Improving the Quality of Citizen Contributed Geodata through Their Historical Contributions: The Case of the Road Network in OpenStreetMap

Afsaneh Nasiri · Rahim Ali Abbaspour · Alireza Chehreghan · Jamal Jokar Arsanjani

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Geographic Information Systems Studies 3D Modeling in Geospatial Applications Automated Road and Building Extraction

Abstract

OpenStreetMap (OSM) has proven to serve as a promising free global encyclopedia of maps with an increasing popularity across different user communities and research bodies. One of the unique characteristics of OSM has been the availability of the full history of users’ contributions, which can leverage our quality control mechanisms through exploiting the history of contributions. Since this aspect of contributions (i.e., historical contributions) has been neglected in the literature, this study aims at presenting a novel approach for improving the positional accuracy and completeness of the OSM road network. To do so, we present a five-stage approach based on a Voronoi diagram that leads to improving the positional accuracy and completeness of the OSM road network. In the first stage, the OSM data history file is retrieved and in the second stage, the corresponding data elements for each object in the historical versions are identified. In the third stage, data cleaning on the historical datasets is carried out in order to identify outliers and remove them accordingly. In the fourth stage, through applying the Voronoi diagram method, one representative version for each set of historical versions is extracted. In the final stage, through examining the spatial relations for each object in the history file, the topology of the target object is enhanced. As per validation, a comparison between the latest version of the OSM data and the result of our approach against a reference dataset is carried out. Given a case study in Tehran, our findings reveal that the completeness and positional precision of OSM features can be improved up to 14%. Our conclusions draw attention to the exploitation of the historical archive of the contributions in OSM as an intrinsic quality indicator.

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References

2010How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets 2010Quality Assessment of the French OpenStreetMap Dataset 2013A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis 2010How Many Volunteers Does it Take to Map an Area Well? The Validity of Linus’ Law to Volunteered Geographic Information 2011The Street Network Evolution of Crowdsourced Maps: OpenStreetMap in Germany 2007–2011 2012Analyzing the Contributor Activity of a Volunteered Geographic Information Project — The Case of OpenStreetMap 2010A Comparative Study of Proprietary Geodata and Volunteered Geographic Information for Germany 2016European Handbook of Crowdsourced Geographic Information

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2024Research on multiscale OpenStreetMap in China: data quality assessment with EWM-TOPSIS and GDP modeling 2021Analysing the Impact of Large Data Imports in OpenStreetMap 2021Reliability extracted from the history file as an intrinsic indicator for assessing the quality of OpenStreetMap 2023Evaluating OSM Building Footprint Data Quality in Québec Province, Canada from 2018 to 2023: A Comparative Study

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