High-quality data on existing bicycle infrastructure are a requirement for evidence-based bicycle network planning, which supports a green transition of human mobility. However, this requirement is rarely met: Data from governmental agencies or crowdsourced projects like OpenStreetMap often suffer from unknown, heterogeneous, or low quality. Currently available tools for road network data quality assessment often fail to account for network topology, spatial heterogeneity, and bicycle-specific data characteristics. To fill these gaps, we introduce BikeDNA, an open-source tool for reproducible quality assessment tailored to bicycle infrastructure data with a focus on network structure and connectivity. BikeDNA performs either a standalone analysis of one data set or a comparative analysis between OpenStreetMap and a reference data set, including feature matching. Data quality metrics are considered both globally for the entire study area and locally on grid cell level, thus exposing spatial variation in data quality. Interactive maps and HTML/PDF reports are generated to facilitate the visual exploration and communication of results. BikeDNA supports quality assessments of bicycle infrastructure data for a wide range of applications -- from urban planning to OpenStreetMap data improvement or network research for sustainable mobility.
翻译:关于现有自行车基础设施的高质量数据是循证自行车网络规划的一项要求,它支持人类流动的绿色过渡。然而,这一要求很少得到满足。来自政府机构或众源项目(如OpenStreetMap)的数据往往不为人所知、杂交或质量低。目前可用于公路网络数据质量评估的工具往往没有考虑到网络地形、空间差异和自行车特有的数据特点。为填补这些空白,我们引入了BikeDNA,这是一个针对自行车基础设施数据的可复制质量评估的公开来源工具,以网络结构和连接为重点。BikeDNA对一个数据集进行独立分析,或者对OpenStreetMap和参考数据集进行比较分析,包括特征匹配。数据质量指标被视为全球范围整个研究领域和局部网格水平的数据质量指标,从而暴露了数据质量的空间差异。我们制作了互动式地图和HTML/PDF报告,以便利对结果进行直观探索和交流。BikeDNA支持对自行车基础设施数据进行质量评估,用于从城市规划到OnStreeMap移动或可持续研究网络的广泛应用。</s>