Lesson06

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Claraview.png IS415 GeoSpatial Analytics and Applications

About

Weekly Session

Take-home Exercises

Geospatial Analytics Project

Course Resources

 


Content

  • Basic concepts of Principal Component Analysis
  • Standard Nonspatial PCA on Spatial Data
  • Locally Weighted PCA
  • Geographically Weighted PCA


References

Methods

Urška Demšar, Paul Harris, Chris Brunsdon, A. Stewart Fotheringham & Sean McLoone (2012): “Principal Component Analysis on Spatial Data: An Overview”. Annals of the Association of American Geographers, 103:1, 106-128.

Harris, P., Brunsdon, C., and Charlton, M. (2011) “Geographically weighted principal component analysis”. International Journal of Geographical Information Science, 25(10): 1717-1736.

Applications

Harris, P., et. al. (2015) “Enhancements to a geographically weighted principal components analysis in the context of an application to an environmental data set”. Geographical Analysis, 47: 146-172.

Comber, A., Harris, P., and Tsutsumida, N. (2016) “Improving land cover classification using texture variables outputted from a geographically weighted principal components analysis”. ISPRS Journal of Photogrammetry and Remote Sensing, 119: 347-360.

Tsutsumida, N., Harris, P., Comber, A. (2017) “The application of a geographically weighted principal components analysis for exploring 23 years of goat population change across Mongolia”. Annals of the Association of American Geographers, 107(5): 1060-1074.

The R Packages

Gollini I, Lu B, Charlton M, Brunsdon C, Harris P (2015) GWmodel: an R Package for exploring Spatial Heterogeneity using Geographically Weighted Models. Journal of Statistical Software 63(17): 1-50.


Lesson competencies