Urban delineation through a prism of intraday commute patterns
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F24%3A00135789" target="_blank" >RIV/00216224:14310/24:00135789 - isvavai.cz</a>
Result on the web
<a href="https://www.frontiersin.org/articles/10.3389/fdata.2024.1356116/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fdata.2024.1356116/full</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3389/fdata.2024.1356116" target="_blank" >10.3389/fdata.2024.1356116</a>
Alternative languages
Result language
angličtina
Original language name
Urban delineation through a prism of intraday commute patterns
Original language description
Introduction Urban mobility patterns are crucial for effective urban and transportation planning. This study investigates the dynamics of urban mobility in Brno, Czech Republic, utilizing the rich dataset provided by passive mobile phone data. Understanding these patterns is essential for optimizing infrastructure and planning strategies.Methods We developed a methodological framework that incorporates bidirectional commute flows and integrates both urban and suburban commute networks. This comprehensive approach allows for a detailed representation of Brno's mobility landscape. By employing clustering techniques, we aimed to identify distinct mobility patterns within the city.Results Our analysis revealed consistent structural features within Brno's mobility patterns. We identified three distinct clusters: a central business district, residential communities, and an intermediate hybrid cluster. These clusters highlight the diversity of mobility demands across different parts of the city.Discussion The study demonstrates the significant potential of passive mobile phone data in enhancing our understanding of urban mobility patterns. The insights gained from intraday mobility data are invaluable for transportation planning decisions, allowing for the optimization of infrastructure utilization. The identification of distinct mobility patterns underscores the practical utility of our methodological advancements in informing more effective and efficient transportation planning strategies.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10100 - Mathematics
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Frontiers in Big Data
ISSN
2624-909X
e-ISSN
2624-909X
Volume of the periodical
7
Issue of the periodical within the volume
March 2024
Country of publishing house
CH - SWITZERLAND
Number of pages
8
Pages from-to
1-8
UT code for WoS article
001186671100001
EID of the result in the Scopus database
2-s2.0-85188088920