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Hierarchical Clustering through Spatial Interaction Data. The Case of Commuting Flows in South-Eastern France

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Computational Science and Its Applications - ICCSA 2011 (ICCSA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6782))

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Abstract

Regional scientists’ methods to partition space in functional areas meet complex system analysts’ methods to detect communities in networks. A common concern is the detection of hierarchical sets of clusters representing underlying structures. In this paper modularity optimization in complex networks is compared to polarized functional area definition through dominant flows. Different approaches to the significance of dominant flows are also tested, namely threshold and Multiple Linkage Analysis approaches.

Both methods are applied recursively in order to obtain a hierarchical clustering of municipalities in the PACA region (France) based on commuting flows in 1999. The comparison focuses on the geographical meaning of the results of the analyses. Modularity optimization and dominant flow results agree in many points and highlight the inadequacy of official methods integrating administrative boundaries in functional area definition. When they differ, they offer complementary views on the urban structure of the PACA region.

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Authors and Affiliations

  1. UMR ESPACE, University of Nice Sophia-Antipolis, Nice, France

    Giovanni Fusco & Matteo Caglioni

Authors
  1. Giovanni Fusco
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  2. Matteo Caglioni
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Editor information

Editors and Affiliations

  1. L.I.S.U.T. - D.A.P.I.T., Basilicata University Potenza, 10, Viale dell’Ateneo Lucano, 85100, Potenza, Italy

    Beniamino Murgante

  2. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli, 1, 06123, Perugia, Italy

    Osvaldo Gervasi

  3. Department of Applied Mathematics and Computational Sciences, University of Cantabria, Avda. de los Castros, s/n, C.P. 39005, Santander, Spain

    Andrés Iglesias

  4. School of Business Systems, Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  5. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, Higashi-ku, 813-8503, Fukuoka, Japan

    Bernady O. Apduhan

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Fusco, G., Caglioni, M. (2011). Hierarchical Clustering through Spatial Interaction Data. The Case of Commuting Flows in South-Eastern France. In: Murgante, B., Gervasi, O., Iglesias, A., Taniar, D., Apduhan, B.O. (eds) Computational Science and Its Applications - ICCSA 2011. ICCSA 2011. Lecture Notes in Computer Science, vol 6782. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21928-3_10

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  • DOI: https://doi.org/10.1007/978-3-642-21928-3_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21927-6

  • Online ISBN: 978-3-642-21928-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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