Conference paper Open Access

The exploration of human activity zones using geo-tagged big data during the COVID-19 first lockdown in London, UK

Chen, Tongxin; Cheng, Tao; Zhu, Di


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  <identifier identifierType="DOI">10.5281/zenodo.4670050</identifier>
  <creators>
    <creator>
      <creatorName>Chen, Tongxin</creatorName>
      <givenName>Tongxin</givenName>
      <familyName>Chen</familyName>
      <affiliation>SpaceTimeLab for Big Data Analytics, Department of Civil, Environmental and Geomatic Engineering, University College London, London WC1E 6BT, UK</affiliation>
    </creator>
    <creator>
      <creatorName>Cheng, Tao</creatorName>
      <givenName>Tao</givenName>
      <familyName>Cheng</familyName>
      <affiliation>SpaceTimeLab for Big Data Analytics, Department of Civil, Environmental and Geomatic Engineering, University College London, London WC1E 6BT, UK</affiliation>
    </creator>
    <creator>
      <creatorName>Zhu, Di</creatorName>
      <givenName>Di</givenName>
      <familyName>Zhu</familyName>
      <affiliation>Department of Geography, Environment and Society, University of Minnesota, Twin Cities, MN 55455, USA</affiliation>
    </creator>
  </creators>
  <titles>
    <title>The exploration of human activity zones using geo-tagged big data during the COVID-19 first lockdown in London, UK</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Issued">2021-04-07</date>
  </dates>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4670050</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4670049</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Exploring the human activity zones (HAZs) gives significant insights into understanding the complex urban environment and reinforcing urban management and planning. Though previous studies have reported the significant human activity shifting at the city-level in global metropolises due to COVID-19 containment policies, the dynamic of human activity across urban areas at space and time during such an ever-changing socioeconomic period has not been examined and discussed hitherto. In this study, we proposed an analysis framework to explore the human activities zones using geo-tagged big data in London, UK. We first utilised the activity- detection method to extract visits/stops at space and time as the human activity metric from the mobile phone GPS trajectory data. Then, we characterised HAZs based on the homogeneity of hourly human activity footfalls on the middle layer super output areas (MSOAs). The results show the HAZs not only exhibit declines in human activity but are strongly associated with urban land-use and population variables during the COVID-19 pandemic.&lt;/p&gt;</description>
  </descriptions>
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