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Semantic enrichment of secondary activities using smart card data and point of interests: a case study in London / Nilufer Sari Aslam in Annals of GIS, vol 27 n° 1 (January 2021)  

Public [article]  inAnnals of GIS > vol 27 n° 1 (January 2021) . - pp 29 - 41 Titre : Semantic enrichment of secondary activities using smart card data and point of interests: a case study in London Type de document : Article/Communication Auteurs : Nilufer Sari Aslam, Auteur ; Di Zhu, Auteur ; Tao Cheng, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 29 - 41 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] carte à puce [Termes IGN] collecte de données [Termes IGN] données socio-économiques [Termes IGN] données spatiotemporelles [Termes IGN] enrichissement sémantique [Termes IGN] loisir [Termes IGN] Londres [Termes IGN] méthode heuristique [Termes IGN] planification urbaine [Termes IGN] point d'intérêt [Termes IGN] transport urbain Résumé : (auteur) The large volume of data automatically collected by smart card fare systems offers a rich source of information regarding daily human activities with a high resolution of spatial and temporal representation. This provides an opportunity for aiding transport planners and policy-makers to plan transport systems and cities more responsively. However, there are currently limitations when it comes to understanding the secondary activities of individual commuters. Accordingly, in this paper, we propose a framework to detect and infer secondary activities from individuals’ daily travel patterns from the smart card data and reduce the use of conventional surveys. First, we proposed a ‘heuristic secondary activity identification algorithm’, which uses commuters’ primary locations (home & work) and the direction (from & to) information to identify secondary activities for individuals. The algorithm provides a high-level classification of the activity types as before-work, midday and after-work activity patterns of individuals. Second, this classification is semantically enriched using Points of Interests to provide meaningful insights into individuals’ travel purposes and mobility in an urban environment. Lastly, using the transit data of London as a case study, the model is compared with a volunteer survey to demonstrate its effectiveness and offering a cost-effective method to travel demand research. Numéro de notice : A2021-319 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475683.2020.1783359 date de publication en ligne : 01/08/2020 En ligne : https://doi.org/10.1080/19475683.2020.1783359 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97550 [article]

Toward green cartography & visualization: a semantically-enriched method of generating energy-aware color schemes for digital maps / Yangli Han in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 1 (January 2021) . - pp 43 - 62 Titre : Toward green cartography & visualization: a semantically-enriched method of generating energy-aware color schemes for digital maps Type de document : Article/Communication Auteurs : Yangli Han, Auteur ; Mingguang Wu, Auteur ; Robert Roth, Auteur Année de publication : 2021 Article en page(s) : pp 43 - 62 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] amélioration des couleurs [Termes IGN] cartographie pour écran mobile [Termes IGN] conception cartographique [Termes IGN] couleur (rédaction cartographique) [Termes IGN] économie d'énergie [Termes IGN] enrichissement sémantique [Termes IGN] impact sur l'environnement [Termes IGN] optimisation (mathématiques) [Termes IGN] relation sémantique [Termes IGN] téléphone intelligent [Termes IGN] visualisation cartographique [Vedettes matières IGN] Géovisualisation Résumé : (auteur) We introduce a semantically-enriched method of generating color schemes for various types of digital maps that reduces the energy consumption of the display device while preserving the quality of the original design. Energy-aware design intersects two important trends in cartography. First, as more maps are viewed today on mobile, battery life has become a central constraint influencing design. Second, there is increasing need for green computing, which encourages the efficient use of energy to limit environmental impacts. This paper focuses on one important aspect of energy-aware cartography: color design. Existing research on energy-aware color adjustment methods apply broadly to images or websites. However, the colors used in maps have more structured semantic relationships than most documents viewed on mobile devices, and efforts to account for these relationships while reducing energy consumption are limited. To fill this gap, we mathematically formalize energy-aware map-color adjustment as a constrained optimization problem: we define energy consumption as the objective function and model the preservation of semantic relationships as the search constraints. We evaluate our proposed method against a common color dimming method using four maps with different semantic relationships. The evaluation suggests that our proposed method better preserves the original color semantics. Numéro de notice : A2021-018 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1827040 date de publication en ligne : 05/11/2020 En ligne : https://doi.org/10.1080/15230406.2020.1827040 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96457 [article]

