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Auteur Ross S. Purves |
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Affiner la recherche Interroger des sources externesStreets 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)
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]
Titre : Fictive motion extraction and classification Type de document : Article/Communication Auteurs : Ekaterina Egorova, Auteur ; Ludovic Moncla Année de publication : 2018 Article en page(s) : pp 2247 - 2271 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] Alpes
[Termes IGN] base de règles
[Termes IGN] corpus
[Termes IGN] extraction automatique
[Termes IGN] traitement du langage naturelRésumé : (Auteur) Fictive motion (e.g. ‘The highway runs along the coast’) is a pervasive phenomenon in language that can imply both a static and a moving observer. In a corpus of alpine narratives, it is used in three types of spatial descriptions: conveying the actual motion of the observer, describing a vista and communicating encyclopaedic spatial knowledge. This study takes a knowledge-based approach to develop rules for automated extraction and classification of these types based on an annotated corpus of fictive motion instances. In particular, we identify the differences in the set of concepts involved into the production of the three types of descriptions, followed by their linguistic operationalization. Based on that, we build a set of rules that classify fictive motion with an overall precision of 0.87 and recall of 0.71. The article highlights the importance of examining spatially rich, naturally occurring corpora for the lines of work dealing with the automated interpretation of spatial information in texts, as well as, more broadly, investigation of spatial language involved into various types of spatial discourse. Numéro de notice : A2018-524 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1498503 Date de publication en ligne : 30/07/2018 En ligne : https://doi.org/10.1080/13658816.2018.1498503 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91349
in International journal of geographical information science IJGIS > vol 32 n° 11-12 (November - December 2018) . - pp 2247 - 2271[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2018061 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : European handbook of crowdsourced geographic information Type de document : Monographie Auteurs : Cristina Capineri, Éditeur scientifique ; Muki M. Haklay, Éditeur scientifique ; Haosheng Huang, Éditeur scientifique ; Vyron Antoniou, Éditeur scientifique ; Juhani Kettunen, Éditeur scientifique ; Franck O. Ostermann, Éditeur scientifique ; Ross S. Purves, Éditeur scientifique Editeur : Londres : Ubiquity press Année de publication : 2016 Importance : 476 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-1-909188-80-8 Langues : Anglais (eng) Note de contenu : Chapter 1. Introduction
Part I: Theoretical and social aspects
Chapter 2. The nature of volunteered geographic information (Cristina Capineri)
Chapter 3. Why is participation inequality important? (Mordechai (Muki) Haklay)
Chapter 4. Social Media Geographic Information: Why social is special when it goes spatial? (Michele Campagna)
Part II: Quality: Criteria and methodologies
Chapter 5. Handling quality in crowdsourced geographic information (Laura Criscuolo, Paola Carrara, Gloria Bordogna, Monica Pepe, Francesco Zucca, Roberto Seppi, Alessandro Oggioni and Anna Rampini)
Chapter 6. Data quality in crowdsourcing for biodiversity research: issues and examples (Clemens Jacobs)
Chapter 7. Semantic Challenges for Volunteered Geographic Information (Andrea Ballatore)
Chapter 8. Quality analysis of the Parisian OSM toponyms evolution (Vyron Antoniou, Guillaume Touya and Ana-Maria Raimond)
Chapter 9. Tackling the thematic accuracy of areal features in OpenStreetMap (Ahmed Loai Ali)
Chapter 10. Enhancing the management of quality of VGI: contributions from context and task modelling (Benedicte Bucher, Gilles Falquet, Claudine Metral and Rob Lemmens)
Part III: Data analytics
Chapter 11. A methodological toolbox for exploring collections of textually annotated georeferenced photographs (Ross S. Purves and William A. Mackaness)
Chapter 12. Gaining Knowledge from Georeferenced Social Media Data with Visual Analytics (Gennady Andrienko and Natalia Andrienko)
Chapter 13. Head/tail Breaks for Visualization of City Structure and Dynamics (Bin Jiang)
Chapter 14. Querying VGI by semantic enrichment (Rob Lemmens, Gilles Falquet, Stefano De Sabbata, Bin Jiang and Benedicte Bucher)
Chapter 15. Extracting Location Information from Crowd-sourced Social Network Data (Pinar Karagoz, Halit Oguztuzun, Ruket Cakici, Ozer Ozdikis, Kezban Dilek Onal and Meryem Sagcan)
Chapter 16. Spatial and Temporal Sentiment Analysis of Twitter data (Zhiwen Song and Jianhong (Cecilia) Xia)
Chapter 17. Social Networks VGI: Twitter Sentiment Analysis of Social Hotspots (Dario Stojanovski, Ivan Chorbev, Ivica Dimitrovski and Gjorgji Madjarov)
Chapter 18. Research on social media feeds – A GIScience perspective (Enrico Steiger, Rene Westerholt and Alexander Zipf)
Part IV: VGI and crowdsourcing in environmental monitoring
Chapter 19. Changing role of citizens in the national environmental monitoring (Juhani Kettunen, Jari Silander, Matti Lindholm, Maiju Lehtiniemi, Outi Setälä and Seppo Kaitala)
Chapter 20. On the contribution of Volunteered Geographic Information to land monitoring efforts (Jamal Jokar Arsanjani and Cidália C. Fonte)
