Encyclopedia of GIS

2017 Edition
| Editors: Shashi Shekhar, Hui Xiong, Xun Zhou

3D Crisp Clustering of Geo-Urban Data

  • Suhaibah Azri
  • Alias Abdul Rahman
  • Uznir Ujang
  • François Anton
  • Darka Mioc
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-17885-1_1610



Crisp clustering is a technique to cluster objects into group without having overlapping partitions. Each data point is either belongs to or not to a group. Most of the clustering algorithms are categorized as crisp clustering. There are several categories of crisp clustering algorithm such as partitional algorithm, hierarchical algorithm, density-based algorithm, and grid-based algorithm. The general definition of each group could be defined as follows (Kovács et al.  2005):
  • Partitional algorithms: divide the data into a set of separate category. This algorithm attempts to define the number of partitions to optimize a certain criterion function. This optimization is an iterative procedure.

  • Hierarchical algorithms: This algorithm creates clusters repeatedly by merging a small cluster into a larger cluster. It also split cluster into several small...

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© Springer International Publishing AG 2017

Authors and Affiliations

  • Suhaibah Azri
    • 1
  • Alias Abdul Rahman
    • 1
  • Uznir Ujang
    • 1
  • François Anton
    • 2
  • Darka Mioc
    • 3
  1. 1.Department of Geoinformation 3D GIS Research LabUniversiti Teknologi MalaysiaJohor BahruMalaysia
  2. 2.Department of GeodesyTechnical University of DenmarkLyngbyDenmark
  3. 3.Department of GeodesyTechnical University of DenmarkLyngbyDenmark