Deep learning for enrichment of vector spatial databases: Application to highway interchange / Guillaume Touya in ACM Transactions on spatial algorithms and systems, TOSAS, vol 6 n° 3 (May 2020)    

Public [article]  inACM Transactions on spatial algorithms and systems, TOSAS > vol 6 n° 3 (May 2020) . - 21 p. Titre : Deep learning for enrichment of vector spatial databases: Application to highway interchange Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Imran Lokhat , Auteur Année de publication : 2020 Projets : 1-Pas de projet / Article en page(s) : 21 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage profond [Termes IGN] base d'apprentissage [Termes IGN] base de données vectorielles [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] échangeur routier [Termes IGN] enrichissement sémantique [Termes IGN] reconnaissance d'objets [Termes IGN] segmentation d'image Résumé : (auteur) Spatial analysis and pattern recognition with vector spatial data is particularly useful to enrich raw data. In road networks, for instance, there are many patterns and structures that are implicit with only road line features, among which highway interchange appeared very complex to recognize with vector-based techniques. The goal is to find the roads that belong to an interchange, such as the slip roads and the highway roads connected to the slip roads. To go further than state-of-the-art vector-based techniques, this article proposes to use raster-based deep learning techniques to recognize highway interchanges. The contribution of this work is to study how to optimally convert vector data into small images suitable for state-of-the-art deep learning models. Image classification with a convolutional neural network (i.e., is there an interchange in this image or not?) and image segmentation with a u-net (i.e., find the pixels that cover the interchange) are experimented and give better results than existing vector-based techniques in this specific use case (99.5% against 74%). Numéro de notice : A2020-365 Affiliation des auteurs : LaSTIG COGIT (2012-2019) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1145/3382080 date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.1145/3382080 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95399 [article]

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An IEEE value loop of human-technology collaboration in geospatial information science / Liqiu Meng in Geo-spatial Information Science, vol 23 n° 1 (March 2020)  

Public [article]  inGeo-spatial Information Science > vol 23 n° 1 (March 2020) . - pp 61- 67 Titre : An IEEE value loop of human-technology collaboration in geospatial information science Type de document : Article/Communication Auteurs : Liqiu Meng, Auteur Année de publication : 2020 Article en page(s) : pp 61- 67 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique [Termes IGN] analyse géovisuelle [Termes IGN] approche holistique [Termes IGN] données localisées numériques [Termes IGN] enrichissement sémantique [Termes IGN] éthique [Termes IGN] géographie sociale [Termes IGN] information sémantique [Termes IGN] intégration de données [Termes IGN] intelligence artificielle [Termes IGN] interface homme-machine [Termes IGN] recherche interdisciplinaire [Termes IGN] web sémantique Résumé : (auteur) Geosensing and social sensing as two digitalization mainstreams in big data era are increasingly converging toward an integrated system for the creation of semantically enriched digital Earth. Along with the rapid developments of AI technologies, this convergence has inevitably brought about a number of transformations. On the one hand, value-adding chains from raw data to products and services are becoming value-adding loops composed of four successive stages – Informing, Enabling, Engaging and Empowering (IEEE). Each stage is a dynamic loop for itself. On the other hand, the “human versus technology” relationship is upgraded toward a game-changing “human and technology” collaboration. The information loop is essentially shaped by the omnipresent reciprocity between humans and technologies as equal partners, co-learners and co-creators of new values. The paper gives an analytical review on the mutually changing roles and responsibilities of humans and technologies in the individual stages of the IEEE loop, with the aim to promote a holistic understanding of the state of the art of geospatial information science. Meanwhile, the author elicits a number of challenges facing the interwoven human-technology collaboration. The transformation to a growth mind-set may take time to realize and consolidate. Research works on large-scale semantic data integration are just in the beginning. User experiences of geovisual analytic approaches are far from being systematically studied. Finally, the ethical concerns for the handling of semantically enriched digital Earth cover not only the sensitive issues related to privacy violation, copyright infringement, abuse, etc. but also the questions of how to make technologies as controllable and understandable as possible for humans and how to keep the technological ethos within its constructive sphere of societal influence. Numéro de notice : A2020-163 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10095020.2020.1718004 date de publication en ligne : 23/01/2020 En ligne : https://doi.org/10.1080/10095020.2020.1718004 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94823 [article]

