Clustering Geo-data Cubes

Tool to perform cluster analysis of multi-dimensional geospatial data, running on local or distributed systems.

8
mentions
7
contributors

Cite this software

What Clustering Geo-data Cubes can do for you

  • Tool to perform co- and tri-cluster analysis
  • Targets geospatial data sets
  • Includes functionalities to refine the clustering using k-means
  • Multiple implementations to work with local or distributed systems

Clustering Geo-data Cubes (CGC) includes various implementations of co- and tri-clustering algorithms to efficiently carry out cluster analysis on both small and large data sets, using either local or distributed resources. Tutorials illustrate how to use this Python tool with real-world geospatial raster data.

Keywords
Programming languages
  • Python 47%
  • Jupyter Notebook 45%
  • TeX 8%
License
  • Apache-2.0
</>Source code
Packages
pypi.org

Participating organisations

University of Twente
Ins
Netherlands eScience Center

Mentions

Contributors

EI
Emma Izquierdo-Verdiguier
Institute of Geomatics, BOKU
Meiert Grootes
Meiert Grootes
Netherlands eScience Center
OK
Ou Ku
Netherlands eScience Center
RZM
Raul Zurita Milla
University of Twente
RG
Romulo Gonçalves
Netherlands eScience Center
SG
Serkan Girgin
University of Twente

Related projects

High spatial resolution phenological modelling at continental scales

Understanding phenological variability

Updated 12 months ago
Finished