Spatial Data Mining for Clustering: An Application to the Florentine Metropolitan Area Using RedCap

  • Federico Benassi
  • Chiara Bocci
  • Alessandra Petrucci
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


The paper presents an original application of the recently proposed RedCap method of spatial clustering and regionalization on the Florentine Metropolitan Area (FMA). Demographic indicators are used as the input of a spatial clustering and regionalization model in order to classify the FMA’s municipalities into a number of demographically homogeneous as well as spatially contiguous zones. In the context of a gradual decentralization of governance activities we believe the FMA is a representative case of study and that the individuation of new spatial areas built considering both the demographic characteristics of the resident population and the spatial dimension of the territory where this population insists could become a useful tool for local governance.


Spatial Cluster Demographic Structure Destination Area Young Couple Spatial Contiguity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Federico Benassi
    • 1
  • Chiara Bocci
    • 1
  • Alessandra Petrucci
    • 1
  1. 1.Department of Statistics “G. Parenti”University of FlorenceFlorenceItaly

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