Exploring five indicators for the quality of OpenStreetMap road networks: a case study of Québec, Canada

Abstract

OpenStreetMap (OSM) is one of the most well-known volunteered geographic information (VGI) projects that aims to produce a free-world map. However, there are serious concerns about its quality. Numerous studies have assessed the quality of OSM by comparing the OSM database with a reference database. Several researchers have proposed the use of quality indicators as variables that can describe OSM quality in regions where no reference data are available. A quality indicator is a variable that has a significant monotonic relationship with quality measures. In this study, a literature review was conducted to identify and define the main quality measures proposed for assessing the quality of linear features. Owing to limited access to current data, only three quality elements—completeness, positional accuracy, and attribute accuracy—were evaluated in this study. These quality measures were then used to assess the quality of the OSM roads in the province of Quebec. Finally, Spearman’s rank correlation coefficient test was applied to determine whether there was a significant correlation between the quality measures related to the three quality elements and the five potential quality indicators: population, average income, density of OSM roads, density of OSM buildings, and number of points of interest (POI). The main contribution of this study is testing the following hypothesis: “There is a significant correlation between the five mentioned variables and the measures related to the three quality elements”. Statistical analysis showed that in terms of completeness, the density of OSM roads and population were the best indicators; in terms of positional accuracy, population and income were the best indicators; and in terms of attribute accuracy, completeness was the best indicator. All five variables have significant correlations with the measures of the three elements of quality, except for the following two pairs (attribute accuracy, density of OSM roads) and (attribute accuracy, density of OSM buildings). This study proposes the density of OSM roads and number of POI as two new quality indicators that have not been found in the literature review.

Mapping roadless areas in regions with contrasting human footprint

“…Our results showed that the challenges of road mapping completeness, including factors such as user interest and the speed of road construction, are particularly pronounced in remote regions with low human influence, like boreal Canada. The quality of OSM road data largely varies due to differences in mapping accuracy and completeness across regions and user contributions 39 . Smaller OSM communities in certain areas result in fewer updates and additions to the road database, particularly in remote or relatively intact regions 35 , 40 .…”

Enhancing Spatial Accuracy of OpenStreetMap Data: A Geometric Approach

“…Initially, geographic data generation for OSM primarily involved the use of global positioning system (GPS) receivers to capture coordinates for upload to the database. With the advent of Bing map aerial imagery made available to OSM in November 2010, users were empowered to generate data through the digitization of aerial photographs as well [4].…”

Evaluating OSM Building Footprint Data Quality in Québec Province, Canada from 2018 to 2023: A Comparative Study

“…In regions where authoritative data are lacking, the feasibility of conducting quality assessments of OpenStreetMap (OSM) through direct comparison with such data is limited. This challenge has prompted researchers to investigate alternative methods, seeking quality indicators that can offer insights into the OSM quality in these data-scarce areas [15,[29][30][31][32][33].…”