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Auteur Hardeep Singh Rai |
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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]