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Modalflow: cross-origin flow data visualization for urban mobility / Ignacio Pérez-Messina in Algorithms, vol 13 n° 11 (November 2020)  

Public [article]  inAlgorithms > vol 13 n° 11 (November 2020) . - n° 298 Titre : Modalflow: cross-origin flow data visualization for urban mobility Type de document : Article/Communication Auteurs : Ignacio Pérez-Messina, Auteur ; Eduardo Graells-Garrido, Auteur ; María-Jesús Lobo , Auteur ; Christophe Hurter, Auteur Année de publication : 2020 Projets : 3-projet - voir note / Article en page(s) : n° 298 Note générale : bibliographie I.P.-M. and E.G.-G. were partially funded by CONICYT Fondecyt de Iniciación project #11180913. Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle [Termes IGN] cartographie des flux [Termes IGN] données localisées [Termes IGN] mobilité urbaine [Termes IGN] réalité augmentée [Termes IGN] visualisation de données [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Pervasive data have become a key source of information for mobility and transportation analyses. However, as a secondary source, it has a different methodological origin than travel survey data, usually relying on unsupervised algorithms, and so it requires to be assessed as a dataset. This assessment is challenging, because, in general, there is not a benchmark dataset or a ground truth scenario available, as travel surveys only represent a partial view of the phenomenon and suffer from their own biases. For this critical task, which involves urban planners and data scientists, we study the design space of the visualization of cross-origin, multivariate flow datasets. For this purpose, we introduce the Modalflow system, which incorporates and adapts different visualization techniques in a notebook-like setting, presenting novel visual encodings and interactions for flows with modal partition into scatterplots, flow maps, origin-destination matrices, and ternary plots. Using this system, we extract general insights on visual analysis of pervasive and survey data for urban mobility and assess a mobile phone network dataset for one metropolitan area. Numéro de notice : A2020-577 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/a13110298 Date de publication en ligne : 15/11/2020 En ligne : https://doi.org/10.3390/a13110298 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96454 [article]