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Developing a flexible framework for spatiotemporal population modeling

Developing a flexible framework for spatiotemporal population modeling
Developing a flexible framework for spatiotemporal population modeling
This article proposes a general framework for modeling population distributions in space and time. This is particularly pertinent to a growing range of applications that require spatiotemporal specificity; for example, to inform planning of emergency response to hazards. Following a review of attempts to construct time-specific representations of population, we identify the importance of assembling an underlying data model at the highest resolution in each of the spatial, temporal, and attribute domains. This model can then be interrogated at any required intersection of these domains. We argue that such an approach is necessary to moderate the effects of what we term the modifiable spatiotemporal unit problem in which even detailed spatial data might be inadequate to support time-sensitive analyses. We present an initial implementation of the framework for a case study of Southampton, United Kingdom, using bespoke software (SurfaceBuilder247). We demonstrate the generation of spatial population distributions for multiple reference times using currently available data sources. The article concludes by setting out key research areas including the enhancement and validation of spatiotemporal population methods and models
0004-5608
754-772
Martin, David
e5c52473-e9f0-4f09-b64c-fa32194b162f
Cockings, Samantha
53df26c2-454e-4e90-b45a-48eb8585e800
Leung, Samuel
97eabff8-58eb-45f8-a3c5-cbe085665789
Martin, David
e5c52473-e9f0-4f09-b64c-fa32194b162f
Cockings, Samantha
53df26c2-454e-4e90-b45a-48eb8585e800
Leung, Samuel
97eabff8-58eb-45f8-a3c5-cbe085665789

Martin, David, Cockings, Samantha and Leung, Samuel (2015) Developing a flexible framework for spatiotemporal population modeling Annals of the Association of American Geographers, 105, (4), pp. 754-772. (doi:10.1080/00045608.2015.1022089).

Record type: Article

Abstract

This article proposes a general framework for modeling population distributions in space and time. This is particularly pertinent to a growing range of applications that require spatiotemporal specificity; for example, to inform planning of emergency response to hazards. Following a review of attempts to construct time-specific representations of population, we identify the importance of assembling an underlying data model at the highest resolution in each of the spatial, temporal, and attribute domains. This model can then be interrogated at any required intersection of these domains. We argue that such an approach is necessary to moderate the effects of what we term the modifiable spatiotemporal unit problem in which even detailed spatial data might be inadequate to support time-sensitive analyses. We present an initial implementation of the framework for a case study of Southampton, United Kingdom, using bespoke software (SurfaceBuilder247). We demonstrate the generation of spatial population distributions for multiple reference times using currently available data sources. The article concludes by setting out key research areas including the enhancement and validation of spatiotemporal population methods and models

Other 00045608.2015.1022089 - Accepted Manuscript
Available under License Other.
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Accepted/In Press date: 1 August 2014
Published date: 13 May 2015
Organisations: Geography & Environment

Identifiers

Local EPrints ID: 380540
URI: https://eprints.soton.ac.uk/id/eprint/380540
ISSN: 0004-5608
PURE UUID: d21db5c3-3691-489b-b167-02840aa81fb0
ORCID for David Martin: ORCID iD orcid.org/0000-0003-0397-0769

Catalogue record

Date deposited: 11 Sep 2015 14:26
Last modified: 17 Jul 2017 20:35

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Contributors

Author: David Martin ORCID iD
Author: Samuel Leung

University divisions

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