Using city-bike stopovers to reveal spatial patterns of urban attractiveness

ABSTRACT

We demonstrate how digital traces of city-bike trips may become useful to identify urban space attractiveness. We exploit their unique feature – stopovers: short, non-traffic-related stops made by cyclists during their trips. As we demonstrate with the case study of Kraków (Poland), when applied to a big dataset, meaningful patterns appear, with hotspots (places with long and frequent stopovers) identified at both the top tourist and leisure attractions as well as emerging new places. We propose a generic method, applicable to any spatiotemporal city-bike traces, providing results meaningful to understand the general urban space attractiveness and its dynamics. With the proposed filtering (to mitigate a selection bias) and empirical cross-validation (to rule-out false-positive classifications) results effectively reveal spatial patterns of urban attractiveness. Valuable for decision-makers and analysts to enhance understanding of urban space consumption patterns by tourists and residents.

KEYWORDS:

• Bike-sharing system
• urban space
• tourist hotspots
• tourist attractiveness
• spatial-data
• digital footprints

Acknowledgments

We thank the City of Kraków, the operator of Wavelo city bike for the data for analysis.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 https://github.com/naumovvs/city-bikes-analysis.