Access to green spaces in urban regions is vital for the well-being of citizens. In this article, we present data on green space quality and path distances to different types of green spaces. The path distances represent green space accessibility using active travel modes (walking, cycling). The path distances were calculated using the pedestrian street network across the seven largest urban regions in Finland. We derived the green space typology from the Urban Atlas Data that is available across functional urban areas in Europe and enhanced it with national data on water bodies, conservation areas and recreational facilities and routes from Finland. We extracted the walkable street network from OpenStreetMap and calculated shortest paths to different types of green spaces using open-source Python programming tools. Network distances were calculated up to ten kilometers from each green space edge and the distances were aggregated into a 250 m × 250 m statistical grid that is interoperable with various statistical data from Finland. The geospatial data files representing the different types of green spaces, network distances across the seven urban regions, as well as the processing and analysis scripts are shared in an open repository. These data offer actionable information about green space accessibility in Finnish urban regions and support the integration of green space quality and active travel modes into further research and planning activities.

Value of the Data

• Data on green space quality and accessibility covering largest urban regions in Finland allows regional comparisons.

• These data allow researchers, local planners and decision-makers to investigate the spatial accessibility and quality of green spaces.

• The data can support impact assessments of land use development options and help to avoid fragmenting and reducing the diversity of green spaces.

• Information about green space quality helps to integrate varying perspectives of green space use from citizens’ point of view into further assessments.

• The accessibility data are interoperable with various statistical data from Finland.

• Open method and open data allow reproducibility over time and beyond the study area.

Specifications Table Subject: Geography Specific subject area: Green space quality and spatial accessibility Type of data: Table Spatial database: (GeoPackage) How the data were acquired: The green space typology was derived from Urban Atlas data [1] and further modified using ancillary data on water bodies and conservation areas [2], [3], [4], and recreation facilities and routes from the Lipas sport facility GIS database [5]. The street network data were acquired from OpenStreetMap (OSM) downloaded in Protocolbuffer Binary Format (PBF) from https://www.geofabrik.de/. Network distances were calculated based on OSM pedestrian street network. Data acquisition and network analysis were conducted using the Python programming language (version 3.8) and standard geospatial Python libraries such as geopandas (version 0.8.2). Pyrosm library (version 0.6.1) was used for fetching and cropping the network data, and Pandana library (version 0.6) was used for calculating network distances to nearest green spaces across the study regions. Data format: Raw, Analyzed Description of data collection: Green space data were compiled for seven largest urban regions in Finland. Green space edges were converted into a set of points to serve as potential access points. Network analysis was conducted from each node in the walkable network to network nodes associated with green space edges. If origin location was inside green space, then distance was set to 0 m. If distance was 10,000 m or greater, distance was set to NULL. Final values were averaged into a 250 m x 250 m statistical grid. Data source location: Raw data for green areas: Urban Atlas Raw data for water bodies: Shoreline10 and Shoreline250 Raw data for conservation areas: The nature protected areas and wilderness reserves dataset Raw data for facilities and routes: LIPAS database Raw data for pedestrian network: OpenStreetMap Urban core areas: continuous inner and outer urban areas combined as delineated in urban–rural classification Statistical grid: 250 m x 250 m grid Raw data for building locations: Building and Dwelling Register Functional Urban Regions in Finland with more than 100,000 inhabitants: Helsinki, Jyväskylä, Kuopio, Lahti, Oulu, Tampere and Turku: Urban Atlas

Data accessibility: Repository name: Zenodo Data identification number: 10.5281/zenodo.8091921 Direct URL to data: https://doi.org/10.5281/zenodo.8091921 Related research article: A. Viinikka, M. Tiitu, V. Heikinheimo, J.I. Halonen, E. Nyberg, K. Vierikko, Associations of neighborhood-level socioeconomic status, accessibility, and quality of green spaces in Finnish urban regions, Appl. Geogr. 157 (2023) 102973. https://doi.org/10.1016/j.apgeog.2023.102973.