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

Fuente: arXiv
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Autores principales: Banet, Krystian, Kucharski, Rafal, Naumov, Vitalii
Formato: Preprint
Publicado: 2021
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author Banet, Krystian
Kucharski, Rafal
Naumov, Vitalii
author_facet Banet, Krystian
Kucharski, Rafal
Naumov, Vitalii
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2104_04493
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Using city-bike stopovers to reveal spatial patterns of urban attractiveness
Banet, Krystian
Kucharski, Rafal
Naumov, Vitalii
Physics and Society
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.
title Using city-bike stopovers to reveal spatial patterns of urban attractiveness
topic Physics and Society
url https://arxiv.org/abs/2104.04493