Microscale walkability indicators for fifty-nine European central urban areas: An open-access tabular dataset and a geospatial web-based platform

Abstract

A growing body of empirical findings suggests that more satisfactory, compact, and traversable built environments can positively influence active travel, physical activity, and the walking experience. To this end, planning for better and more walkable places has been identified as a hot topic in urban studies and public health research, since. However, European-level indicators assessing aspects of pedestrian-friendly urban environments are largely lacking. This article introduces spatial and tabular data files of 17 pre-processed and microscale walkability indicators. The dataset presents relevant to the pedestrian environment information for 59 central urban areas from 26 European countries and aims to support policy analysis and assessment related to healthy and low-carbon transportation systems as well as sustainable communities. Methodologically, we applied a virtual (i.e., Google Street View) street audit tool, block-by-block and on both sides of each street and crossing segment separately. To this end, we digitized in polyline features observations and evaluations for a total of 112.577 street- and/or crossing-segments. The data collection process was a demanding and challenging process, which lasted for 21 months and involved 46 trained observers. The data tables in this paper present processed data of each audited item topic as a total share of street segments or crossings length by city. More specifically, the data tables contain indicators that describe the following seventeen themes: percent of segments with predominant commercial or/and entertainment buildings (active uses), percent of segments with access to park/plaza, percent of segments with transit stop(s), percent of segments with available public seats, percent of segments according to their street lighting conditions, percent of segments with well-maintained buildings, percent of segments where graffiti is not present, percent of segments where a bike lane is present, percent of segments where a sidewalk is present, percent of segments with well-maintained sidewalks, percent of segments with sidewalk buffers, percent of segments according to shading levels, percent of segments with wider sidewalks, percent of segments according to the number of road traffic lanes, percent of crossings with a pedestrian walk signal, percent of crossings with curb(s) ramp and percent of crossings with a marked pedestrian crosswalk. Additionally, a dedicated web-GIS platform has been designed and developed to visualize and disseminate collected data in openly available density maps of high spatial resolution (50 m × 50 m). The above data can be utilized to both raise awareness of unsatisfactory pedestrian environments and appoint them as a key health and environmental issue, as well as to assist European policy-makers to apply urban mobility strategies and monitor progress in urban sustainability and public health goals.

Keywords: City center; European Cities; Pedestrian Planning; Physical activity; Urban Design; Urban Indicators; Urban Mobility; Walkability.

Fig. 1

Visualization of the topics covered by the data indicators.

Fig. 2

Preview of the geospatial platform and the provided spatial dataset in density (decile) maps (URL link: http://geochoros.survey.ntua.gr/walkandthecitycenter/app-map).

Fig. 3

Preview of the web-platform and the ranking function of cities per each indicator (URL link: http://geochoros.survey.ntua.gr/walkandthecitycenter/cities).

Fig. 4

Preview of the web-platform and the compare graphs tool (URL link: http://geochoros.survey.ntua.gr/walkandthecitycenter/chart).

Fig. 5

Data collection process.

Fig. 6

A screenshot from the GIS environment presenting the structure of the street- and crossing-segments (raw) GIS data.

Fig. 7

A screenshot from the GIS environment that demonstrates the structure of the attribute table.

Fig. B-1

European-level quantile (n = 10) maps of indicators S1_1, S2_12, S3_12, S4_1, S5_2, S6_1 (indicator codes are available in the supplementary tabular dataset).

Fig. B-2

European-level quantile (n = 10) maps of indicators S7_0, S8_0, S9_0, S10_1, S11_1, S12_12 (indicator codes are available in the supplementary tabular dataset).

Fig. B-3

European-level quantile (n = 10) maps of indicators S13_1, S14_0, C11_1, C12_0, C13_1 (indicator codes are available in the supplementary tabular dataset).