Longitudinal spatial dataset on travel times and distances by different travel modes in Helsinki Region

Abstract

Comparable data on spatial accessibility by different travel modes are frequently needed to understand how city regions function. Here, we present a spatial dataset called the Helsinki Region Travel Time Matrix that has been calculated for 2013, 2015 and 2018. This longitudinal dataset contains travel time and distance information between all 250 metres statistical grid cell centroids in the Capital Region of Helsinki, Finland. The dataset is multimodal and multitemporal by nature: all typical transport modes (walking, cycling, public transport, and private car) are included and calculated separately for the morning rush hour and midday for an average working day. We followed a so-called door-to-door principle, making the information between travel modes comparable. The analyses were based primarily on open data sources, and all the tools that were used to produce the data are openly available. The matrices form a time-series that can reveal the accessibility conditions within the city and allow comparisons of the changes in accessibility in the region, which support spatial planning and decision-making.

Measurement(s)	spatiotemporal_interval • Spatial Qualifier • travel time by public transport • travel time by private car • travel time by walking • travel time by cycling • travel distance by public transport • travel distance by private car • travel distance by walking • travel distance by cycling
Technology Type(s)	computational modeling technique • digital curation • directed network graph construction • node shortest path identification
Factor Type(s)	transport mode • year • time of day
Sample Characteristic - Environment	anthropogenic environment
Sample Characteristic - Location	Helsinki • Espoo • Vantaa • Municipality of Kauniainen

Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.11841462