Operationalizing Central Place Theory and Central Flow Theory with mobile phone data
- Published
- Accepted
- Subject Areas
- Data Science, Network Science and Online Social Networks
- Keywords
- mobile phone data, central place theory, data for development, central flow theory
- Copyright
- © 2015 Doran et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Operationalizing Central Place Theory and Central Flow Theory with mobile phone data. PeerJ PrePrints 3:e1342v1 https://doi.org/10.7287/peerj.preprints.1342v1
Abstract
Central Place and Central Flow Theory are geographic principles explaining why and how cities develop across large regional spaces. Central Place Theory postulates that cities self-organize into a spatial hierarchy were small numbers of very large ‘Central Places’ support numerous surrounding and less developed ‘Low Places’, while ‘Middle Places’ develop at the periphery of where Central Places carry spatial influence. Central Flow Theory is a comple- mentary notion that explains the cooperative development of cities through joint information sharing. Both theories are often discussed, with multiple regional development and economic models built upon their tenents. However, it is very difficult to quantify the degree to which Central Place and Central Flow Theory explains the development and positions of cities in a region, particularly in developing countries where socioeconomic data is difficult to collect. To facilitate these measurements, this paper presents a way to operationalize Central Place and Central Flow Theory using mobile phone data collected across a region. It defines a set of mobile phone data attributes that are related to basic facets of the two theories, and demonstrates how their measurements speak to the degree to which the theories hold in the region the mobile phone data covers. The theory is then applied in a case study where promising locations for economic investment in a developing nation are identified.
Author Comment
This is a preprint submission to PeerJ Computer Science.