LIPIcs.GISCIENCE.2018.43.pdf
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Towards a Comprehensive Temporal Classification of Footfall Patterns in the Cities of Great Britain (Short Paper)
Authors
Karlo Lugomer 
,
Paul Longley
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Volume:
10th International Conference on Geographic Information Science (GIScience 2018)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: International Conference on Geographic Information Science (GIScience) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2018-08-02
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Author Details
- Department of Geography, University College London, Pearson Building, Gower Street, WC1E 6BT, London, United Kingdom
Cite As Get BibTex
Karlo Lugomer and Paul Longley. Towards a Comprehensive Temporal Classification of Footfall Patterns in the Cities of Great Britain (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 43:1-43:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.GISCIENCE.2018.43
Abstract
The temporal fluctuations of footfall in the urban areas have long been a neglected research problem, and this mainly has to do with the past technological limitations and inability to consistently collect large volumes of data at fine intra-day temporal resolutions. This paper makes use of the extensive set of footfall measurements acquired by the Wi-Fi sensors installed in the retail units across the British town centres, shopping centres and retail parks. We present the methodology for classifying the diurnal temporal signatures of human activity at the urban microsite locations and identify characteristic profiles which make them distinctive regarding when people visit them. We conclude that there exist significant differences regarding the time when different locations are the busiest during the day, and this undoubtedly has a substantial impact on how retailers should plan where and how their businesses operate.
Subject Classification
ACM Subject Classification
- Information systems → Geographic information systems
Keywords
- temporal classification
- temporal profiles
- time series cluster analysis
- Wi-Fi sensors
- retail analytics
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References
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