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Network-Based Functional Regions

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  • Carson J Q Farmer
  • A Stewart Fotheringham

Abstract

For administration efficiency most countries subdivide their national territory into administrative regions. These regions are used to delineate areas which are internally well connected and relatively cohesive, especially compared with the links between regions. Hence, many countries seek to delineate local labour markets (LLMs): geographical regions where the majority of the local population seeks employment and from which the majority of local employers recruit labour. LLM boundaries are often based on functional regions, which represent the aggregate commuting patterns of the local population. A number of regionalisation procedures for objectivity delineating functional regions have been suggested, though many of these procedures require the use of ad hoc parameters to control the size and number of regions. Recently, a range of network-based alternatives have been developed in the literature. One of the most successful such methods is based on the concept of modularity: the extent to which there are dense connections within functional regions, but only sparse connections between functional regions. In this paper we maximise the modularity of a network of commuting flows to produce a regionalisation that exhibits less interaction than expected between regions. We demonstrate the effectiveness of this type of regionalisation procedure on a simulated geographical network, as well as using commuting data for the Republic of Ireland. We suggest that this new method has specific advantages over existing regionalisation procedures, particularly in the context of disaggregate commuting patterns of socioeconomic subgroups.

Suggested Citation

  • Carson J Q Farmer & A Stewart Fotheringham, 2011. "Network-Based Functional Regions," Environment and Planning A, , vol. 43(11), pages 2723-2741, November.
  • Handle: RePEc:sae:envira:v:43:y:2011:i:11:p:2723-2741
    DOI: 10.1068/a44136
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    References listed on IDEAS

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    5. Yunfeng Hu & Yueqi Han, 2019. "Identification of Urban Functional Areas Based on POI Data: A Case Study of the Guangzhou Economic and Technological Development Zone," Sustainability, MDPI, vol. 11(5), pages 1-15, March.

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