Composition of place: towards a compositional view of functional space / Emmanuel Papadakis in Cartography and Geographic Information Science, Vol 47 n° 1 (January 2020)  

Public [article]  inCartography and Geographic Information Science > Vol 47 n° 1 (January 2020) . - pp 28 - 45 Titre : Composition of place: towards a compositional view of functional space Type de document : Article/Communication Auteurs : Emmanuel Papadakis, Auteur ; Bernd Resch, Auteur ; Thomas Blaschke, Auteur Année de publication : 2020 Article en page(s) : pp 28 - 45 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] approche holistique [Termes IGN] enrichissement sémantique [Termes IGN] information géographique [Termes IGN] interaction humain-espace [Termes IGN] modélisation spatiale [Termes IGN] organisation spatiale [Termes IGN] représentation spatiale [Termes IGN] système d'information géographique Résumé : (Auteur) A long-standing question in GIScience is whether geographic information systems (GIS) facilitates an adequate quantifiable representation of the concept of place. Considering the difficulties of quantifying elusive concepts related to place, several researchers focus on more tangible dimensions of the human understanding of place. The most common approaches are semantic enrichment of spatial information and holistic conceptualization of the notion of place. However, these approaches give emphasis on either space or human meaning, or they mainly exist as concepts without practically proven usable artifacts. A partial answer to this problem was proposed by the function-based model that treats place as functional space. This paper focuses primarily on the level of composition, describing and formalizing it as a rule-based framework with the following objectives: (a) contribute to the formalization efforts of the notion of place and its integration within GIS and (b) maintain tangible properties intertwined with the human understanding of place. The operationalization potential of the proposed framework is illustrated with an example of identifying the shopping areas in an urban region. The results show that the proposed model is able to capture all shopping malls as well as other areas that are not explicitly labeled as such but still function similarly to a shopping mall. Numéro de notice : A2020-006 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1598894 date de publication en ligne : 06/06/2019 En ligne : https://doi.org/10.1080/15230406.2019.1598894 Format de la ressource électronique : URL Sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94343 [article]

Génération de cartes tactiles photoréalistes pour personnes déficientes visuelles par apprentissage profond / Gauthier Fillières-Riveau in Revue internationale de géomatique, vol 30 n° 1-2 (janvier - juin 2020)  

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SEH-SDB : a semantically enriched historical spatial database for documentation and preservation of monumental heritage based on CityGML / Reda Yaagoubi in Applied geomatics, vol 11 n° 1 (March 2019)  

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Enrichissement d'orthophotographie par des données OpenStreetMap pour l'apprentissage machine / Gauthier Fillières-Riveau (2019)    

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Integration of lidar data and GIS data for point cloud semantic enrichment at the point level / Harith Aljumaily in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)  

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Land cover mapping at very high resolution with rotation equivariant CNNs : Towards small yet accurate models / Diego Marcos in ISPRS Journal of photogrammetry and remote sensing, vol 145 - part A (November 2018)  

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OpenStreetMap data quality enrichment through awareness raising and collective action tools—experiences from a European project / Amin Mobasheri in Geo-spatial Information Science, vol 21 n° 3 (October 2018)  

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A framework for annotating OpenStreetMap objects using geo-tagged tweets / Xin Chen in Geoinformatica [en ligne], vol 22 n° 3 (July 2018)  

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Visual analytics of human mobility behavior / Robert Lutz Krüger (2017) 

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European handbook of crowdsourced geographic information, ch. 14. Querying VGI by semantic enrichment / Robert Lemmens (2016)    

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Extraction et Gestion des Connaissances, EGC 2008, 8es journées francophones, 29 janvier 2008, Sophia Antipolis, France / Marie-Aude Aufaure Portier (2008)

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