Estimating the service population of a large metropolitan university campus

Charles-Edwards, Elin and Bell, Martin (2013) Estimating the service population of a large metropolitan university campus. Applied Spatial Analysis and Policy, 6 3: 209-228. doi:10.1007/s12061-012-9079-y

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Author Charles-Edwards, Elin
Bell, Martin
Title Estimating the service population of a large metropolitan university campus
Journal name Applied Spatial Analysis and Policy   Check publisher's open access policy
ISSN 1874-463X
Publication date 2013-09
Year available 2012
Sub-type Article (original research)
DOI 10.1007/s12061-012-9079-y
Open Access Status
Volume 6
Issue 3
Start page 209
End page 228
Total pages 20
Place of publication Dordrecht, Netherlands
Publisher Springer
Collection year 2013
Language eng
Abstract Conventional population estimates prepared by statistical agencies typically focus on the population resident in a given geographic area at a defined point in time, but in practice many locations undergo substantial daily, weekly and seasonal flux in population numbers. Such fluctuations exert wide-ranging impacts for goods and services in destination areas, such that increasing recognition is being given to the need for more refined estimates that capture these 'service populations'. While a number of methods have been proposed to count visitors or estimate temporary populations, systematic testing has been limited, and the evidence suggests that no single methodology is effective at multiple spatial and temporal scales. This paper utilises a hybrid approach which couples cordon counts based on multiple technologies with administrative data and an on-line survey to estimate the daily, weekly and seasonal fluctuation in the population of a large Australian metropolitan University campus. Our results trace the rise and fall of the campus population over the course of the day, identify the scale and duration of the peak, and show how population numbers vary from day to day and over the course of the teaching semester. We track aggregate flows to and from Campus by mode of travel and find they significantly exceed the on-campus population peak, underlining its sensitivity to timetabling of classes and other events. We also identify strong correlations between data sources which assist in validating the estimates and, together with evolving technologies, offer potential avenues for substantial cost saving in future estimations.
Keyword Commuting
Daytime populations
Population estimates
Service populations
Temporary mobility
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online: 19 August 2012.

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
Official 2013 Collection
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 4 times in Scopus Article | Citations
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Created: Mon, 04 Feb 2013, 12:10:10 EST by Ms Elin Charles-edwards on behalf of School of Geography, Planning & Env Management