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Data scale as cartography: a semi-automatic approach for thematic web map creation / Auriol Degbelo in Cartography and Geographic Information Science, vol 47 n° 2 (February 2020)
[article]
Titre : Data scale as cartography: a semi-automatic approach for thematic web map creation Type de document : Article/Communication Auteurs : Auriol Degbelo, Auteur ; Saad Sarfraz, Auteur ; Christian Kray, Auteur Année de publication : 2020 Article en page(s) : pp 153 - 170 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] accès aux données localisées
[Termes IGN] carte thématique
[Termes IGN] cartographie numérique
[Termes IGN] données ouvertes
[Termes IGN] échelle des données
[Termes IGN] géovisualisation
[Termes IGN] test statistique
[Termes IGN] web mappingRésumé : (auteur) Open government promises increased transparency by providing its citizens datasets about city processes. Open data portals have been emerging all over the world as mines of open geographic datasets. Thematic web maps are key to understanding these open geographic datasets. Current thematic web maps are created by programmers and/or cartographers, and thus are not designed to be easily reused with new geographic datasets. As a result, they pose several challenges to non-experts wanting to adapt them to new scenarios. This article introduces a semi-automatic approach for the creation of thematic web maps by and for users with no prior training in cartography. The approach relies on the mapping between Stevens’ data types and Bertin’s visual variables, to suggest (meaningful) thematic map visualizations for a given input geographic dataset. It was implemented as a web prototype in AngularJS and evaluated with 19 participants. Results from the user study suggest that despite facing a few challenges in accurately identifying Stevens’ data types, participants managed to successfully create web maps and correctly answer spatial questions. The prototype and insights gathered from the user study are relevant to making cartographic products more accessible to a broader population, and open geographic data more usable in the context of an open government. Numéro de notice : A2020-059 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1677176 Date de publication en ligne : 05/11/2019 En ligne : https://doi.org/10.1080/15230406.2019.1677176 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94576
in Cartography and Geographic Information Science > vol 47 n° 2 (February 2020) . - pp 153 - 170[article]Extending Processing Toolbox for assessing the logical consistency of OpenStreetMap data / Sukhjit Singh Sehra in Transactions in GIS, Vol 24 n° 1 (February 2020)
[article]
Titre : Extending Processing Toolbox for assessing the logical consistency of OpenStreetMap data Type de document : Article/Communication Auteurs : Sukhjit Singh Sehra, Auteur ; Jaiteg Singh, Auteur ; Hardeep Singh Rai, Auteur Année de publication : 2020 Article en page(s) : pp 44 - 71 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] cartographie collaborative
[Termes IGN] données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] données localisées libres
[Termes IGN] données routières
[Termes IGN] Inde
[Termes IGN] information sémantique
[Termes IGN] intégrité topologique
[Termes IGN] morphologie urbaine
[Termes IGN] OpenStreetMap
[Termes IGN] QGIS
[Termes IGN] qualité des donnéesRésumé : (auteur) OpenStreetMap (OSM) produces a huge amount of labeled spatial data, but its quality has always been a deep concern. Numerous quality issues have been discussed in the vast literature, while the fitness of OSM for road navigability is only partly explored. Navigability depends on logical consistency, which focuses on the existence of logical contradictions within a data set. Researchers have discussed the insufficiency of established methods and the lack of a computational paradigm to assess the quality of the OSM data. To address the research gaps, the current work extended the capabilities of the Quantum GIS Processing Toolbox for assessment of spatial data. The models and scripts developed are able to assess logical consistency based on geographical topological consistency, semantic information, and morphological consistency. The established and proxy indicators are selected for measuring the logical consistency of OSM data for navigability. For empirical validation, OSM Punjab data are compared with authoritative data from HERE (proprietary) and the Remote Sensing Centre (RSC), Punjab, India. The results conclude that even the proprietary road data sets are not free from logical inconsistencies and data contributed by the masses are credible and navigable. OSM has produced better results than the RSC, but needs more crowd contributions to improve its quality. Numéro de notice : A2020-101 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12587 Date de publication en ligne : 08/11/2019 En ligne : https://doi.org/10.1111/tgis.12587 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94692
in Transactions in GIS > Vol 24 n° 1 (February 2020) . - pp 44 - 71[article]Micro-tasking as a method for human assessment and quality control in a geospatial data import / Atle Frenvik Sveen in Cartography and Geographic Information Science, vol 47 n° 2 (February 2020)
[article]
Titre : Micro-tasking as a method for human assessment and quality control in a geospatial data import Type de document : Article/Communication Auteurs : Atle Frenvik Sveen, Auteur ; Anne Sofie Strom Erichsen, Auteur ; Terje Midtbo, Auteur Année de publication : 2020 Article en page(s) : pp 141 - 152 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] algorithme de filtrage
[Termes IGN] chevauchement
[Termes IGN] contrôle qualité
[Termes IGN] données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] évaluation des données
[Termes IGN] import de données
[Termes IGN] OpenStreetMap
[Termes IGN] précision des données
