Extended Fuzzy C-Means Clustering in GIS Environment for Hot Spot Events

  • Ferdinando Di Martino
  • Vincenzo Loia
  • Salvatore Sessa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4692)


The Extended Fuzzy C-Means (EFCM) algorithm in a Geographic Information System (GIS) is used for identifying the volume clusters as Hot Spot areas, being the data events geo-referenced as points on the geographic map. We have implemented EFCM with the usage of the software tools ESRI/ARCGIS and ESRI/ARCVIEW 3.x and moreover we have made a comparison with the classical Fuzzy C-Means (FCM) algorithm. The application concerns a specific problem of maintenance, executed in the years 2001-2005, over the buildings constructed before 1960 in the city of Cava de’ Tirreni, located in the district of Salerno (Italy).


Fuzzy C-Means EFCM GIS Hot Spot Event Spatial Analysis 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ferdinando Di Martino
    • 1
  • Vincenzo Loia
    • 1
  • Salvatore Sessa
    • 2
  1. 1.Università degli Studi di Salerno, Dipartimento di Matematica e Informatica, Via Ponte Don Melillo, 84084 Fisciano (Salerno)Italy
  2. 2.Università degli Studi di Napoli Federico II, Dipartimento di Costruzioni e Metodi, Matematici in Architettura, Via Monteoliveto 3, 80134 NapoliItaly

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