Lesson07

From Geospatial Analytics and Applications
Revision as of 20:41, 14 February 2019 by Tskam (talk | contribs)
Jump to navigation Jump to search

Claraview.png IS415 GeoSpatial Analytics and Applications

About

Weekly Session

Take-home Exercises

Geospatial Analytics Project

Course Resources

 


Modelling Spatial Varying Relationship: Geographically Weighted Regression methods

Content

  • Granddaddy of All Models: Multiple Regression
  • Basic concepts of Spatial Non-stationary
  • Geographically Weighted Regression (gwr) Methods
    • Basic principles and concepts
    • Distance matrix, kernel and bandwidth
    • Basic grw
    • Beyond basic grw
    • GW regression and addressing local collinearity


References

Methods

Brunsdon, C., Fotheringham, A.S., and Charlton, M. (2002) “Geographically weighted regression: A method for exploring spatial nonstationarity”. Geographical Analysis, 28: 281-289.

Brunsdon, C., Fotheringham, A.S. and Charlton, M., (1999) “Some Notes on Parametric Significance Tests for Geographically Weighted Regression”. Journal of Regional Science, 39(3), 497-524.

Harris, P. et al., (2010) “The Use of Geographically Weighted Regression for Spatial Prediction: An Evaluation of Models Using Simulated Data Sets”. Mathematical Geosciences, 42(6), 657-680.

Applications

R Packages

GWmodel: Geographically-Weighted Models [1]


Lesson competencies

Technical References

Application References