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Documents authored by Zhang, Xianghui

Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.80
The Ups and Downs of London High Streets Throughout COVID-19 Pandemic: Insights from Footfall-Based Clustering Analysis (Short Paper)

Authors: Xinglei Wang, Xianghui Zhang, and Tao Cheng

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
As an important part of the economic and social fabric of urban areas, high streets were hit hard during the COVID-19 pandemic, resulting in massive closures of shops and plunge of footfall. To better understand how high streets respond to and recover from the pandemic, this paper examines the performance of London’s high streets, focusing on footfall-based clustering analysis. Applying time series clustering to longitudinal footfall data derived from a mobile phone GPS dataset spanning over two years, we identify distinct groups of high streets with similar footfall change patterns. By analysing the resulting clusters' footfall dynamics, composition and geographic distribution, we uncover the diverse responses of different high streets to the pandemic disruption. Furthermore, we explore the factors driving specific footfall change patterns by examining the number of local and nonlocal visitors. This research addresses gaps in the existing literature by presenting a holistic view of high street responses throughout the pandemic and providing in-depth analysis of footfall change patterns and underlying causes. The implications and insights can inform strategies for the revitalisation and redevelopment of high streets in the post-pandemic era.
Cite as

Xinglei Wang, Xianghui Zhang, and Tao Cheng. The Ups and Downs of London High Streets Throughout COVID-19 Pandemic: Insights from Footfall-Based Clustering Analysis (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 80:1-80:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{wang_et_al:LIPIcs.GIScience.2023.80,
  author =	{Wang, Xinglei and Zhang, Xianghui and Cheng, Tao},
  title =	{{The Ups and Downs of London High Streets Throughout COVID-19 Pandemic: Insights from Footfall-Based Clustering Analysis}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{80:1--80:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.80},
  URN =		{urn:nbn:de:0030-drops-189754},
  doi =		{10.4230/LIPIcs.GIScience.2023.80},
  annote =	{Keywords: High street, performance, footfall, clustering analysis, COVID-19}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.92
Unlocking the Power of Mobile Phone Application Data to Accelerate Transport Decarbonisation (Short Paper)

Authors: Xianghui Zhang and Tao Cheng

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
Decarbonising transport is crucial in addressing climate change and achieving the Net Zero target. However, limitations arising from traditional data sources and methods obstruct the provision of individual travel information with comprehensive travel modes, high spatiotemporal granularity and updating frequency for achieving transport decarbonisation. Mobile phone application data, an essentially new form of data, can provide valuable travel information after effective mining and assist in progress monitoring, policy evaluation, and system optimisation in transport decarbonisation. This paper proposes a standardised methodology to unlock the power of mobile phone application data for supporting transport decarbonisation. Three typical cases are employed to demonstrate the capabilities of the generated individual multimodal dataset, including monitoring Londoners’ 20-minute active travel target, transport GHGs emissions and their contributors, and evaluating small-scale transport interventions. The paper also discusses the limitations of mobile phone application data, such as issues surrounding data privacy and regulation.
Cite as

Xianghui Zhang and Tao Cheng. Unlocking the Power of Mobile Phone Application Data to Accelerate Transport Decarbonisation (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 92:1-92:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{zhang_et_al:LIPIcs.GIScience.2023.92,
  author =	{Zhang, Xianghui and Cheng, Tao},
  title =	{{Unlocking the Power of Mobile Phone Application Data to Accelerate Transport Decarbonisation}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{92:1--92:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.92},
  URN =		{urn:nbn:de:0030-drops-189873},
  doi =		{10.4230/LIPIcs.GIScience.2023.92},
  annote =	{Keywords: Transport decarbonisation, Mobile phone application data, Application, London}
}
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