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...

詳細記述

書誌詳細

出版年:	ISPRS International Journal of Geo-Information
主要な著者:	Aphiwe Madubedube, Serena Coetzee, Victoria Rautenbach
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2021-03-01
主題:	volunteered geographic information crowdsourcing data quality intrinsic quality assessment contributors OpenStreetMap
オンライン･アクセス:	https://www.mdpi.com/2220-9964/10/3/156