[Termes IGN] production participativeRésumé : (auteur) Crowd-sourced geospatial data can often be enriched by importing open governmental datasets as long as they are up-to date and of good quality. Unfortunately, merging datasets is not straight forward. In the context of geospatial data, spatial overlaps pose a particular problem, as existing data may be overwritten when a naïve, automated import strategy is employed. For example: OpenStreetMap has imported over 100 open geospatial datasets, but the requirement for human assessment makes this a time-consuming process which requires experienced volunteers or training. In this paper, we propose a hybrid import workflow that combines algorithmic filtering with human assessment using the micro-tasking method. This enables human assessment without the need for complex tools or prior experience. Using an online experiment, we investigated how import speed and accuracy is affected by volunteer experience and partitioning of the micro-task. We conclude that micro-tasking is a viable method for massive quality assessment that does not require volunteers to have prior experience working with geospatial data. Numéro de notice : A2020-058 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1659187 Date de publication en ligne : 16/09/2020 En ligne : https://doi.org/10.1080/15230406.2019.1659187 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94575
in Cartography and Geographic Information Science > vol 47 n° 2 (February 2020) . - pp 141 - 152[article]Volcano-seismic transfer learning and uncertainty quantification with bayesian neural networks / Angel Bueno in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
[article]
Titre : Volcano-seismic transfer learning and uncertainty quantification with bayesian neural networks Type de document : Article/Communication Auteurs : Angel Bueno, Auteur ; Carmen Benitez, Auteur ; Silvio De Angelis, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] apprentissage profond
[Termes IGN] classification bayesienne
[Termes IGN] classification par réseau neuronal
[Termes IGN] forme d'onde
[Termes IGN] incertitude des données
[Termes IGN] réseau bayesien
[Termes IGN] réseau neuronal profond
[Termes IGN] Russie
[Termes IGN] séisme
[Termes IGN] sismologie
[Termes IGN] surveillance géologique
[Termes IGN] volcanologie
[Termes IGN] Washington (Etats-Unis ; état)Résumé : (auteur) Over the past few years, deep learning (DL) has emerged as an important tool in the fields of volcano and earthquake seismology. However, these methods have been applied without performing thorough analyses of the associated uncertainties. Here, we propose a solution to enhance volcano-seismic monitoring systems, through probabilistic Bayesian DL; we implement and demonstrate a workflow for waveform classification, rapid quantification of the associated uncertainty, and link these uncertainties to changes in volcanic unrest. Specifically, we introduce Bayesian neural networks (BNNs) to perform event identification, classification, and their estimated uncertainty on data gathered at two active volcanoes, Mount St. Helens, Washington, USA, and Bezymianny, Kamchatka, Russia. We demonstrate how BNNs achieve excellent performance (92.08%) in discriminating both the type of event and its origin when the two data sets are merged together, and no additional training information is provided. Finally, we demonstrate that the data representations learned by the BNNs are transferable across different eruptive periods. We also find that the estimated uncertainty is related to changes in the state of unrest at the volcanoes and propose that it could be used to gauge whether the learned models may be exported to other eruptive scenarios. Numéro de notice : A2020-094 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2941494 Date de publication en ligne : 07/10/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2941494 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94657
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 2 (February 2020) . - pp[article]
Titre : 3rd International Workshop on Spatial Data Quality (SDQ 2020) : Joint Workshop of EuroGeographics - EuroSDR - OGC - ISO TC 211 - ICA Type de document : Actes de congrès Auteurs : Jonathan Holmes, Éditeur scientifique ; Carol Agius, Éditeur scientifique ; Joep Crompvoets, Éditeur scientifique Editeur : Dublin : European Spatial Data Research EuroSDR Année de publication : 2020 Collection : EuroSDR Workshop report Conférence : SDQ 2020, 3rd International Workshop on Spatial Data Quality 28/01/2020 29/01/2020 La Vallette Malte Open Access Proceedings Importance : 84 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] données localisées
[Termes IGN] qualité des donnéesRésumé : (éditeur) This workshop report presents the highlights of the EuroGeographics/EuroSDR/OGC/ISO TC 211/ICA workshop on Spatial Data Quality that took place on 28 and 29 January 2020 in Valletta, Malta Numéro de notice : 14262 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Actes DOI : sans Date de publication en ligne : 01/12/2020 En ligne : http://www.eurosdr.net/sites/default/files/uploaded_files/eurosdr_spatial_data_q [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96899 PermalinkAssessment of inner reliability in the Gauss-Helmert model / Andreas Ettlinger in Journal of applied geodesy, vol 14 n° 1 (January 2020)PermalinkPermalinkCollaborative user oriented metadata production on EuroSDR Geometadatalabs platform [paper and diaporama] / Bénédicte Bucher (2020)PermalinkComparing supervised learning algorithms for Spatial Nominal Entity recognition / Amine Medad (2020)PermalinkDéveloppement d’une méthode d’intégration systématique des capteurs dans le BIM pour les constructions durables / Yasmine El Khadraoui (2020)PermalinkDéveloppement d’outils ad-hoc open source pour des applications Web cartographiques / Bruno Verchère (2020)PermalinkDiagnostic qualité et apurement des données de mobilité quotidienne issues de l’enquête mixte et longitudinale Mobi’Kids / Sylvestre Duroudier in Revue internationale de géomatique, vol 30 n° 1-2 (janvier - juin 2020)PermalinkPermalinkFeuilles de route de la recherche européenne sur les big geodata du passé [diaporama] / Bénédicte Bucher (2020)Permalink