NordGISci 2006
The First Nordic Summer School in Geographic Information Science

The standard procedure in the vast majority of empirical analyses of spatial data is either to calculate a global statistic or to calibrate a global model.  The term ‘global’ implies that all the spatial data are used to compute a single statistic which is essentially an average of the conditions that exist throughout the study area in which the data have been measured. Such a procedure is flawed when the relationships being measured vary over space. Geographically Weighted Regression (GWR) is a statistical technique that allows variations in relationships over space to be measured within a single modelling framework.  The output from GWR is a set of surfaces, each surface depicting the spatial variation of a relationship. The technique is based on regular regression modelling but can be extended in many different ways.  It provides a great richness in the results obtained for any spatial data set and should be useful across all disciplines in which spatial data are used.

The workshop will be based around a textbook: Fotheringham A S, Brunsdon C and M Charlton Geographically Weighted Regression: the analysis of spatially varying relationships (Wiley 2002). The authors have also written windows-based, user-friendly software for GWR which participants will use in the labs.  The lab sessions will be based on self-paced exercises and participants will be given a lab manual with detailed instructions. It is hoped that participants have some knowledge of statistical analysis, particularly regression.  It would be helpful if they also had some experience with ArcGIS. 


Workshop I
Workshop II
Workshop III
Workshop IV
Workshop I on Geographically Weighted Regression (GWR)
12-16 June 2006, Gävle, Sweden