Using Linked Open Geo Boundaries for Adaptive Delineation of Functional Urban Areas

  • Ali KhaliliEmail author
  • Peter van den Besselaar
  • Klaas Andries de Graaf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11155)


The concentration of people, companies, research organizations and other activities in urban areas is a key process in the development of economies and societies. In order to investigate how these urban systems function, the OECD (Organization for Economic Co-operation and Development) in collaboration with EC (European Commission) and Eurostat have introduced the concept of Functional Urban Areas (FUAs). FUAs consider a preliminary set of socio-economic and environmental factors and provide a basis for an agreed definition for measuring development of metropolitan areas. However, because FUAs are predefined they do not meet the need for designing policies and research questions involving different types of urban areas that are defined by weighting some factors more than others or by using additional factors. Therefore, providing an adaptive approach for dynamic and multi-faceted delineation of FUAs, rather than merely relying on a rigid schema with a fixed list of FUAs per country, allows to more flexibly reflect the socio-economic geography of where people live and work. This adaptive definition of FUAs demands integration of data from multiple up-to-date linked data sources. In this paper, we describe an approach and implementation for a Linked Open Geo-Data space, which combines openly available spatial and non-spatial resources on the Web to classify urban areas with the aim to more flexibly monitor and research urban development.



We would like to thank our colleagues from the Knowledge Representation & Reasoning research group at Vrije Universiteit Amsterdam for their helpful comments during the development of our approach for delineation of functional urban areas. This work was supported by a grant from the European Union’s 7th Framework Programme provided for the project RISIS (GA no. 313082).


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Ali Khalili
    • 1
    Email author
  • Peter van den Besselaar
    • 2
  • Klaas Andries de Graaf
    • 1
  1. 1.Department of Computer ScienceVrije Universiteit AmsterdamAmsterdamNetherlands
  2. 2.Department of Organization SciencesVrije Universiteit AmsterdamAmsterdamNetherlands

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