Difference between revisions of "Lesson06"
Jump to navigation
Jump to search
| Line 28: | Line 28: | ||
|} | |} | ||
<br/> | <br/> | ||
| + | |||
| + | <font size="6">'''Geographical Segmentation with Spatially Constrained Cluster Analysis'''</font> | ||
=Content= | =Content= | ||
| − | * Basic concepts of | + | * Basic concepts of geographic segmentation |
| − | * | + | * Conventional cluster analysis techniques |
| − | * | + | * Approaches for clustering geographically referenced data |
| − | * | + | ** Hierarchical clustering with spatial constraints |
| + | ** Minimum spanning trees | ||
| + | ** Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning (Redcap) | ||
| Line 40: | Line 44: | ||
==Methods== | ==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== | ==Applications== | ||
| − | |||
| − | + | =R Packages= | |
| − | + | '''AMOEBA''': A Multidirectional Optimum Ecotope-Based Algorithm [https://cran.r-project.org/web/packages/AMOEBA/index.html] | |
| − | + | '''ClustGeo''': Hierarchical Clustering with Spatial Constraints [https://cran.r-project.org/web/packages/ClustGeo/index.html] and Introduction to Clustgeo [https://cran.r-project.org/web/packages/ClustGeo/vignettes/intro_ClustGeo.html] | |
| − | + | '''skater''': A function from spdep package that implements a SKATER procedure for spatial clustering analysis.[https://www.rdocumentation.org/packages/spdep/versions/0.8-1/topics/skater] | |
| + | '''spatialcluster''': An R package for spatially-constrained clustering using either distance or covariance matrices. [https://github.com/mpadge/spatialcluster] | ||
| − | |||
| − | |||
| + | =Lesson competencies= | ||
| − | = | + | =Technical References= |
| + | |||
| + | |||
| + | =Application References= | ||
Revision as of 16:16, 6 February 2019
IS415 GeoSpatial Analytics and Applications
|
|
|
|
|
|
Geographical Segmentation with Spatially Constrained Cluster Analysis
Contents
Content
- Basic concepts of geographic segmentation
- Conventional cluster analysis techniques
- Approaches for clustering geographically 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
AMOEBA: A Multidirectional Optimum Ecotope-Based Algorithm [1]
ClustGeo: Hierarchical Clustering with Spatial Constraints [2] and Introduction to Clustgeo [3]
skater: A function from spdep package that implements a SKATER procedure for spatial clustering analysis.[4]
spatialcluster: An R package for spatially-constrained clustering using either distance or covariance matrices. [5]
