Littérature scientifique sur le sujet « Cartographie crowdsourcée »
Créez une référence correcte selon les styles APA, MLA, Chicago, Harvard et plusieurs autres
Consultez les listes thématiques d’articles de revues, de livres, de thèses, de rapports de conférences et d’autres sources académiques sur le sujet « Cartographie crowdsourcée ».
À côté de chaque source dans la liste de références il y a un bouton « Ajouter à la bibliographie ». Cliquez sur ce bouton, et nous générerons automatiquement la référence bibliographique pour la source choisie selon votre style de citation préféré : APA, MLA, Harvard, Vancouver, Chicago, etc.
Vous pouvez aussi télécharger le texte intégral de la publication scolaire au format pdf et consulter son résumé en ligne lorsque ces informations sont inclues dans les métadonnées.
Articles de revues sur le sujet "Cartographie crowdsourcée"
Dodge, Martin, et Rob Kitchin. « Crowdsourced Cartography : Mapping Experience and Knowledge ». Environment and Planning A : Economy and Space 45, no 1 (janvier 2013) : 19–36. http://dx.doi.org/10.1068/a44484.
Texte intégralGrove, Nicole Sunday. « The cartographic ambiguities of HarassMap : Crowdmapping security and sexual violence in Egypt ». Security Dialogue 46, no 4 (août 2015) : 345–64. http://dx.doi.org/10.1177/0967010615583039.
Texte intégralBallatore, Andrea, et Peter Mooney. « Conceptualising the geographic world : the dimensions of negotiation in crowdsourced cartography ». International Journal of Geographical Information Science 29, no 12 (6 août 2015) : 2310–27. http://dx.doi.org/10.1080/13658816.2015.1076825.
Texte intégralGkeli, M., C. Potsiou et C. Ioannidis. « DESIGN OF A CROWDSOURCED 3D CADASTRAL TECHNICAL SOLUTION ». ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020 (24 août 2020) : 269–76. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2020-269-2020.
Texte intégralCalvini-Lefebvre, Marc, Lucy Delap, Sarah Richardson et Claire Sorin-Delpuech. « Digital Humanities, Citizen Science and Feminist History : The Promise and Limits of Digital Mapping ». Histoire sociale / Social History 56, no 116 (novembre 2023) : 453–70. http://dx.doi.org/10.1353/his.2023.a914572.
Texte intégralAnderson, Cary. « Quantifying Emotion : Survey Methods and Sentiment Analysis in Cartographic Design Research ». Abstracts of the ICA 1 (15 juillet 2019) : 1–2. http://dx.doi.org/10.5194/ica-abs-1-8-2019.
Texte intégralBrennan-Horley, Chris, Louisa Smith, Dennis Frost et Lyn Phillipson. « Getting People with Dementia onto the Map : Scaffolding Qualitative GIS ». International Journal of Qualitative Methods 22 (janvier 2023) : 160940692311657. http://dx.doi.org/10.1177/16094069231165706.
Texte intégralChow, T. Edwin. « Estimating the Crowd Size of a Rally by Crowdsourcing-Geocomputation ». Abstracts of the ICA 1 (15 juillet 2019) : 1–2. http://dx.doi.org/10.5194/ica-abs-1-46-2019.
Texte intégralDodge, Martin, et Rob Kitchin. « Mapping Experience : Crowdsourced Cartography ». SSRN Electronic Journal, 2011. http://dx.doi.org/10.2139/ssrn.1921340.
Texte intégralQuinn, Sterling D., et Doran A. Tucker. « How geopolitical conflict shapes the mass-produced online map ». First Monday, 31 octobre 2017. http://dx.doi.org/10.5210/fm.v22i11.7922.
Texte intégralThèses sur le sujet "Cartographie crowdsourcée"
Stoven-Dubois, Alexis. « Robust Crowdsourced Mapping for Landmarks-based Vehicle Localization ». Electronic Thesis or Diss., Université Clermont Auvergne (2021-...), 2022. http://www.theses.fr/2022UCFAC116.
