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

TL;DR

This study uses city-bike stopover data to identify and analyze spatial patterns of urban attractiveness, revealing hotspots and dynamics in Krakow through a novel, generalizable method.

Contribution

It introduces a new method to analyze city-bike stopovers for understanding urban attractiveness, applicable across different cities and datasets.

Findings

Hotspots identified at tourist and leisure attractions

Emerging new places with frequent stopovers

Method effectively reveals spatial attractiveness patterns

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 on the case-study of Krakow (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 both 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.