Difference between revisions of "Lesson07"

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<font size="6">'''Geographical Segmentation with Spatially Constrained Cluster Analysis'''</font>
  
 
=Content=
 
=Content=
* What is geospatial analytics?
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* Basic concepts of geographic segmentation
* Motivation of promoting geospatial analytics
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* Conventional cluster analysis techniques
* Case study
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* Approaches for clustering geographical referenced data
* An overview of Geographic Information Systems (GIS)
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** Hierarchical clustering with spatial constraints
* GIS versus Geospatial Analytics
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** Minimum spanning trees
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** Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning (Redcap)
  
Lesson 7: Geographical Segmentation with Spatially Constrained Cluster Analysis
 
• Basic concepts of geographic segmentation
 
• Conventional cluster analysis techniques
 
• Approaches for clustering geographical referenced data
 
o Hierarchical clustering with spatial constraints
 
o Minimum spanning trees
 
o Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning (Redcap)
 
  
References
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=References=
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==Methods==
  
 
Assuncao, R. M., Neves, M.C., Camara, G. and Costa Freitas, C.D. 2006. “Efficient Regionalization Techniques for Socio-Economic Geographical Units Using Minimum Spanning Trees.” International Journal of Geographical Information Science 20: 797–811.
 
Assuncao, R. M., Neves, M.C., Camara, G. and Costa Freitas, C.D. 2006. “Efficient Regionalization Techniques for Socio-Economic Geographical Units Using Minimum Spanning Trees.” International Journal of Geographical Information Science 20: 797–811.
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Guo, D. 2008. “Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning (Redcap).” International Journal of Geographical Information Science, 22(7): 801-823.  
 
Guo, D. 2008. “Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning (Redcap).” International Journal of Geographical Information Science, 22(7): 801-823.  
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==Applications==
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=R Packages=
  
  

Revision as of 23:32, 8 January 2019

Claraview.png IS415 GeoSpatial Analytics and Applications

About

Weekly Session

Take-home Exercises

Geospatial Analytics Project

Course Resources

 


Geographical Segmentation with Spatially Constrained Cluster Analysis

Content

  • Basic concepts of geographic segmentation
  • Conventional cluster analysis techniques
  • Approaches for clustering geographical referenced data
    • Hierarchical clustering with spatial constraints
    • Minimum spanning trees
    • Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning (Redcap)


References

Methods

Assuncao, R. M., Neves, M.C., Camara, G. and Costa Freitas, C.D. 2006. “Efficient Regionalization Techniques for Socio-Economic Geographical Units Using Minimum Spanning Trees.” International Journal of Geographical Information Science 20: 797–811.

Chavent, M., Kuentz-Simonet, V., Labenne,A. and Saracco, J. 2018. “ClustGeo: an R package for hierarchical clustering with spatial constraints” Computational Statistics. 33: 1799-1822.

Guo, D. 2008. “Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning (Redcap).” International Journal of Geographical Information Science, 22(7): 801-823.

Applications

R Packages

Lesson competencies

Technical References

Application References