] algorithme génétique
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] gestion urbaine
[Termes IGN] Inférence floue
[Termes IGN] métadonnées
[Termes IGN] navigation autonome
[Termes IGN] planification urbaine
[Termes IGN] système de transport intelligent
[Termes IGN] trafic routier
[Termes IGN] ville intelligente
[Termes IGN] vision par ordinateurRésumé : (éditeur) Smart cities operate under more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which led to the creation of smart enterprises and organizations that depend on advanced technologies. This book includes 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Chapters refer to the following areas of interest: vehicular traffic prediction, social big data analysis, smart city management, driving and routing, localization, safety, health, and life quality. Note de contenu : 1- Artificial intelligence applications to smart city and smart enterprise
2- Global spatial-temporal graph convolutional network for urban traffic speed prediction
3- TrafficWave: Generative deep learning architecture for vehicular traffic flow prediction
4- Grassmann manifold based state analysis method of traffic surveillance video
5- Improved spatio-temporal residual networks for bus traffic flow prediction
6- Sehaa: A big data analytics tool for healthcare symptoms and diseases detection using Twitter, Apache Spark, and machine learning
7- Smart cities big data algorithms for sensors location
8- Managing a smart city integrated model through smart program management
9- Conceptual framework of an intelligent decision support system for smart city
disaster management
10- Vision-based potential pedestrian risk analysis on unsignalized crosswalk using data mining techniques
11- Development of deep learning based human-centered threat assessment for application to automated driving vehicle
12- Modeling and solution of the routing problem in vehicular Delay-Tolerant networks: A dual, deep learning perspective
13- “Texting & Driving” detection using deep convolutional neural networks
14- Deep learning system for vehicular re-routing and congestion avoidance
15- Identifying foreign tourists’ nationality from mobility traces via LSTM neural network and location embeddings
16- Feature adaptive and cyclic dynamic learning based on infinite term memory extreme learning machine
17- LSTM DSS automatism and dataset optimization for diabetes prediction
18- Convolutional models for the detection of firearms in surveillance videos
19- PARNet: A joint loss function and dynamic weights network for pedestrian semantic attributes recognition of smart surveillance image
20- Supervised machine-learning predictive analytics for national quality of life scoring
21- Bacterial foraging-based algorithm for optimizing the powerGeneration of an isolated microgrid
22- Optimizgtion of EPB shield performance with adaptive neuro-fuzzy inference system and Genetic algorithmNuméro de notice : 28448 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-03936-438-1 En ligne : https://doi.org/10.3390/books978-3-03936-438-1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98929 PermalinkCollaborative user oriented metadata production on EuroSDR Geometadatalabs platform [paper and diaporama] / Bénédicte Bucher (2020)PermalinkComparing supervised learning algorithms for Spatial Nominal Entity recognition / Amine Medad (2020)PermalinkPermalinkIndividual internet usage and the availability of online content of local interest: A multilevel approach / Emmanouil Tranos in Computers, Environment and Urban Systems, vol 79 (January 2020)PermalinkInitiatives for Providing Data and Tools for Research and Education: EuroSDR survey / Bénédicte Bucher (2020)PermalinkPermalinkModelling perceived risks to personal privacy from location disclosure on online social networks / Fatma S. Alrayes in International journal of geographical information science IJGIS, vol 34 n° 1 (January 2020)PermalinkPermalinkPermalink