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Stop-and-move sequence expressions over semantic trajectories / Yenier Torres Izquierdo in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 4 (April 2021) . - pp 793 - 818 Titre : Stop-and-move sequence expressions over semantic trajectories Type de document : Article/Communication Auteurs : Yenier Torres Izquierdo, Auteur ; Grettel Monteagudo Garcia, Auteur ; Marco A. Casanova, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 793 - 818 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] algorithme de recherche [Termes IGN] appariement sémantique [Termes IGN] exploration de données [Termes IGN] image Flickr [Termes IGN] information sémantique [Termes IGN] intelligence artificielle [Termes IGN] langage de requête [Termes IGN] RDF [Termes IGN] SPARQL Résumé : (auteur) Stop-and-move semantic trajectories are segmented trajectories where the stops and moves are semantically enriched with additional data. A query language for semantic trajectory datasets has to include selectors for stops or moves based on their enrichments and sequence expressions that define how to match the results of selectors with the sequence the semantic trajectory defines. This article addresses the problem of searching semantic trajectories, using stop-and-move sequence expressions. The article first proposes a formal framework to define semantic trajectories and introduces stop-and-move sequence expressions, with well-defined syntax and semantics, which act as an expressive query language for semantic trajectories. Then, it describes a concrete semantic trajectory model in RDF, defines SPARQL stop-and-move sequence expressions and discusses strategies to compile such expressions into SPARQL queries. Lastly, the article specifies user-friendly keyword search expressions over semantic trajectories based on the use of keywords to specify stop-and-move queries, and the adoption of terms with predefined semantics to compose sequence expressions. It then shows how to compile such keyword search expressions into SPARQL queries. Finally, it provides a proof-of-concept experiment over a semantic trajectory dataset constructed with user-generated content from Flickr, combined with Wikipedia data. Numéro de notice : A2021-270 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1793157 date de publication en ligne : 20/07/2020 En ligne : https://doi.org/10.1080/13658816.2020.1793157 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97328 [article]

Recognition of varying size scene images using semantic analysis of deep activation maps / Shikha Gupta in Machine Vision and Applications, vol 32 n° 2 (March 2021)  

Public [article]  inMachine Vision and Applications > vol 32 n° 2 (March 2021) . - n° 52 Titre : Recognition of varying size scene images using semantic analysis of deep activation maps Type de document : Article/Communication Auteurs : Shikha Gupta, Auteur ; A.D. Dileep, Auteur ; Veena Thenkanidiyoor, Auteur Année de publication : 2021 Article en page(s) : n° 52 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] analyse sémantique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] compréhension de l'image [Termes IGN] méthode fondée sur le noyau [Termes IGN] modèle conceptuel de données [Termes IGN] reconnaissance de formes Résumé : (auteur) Understanding the complex semantic structure of scene images requires mapping the image from pixel space to high-level semantic space. In semantic space, a scene image is represented by the posterior probabilities of concepts (e.g., ‘car,’ ‘chair,’ ‘window,’ etc.) present in it and such representation is known as semantic multinomial (SMN) representation. SMN generation requires a concept annotated dataset for concept modeling which is infeasible to generate manually due to the large size of databases. To tackle this issue, we propose a novel approach of building the concept model via pseudo-concepts. Pseudo-concept acts as a proxy for the actual concept and gives the cue for its presence instead of actual identity. We propose to use filter responses from deeper convolutional layers of convolutional neural networks (CNNs) as pseudo-concepts, as filters in deeper convolutional layers are trained for different semantic concepts. Most of the prior work considers fixed-size (≈227×227) images for semantic analysis which suppresses many concepts present in the images. In this work, we preserve the true-concept structure in images by passing in their original resolution to convolutional layers of CNNs. We further propose to prune the non-prominent pseudo-concepts, group the similar one using kernel clustering and later model them using a dynamic-based support vector machine. We demonstrate that resulting SMN representation indeed captures the semantic concepts better and results in state-of-the-art classification accuracy on varying size scene image datasets such as MIT67 and SUN397. Numéro de notice : A2021-454 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00138-021-01168-8 date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.1007/s00138-021-01168-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97898 [article]

Bretagne, la végétation cartographiée / Marielle Mayo in Géomètre, n° 2185 (novembre 2020)

Public [article]  inGéomètre > n° 2185 (novembre 2020) . - pp 46 - 49 Titre : Bretagne, la végétation cartographiée Type de document : Article/Communication Auteurs : Marielle Mayo, Auteur Année de publication : 2020 Article en page(s) : pp 46 - 49 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] 1:25.000 [Termes IGN] acquisition d'images [Termes IGN] aménagement régional [Termes IGN] appariement semi-automatique [Termes IGN] ArcGIS [Termes IGN] BD ortho [Termes IGN] Bretagne [Termes IGN] carte de la végétation [Termes IGN] classification orientée objet [Termes IGN] données localisées [Termes IGN] données publiques [Termes IGN] IGN cité [Termes IGN] image infrarouge couleur [Termes IGN] image proche infrarouge [Termes IGN] modèle orienté objet [Termes IGN] phytoécologie Résumé : (Auteur) Une cartographie inédite de la végétation de Bretagne sera accessible en totalité en ligne en décembre. Produite par télédétection grâce à une méthode semi-automatisée innovante, elle répond aux nouveaux besoins des acteurs de la biodiversité et de l'aménagement du territoire. Numéro de notice : A2020-707 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96281 [article]

