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Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases

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Bibliographic Details
Published in:Journal of Spatial Information Science
Format: Online Article RSS Article
Published: 2021
Subjects:
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container_title Journal of Spatial Information Science
description
discipline_display Geography
discipline_facet Geography
format Online Article
RSS Article
genre Journal Article
id rss_article:70514
institution FRELIP
journal_source_facet Journal of Spatial Information Science
publishDate 2021
publishDateSort 2021
record_format rss_article
spellingShingle Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases
Geography
General
Geography
sub_discipline_display General
sub_discipline_facet General
subject_display Geography
General
Geography
Geography
General
Geography
subject_facet Geography
General
Geography
title Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases
title_auth Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases
title_full Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases
title_fullStr Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases
title_full_unstemmed Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases
title_short Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases
title_sort towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases
topic Geography
General
Geography
url https://digitalcommons.library.umaine.edu/josis/vol2021/iss22/2