Texte intégralThe deployment of intelligent and connected vehicles, equipped with increasingly sophisticated equipment, and capable of sharing accurate positions and trajectories, is expected to lead to a substantial improvement of road safety and traffic efficiency. For this safety gain to become effective, vehicles will have to be accurately geo-positioned in a common reference, with an error up to a few decimeters [1]. To achieve this, they will be able to count on a variety of embedded sensors, such as GNSS (Global Navigation Satellite Systems) receivers, as well as additional proprioceptive and perception sensors. Nevertheless, in order to guarantee accurate positioning in all conditions, including in dense zones where GNSS signals can get degraded by multi-path effects, it is expected that vehicles will need to use precise maps of the environment to support their localization algorithms.To build maps of the main highways, major automotive actors have made use of dedicated fleets of vehicles equipped with high-end sensors. Because of the associated high operational costs, they have been operating a limited number of vehicles, and remain unable to provide live updates of the maps and to register entire road networks. Crowdsourced mapping represents a cost-effective solution to this problem, and has been creating interest among automotive players. It consists in making use of measurements retrieved by multiple production vehicles equipped with standard sensors in order to build a map of landmarks. Nevertheless, while this approach appears promising, its real potential to build an accurate map of landmarks and maintain it up-to-date remains to be assessed in realistic, long-term scenarios.In this thesis, in a first time, we propose a crowdsourced mapping solution based on triangulation optimization, and evaluate it using field-tests. The result analysis shows the potential of crowdsourced mapping to take advantage from measurements issued by multiple vehicles. On the other hand, it also indicates some critical limitations associated with triangulation optimization.Therefore, in a second time, we propose another crowdsourced mapping solution based on graph optimization, and we introduce different approaches to include and update the map within the optimization, which correspond to different trade-offs between the map quality and computational scalability. Simulation experiments are conducted in order to compare the different approaches. The results enable to identify the most efficient one, and to assert that it provides a scalable solution for crowdsourced mapping.The robustness of this solution to various types of noises, such as auto-correlated and biased noises, is then evaluated using extended simulation tests. The results analysis show its ability to build an accurate map of landmarks in various noises conditions, making use of measurements retrieved by multiple vehicles. Subsequently, field-tests are performed to confirm the results obtained in simulation, and draw conclusions both from a theoretical and practical viewpoint. Finally, the capacity of our crowdsourced mapping solution to increase the localization capabilities of vehicles is evaluated in simulation. The results show the effectiveness of the proposed approach to improve positioning performances in various conditions, while also pointing out the importance of providing a map with a sufficient density of landmarks
Livres sur le sujet "Cartographie crowdsourcée"
Foody, Giles, Peter Mooney, Cidália Costa Fonte, Ana Maria Olteanu Raimond, Steffen Fritz et Linda See, dir. Mapping and the Citizen Sensor. London, United Kingdom : Ubiquity Press, 2017.
Trouver le texte intégralMooney, Peter, Giles Foody et Linda See. Mapping and the Citizen Sensor. Saint Philip Street Press, 2020.
Trouver le texte intégralChapitres de livres sur le sujet "Cartographie crowdsourcée"
Pődör, Andrea, et László Zentai. « Educational Aspects of Crowdsourced Noise Mapping ». Dans Advances in Cartography and GIScience, 35–46. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57336-6_3.
Texte intégralBallatore, Andrea, et Stefano De Sabbata. « Charting the Geographies of Crowdsourced Information in Greater London ». Dans Lecture Notes in Geoinformation and Cartography, 149–68. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78208-9_8.
Texte intégralIvanovic, Stefan S., Ana-Maria Olteanu-Raimond, Sébastien Mustière et Thomas Devogele. « Potential of Crowdsourced Traces for Detecting Updates in Authoritative Geographic Data ». Dans Lecture Notes in Geoinformation and Cartography, 205–21. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14745-7_12.
Texte intégralResch, Bernd, Anja Summa, Günther Sagl, Peter Zeile et Jan-Philipp Exner. « Urban Emotions—Geo-Semantic Emotion Extraction from Technical Sensors, Human Sensors and Crowdsourced Data ». Dans Lecture Notes in Geoinformation and Cartography, 199–212. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11879-6_14.
Texte intégralTruong, Quy Thy, Guillaume Touya et Cyril de Runz. « Building Social Networks in Volunteered Geographic Information Communities : What Contributor Behaviours Reveal About Crowdsourced Data Quality ». Dans Lecture Notes in Geoinformation and Cartography, 125–31. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63946-8_25.
Texte intégralvon Reumont, Frederik. « Taking the Battle to Cyberspace : Delineating Borders and Mapping Identities in Western Sahara ». Dans Media and Mapping Practices in the Middle East and North Africa. Nieuwe Prinsengracht 89 1018 VR Amsterdam Nederland : Amsterdam University Press, 2021. http://dx.doi.org/10.5117/9789462989092_ch03.
Texte intégralActes de conférences sur le sujet "Cartographie crowdsourcée"
Nobajas, Alexandre. « Targeted Crowdsourced Vectorisation of Historical Cartography ». Dans International Workshop on Automatic Vectorisation of Historical Maps. Department of Cartography and Geoinformatics ELTE, 2020. http://dx.doi.org/10.21862/avhm2020.09.
Texte intégral