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Delivering time-evolving 3D city models for web visualization / Vincent Jaillot in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 10 (October 2020) . - pp 2030 - 2052 Titre : Delivering time-evolving 3D city models for web visualization Type de document : Article/Communication Auteurs : Vincent Jaillot, Auteur ; Sylvie Servigne, Auteur ; Gilles Gesquière, Auteur Année de publication : 2020 Article en page(s) : pp 2030 - 2052 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] CityGML [Termes IGN] implémentation (informatique) [Termes IGN] interactivité [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modèle conceptuel de données [Termes IGN] modélisation spatio-temporelle [Termes IGN] Open geospatial consortium Résumé : (auteur) Studying and planning urban evolution is essential for understanding the past and designing the cities of the future and can be facilitated by providing means for sharing, visualizing, and navigating in cities, on the web, in space and in time. Standard formats, methods, and tools exist for visualizing large-scale 3D cities on the web. In this paper, we go further by integrating the temporal dimension of cities in geospatial web delivery standard formats. In doing so, we enable interactive visualization of large-scale time-evolving 3D city models on the web. A key characteristic of this paper lies in the proposed four-step generic approach. First, we design a generic conceptual model of standard formats for delivering 3D cities on the web. Then, we formalize and integrate the temporal dimension of cities into this generic conceptual model. Following which, we specify the conceptual model in the 3D Tiles standard at logical and technical specification levels, resulting in an extension of 3D Tiles for delivering time-evolving 3D city models on the web. Finally, we propose an open-source implementation, experiments, and an evaluation of the propositions and visualization rules. We also provide access to reproducibility notes allowing researchers to replicate all the experiments. Numéro de notice : A2020-514 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1749637 date de publication en ligne : 14/04/2020 En ligne : https://doi.org/10.1080/13658816.2020.1749637 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95673 [article]

Integration of spatialization and individualization: the future of epidemic modelling for communicable diseases / Meifang Li in Annals of GIS, vol 26 n° 3 (July 2020)  

Public [article]  inAnnals of GIS > vol 26 n° 3 (July 2020) . - pp 219 - 226 Titre : Integration of spatialization and individualization: the future of epidemic modelling for communicable diseases Type de document : Article/Communication Auteurs : Meifang Li, Auteur ; Xun Shi, Auteur ; Xia Li, Auteur Année de publication : 2020 Article en page(s) : pp 219 - 226 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] épidémie [Termes IGN] historique des données [Termes IGN] modèle orienté objet [Termes IGN] modélisation spatio-temporelle [Termes IGN] risque sanitaire [Termes IGN] système d'information géographique [Termes IGN] transmissibilité Résumé : (auteur) In the past several decades, epidemic modelling for communicable diseases has experienced transitions from treating the entire study area as a whole to addressing spatial variation within the area, and from targeting the entire population to incorporating characteristics of categorized subpopulations and finally going down to the individual level. These transitions have been first driven by the recognition that generalizations of space and population in conventional epidemic modelling may have hampered the effectiveness of the modelling; they then have been supported by increasingly available data that allow depiction of detailed spatiotemporal characteristics of an epidemic, as well as those characteristics of the environment in both human and natural aspects; and finally they have been facilitated by developments in geographic information science, data science, computer science, and computing technologies. Based on a review of a variety of recently developed communicable disease models, we explicitly put forward the notions of spatialization and individualization in this area, and point out that the integration of the two is the future of communicable disease modelling. We also point out that in this area models based on the object conceptualization are good at modelling spatiotemporal process, whereas models based on the field conceptualization are good at representing spatialized information. We propose a procedural framework of epidemic modelling that implements the integration of individualization and spatialization, integration of object-based process and field-based representation, and integration of modelling that retrospectively traces infection relationships based on historical patient data and modelling that prospectively predicts such relationships of future epidemics. Numéro de notice : A2020-581 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2020.1768438 date de publication en ligne : 25/05/2020 En ligne : https://doi.org/10.1080/19475683.2020.1768438 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95903 [article]

A hybrid deep learning–based model for automatic car extraction from high-resolution airborne imagery / Mehdi Khoshboresh Masouleh in Applied geomatics, vol 12 n° 2 (June 2020)  

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Mining spatiotemporal association patterns from complex geographic phenomena / Zhanjun He in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)  

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Projet infos usagers et projet transport à la demande / Oriane Sobreira (2020) 

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Relative space-based GIS data model to analyze the group dynamics of moving objects / Mingxiang Feng in ISPRS Journal of photogrammetry and remote sensing, vol 153 (July 2019)  

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A conceptual framework for studying collective reactions to events in location-based social media / Alexander Dunkel in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

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A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data / Luis Vilches-Blazquez in Transactions in GIS, vol 23 n° 1 (February 2019)  

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Process modelling and simulation / Cesar De Prada (2019)  

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GIS approach to publishing commonfacilities plans of land consolidation in the Czech Republic / Arnošt Müller in Geodetski vestnik, vol 62 n° 4 (December 2018 - February 2019)  

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Scene classification based on multiscale convolutional neural network / Yanfei Liu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)  

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Ontologies pour représenter l’évolution des découpages territoriaux statistiques / Camille Bernard in Revue internationale de géomatique, vol 28 n° 4 (octobre - décembre 2018)  

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