Chapter 21. Discussing the potential of crowdsourced geographic information for urban areas monitoring using the panoramio initiative (Flavio Lupia and Jacinto Estima)
Chapter 22. AtrapaelTigre.com: enlisting citizen-scientists in the war on tiger mosquitoes (Aitana Oltra, John R.B. Palmer and Frederic Bartumeus)
Chapter 23. Crowdsourcing geographic information for disaster risk management and improving urban resilience: an overview of the lessons learned (João Porto de Albuquerque, Melanie Eckle, Benjamin Herfort and Alexander Zipf)
Part V: VGI in mobility
Chapter 24. Crowdsourcing for individual needs - the case of routing and navigation for mobility-impaired persons (Alexander Zipf, Amin Mobasheri, Adam Rousell and Stefan Hahmann)
Chapter 25. Smart Timetable Service Based on Crowdsensed Data (Károly Farkas)
Chapter 26. Mobile crowd-sensing in the Smart City (Imre Lendák)
Chapter 27. Mobile crowd sensing for smart urban mobility (Dragan Stojanovic, Bratislav Predic and Natalija Stojanovic)
Part VI: VGI in spatial planning
Chapter 28. Using mobile crowdsourcing and geotagged social media data to study people’s affective responses to environments (Haosheng Huang and Georg Gartner)
Chapter 29. Integrating Authoritative and Volunteered Geographic Information for spatial planning (Pierangelo Massa and Michele Campagna)
Chapter 30. A Proposed Crowdsourcing Cadastral Model: Taking Advantage of Previous Experience and Innovative Techniques (Sofia Basiouka and Chryssy Potsiou)
Chapter 31. Modelling the world in 3D from VGI/Crowdsourced data (Hongchao Fan and Alexander Zipf)
Glossary (Linda See, Cristina Capineri and Sofia Basiouka)Numéro de notice : 17356 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5334/bax En ligne : https://doi.org/10.5334/bax Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83781
- European handbook of crowdsourced geographic information, ch. 8. Quality analysis of the Parisian OSM toponyms evolution / Vyron Antoniou (2016)
- European handbook of crowdsourced geographic information, ch. 10. Enhancing the management of quality of VGI: contributions from context and task modelling / Bénédicte Bucher (2016)
- European handbook of crowdsourced geographic information, ch. 12. Gaining knowledge from georeferenced social media data with visual analytics / Gennady Andrienko (2016)
- European handbook of crowdsourced geographic information, ch. 14. Querying VGI by semantic enrichment / Robert Lemmens (2016)
Documents numériques
en open access
European handbook of crowdsourced geographic informationAdobe Acrobat PDFProceedings of the 9th Workshop on Geographic Information Retrieval, GIR'2015 / Ross S. Purves (2015)
Titre : Proceedings of the 9th Workshop on Geographic Information Retrieval, GIR'2015 : Proceedings of the 9th Workshop on Geographic Information Retrieval Type de document : Actes de congrès Auteurs : Ross S. Purves, Éditeur scientifique ; Christopher B. Jones, Éditeur scientifique ; GIR 2015, 9th Workshop on Geographic Information Retrieval (26 - 27 novembre 2015), Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2015 Conférence : GIR 2015, 9th Workshop on Geographic Information Retrieval 26/11/2015 27/11/2015 Paris France Proceedings ACM Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] recherche d'information géographiqueNuméro de notice : 17315 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Actes DOI : sans En ligne : http://dl.acm.org/citation.cfm?id=2837689&picked=prox Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83167
Titre : Exploring and visualizing differences in geographic and linguistic web coverage Type de document : Article/Communication Auteurs : Ramya Venkateswaran, Auteur ; Robert Weibel, Auteur ; Ross S. Purves, Auteur Année de publication : 2014 Article en page(s) : pp 852 – 876 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] couverture (données géographiques)
[Termes IGN] densité de population
[Termes IGN] exploration de données
[Termes IGN] information géographique
[Termes IGN] langage naturel (informatique)
[Termes IGN] Suisse
[Termes IGN] visualisation de donnéesRésumé : (Auteur) This article reports on a study performed to understand the geographic and linguistic coverage of web resources, focusing on the example of tourism-related themes in Switzerland. Search engine queries of web documents were used to gather counts for phrases in four different languages. The study focused on selected populated places and tourist attractions in Switzerland from three gazetteer datasets: topographic gazetteer data from the Swiss national mapping agency (SwissTopo); POI data from a commercial data provider (Tele Atlas) and user generated geographic content (geonames.org). The web counts illustrate the geographic extent and trends of web coverage of tourism for different languages. Results show that coverage for local languages, i.e. German, French and Italian, is more strongly related to the region of the spoken language. Correlation of the web counts to typical tourism indicators, e.g. population and number of hotel nights rented per year, are also computed and compared. Numéro de notice : A2014-574 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12071 Date de publication en ligne : 27/01/2014 En ligne : https://doi.org/10.1111/tgis.12071 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74764
in Transactions in GIS > vol 18 n° 6 (December 2014) . - pp 852 – 876[article]vol 22 n° 3 - march 2008 - Geographical information retrieval (Bulletin de International journal of geographical information science IJGIS) / C. Jones
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