Zone division and extraction of historic area based on big data

Zhu, He

doi:10.1080/13683500.2020.1814223

Cited by 8 publications

(1 citation statement)

References 65 publications

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“…Which, in turn, allows for a refined notion of tourism attractiveness at a national (Mitra, 2020), regional (Cracolici & Nijkamp, 2009), city (Van der Ark & Richards, 2006), or site (Jacobsen et al, 2019) level. Which, however, becomes challenging when within-urban attractiveness needs to be delimited (Zhu, 2020).…”

Section: Urban Space Attractivenessmentioning

confidence: 99%

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

Banet

Kucharski

Naumov

2022

Current Issues in Tourism

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We demonstrate how digital traces of city-bike trips may become useful to identify urban space attractiveness. We exploit their unique featurestopovers: 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.

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