A Contributor-Focused Intrinsic Quality Assessment of OpenStreetMap in Mozambique Using Unsupervised Machine Learning

A Contributor-Focused Intrinsic Quality Assessment of OpenStreetMap in Mozambique Using Unsupervised Machine Learning

Anyone can contribute geographic information to OpenStreetMap (OSM), regardless of their level of experience or skills, which has raised concerns about quality. When reference data is not available to assess the quality of OSM data, intrinsic methods that assess the data and its metadata can be used...

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Manylion Llyfryddiaeth
Prif Awduron: Aphiwe Madubedube, Serena Coetzee, Victoria Rautenbach
Fformat: Erthygl
Iaith:English
Cyhoeddwyd: MDPI AG 2021-03-01
Cyfres:ISPRS International Journal of Geo-Information
Pynciau:
volunteered geographic information
crowdsourcing
data quality
intrinsic quality assessment
contributors
OpenStreetMap
Mynediad Ar-lein:https://www.mdpi.com/2220-9964/10/3/156

Rhyngrwyd

https://www.mdpi.com/2220-9964/10/3/156

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