This chapter will look at spatial attribute analysis and geostatistical methods, and will introduce you to the various interpolation methods for spatial data that are available in R. We'll learn how to test for spatial autocorrelation, model spatial autocorrelation, how to spatially interpolate, how to fit a Generalized Linear Model (GLM) and look at some of the most widely used geostatistical methods such as variogram and kriging.. We'll also look at how point data can be converted into raster data using interpolation methods.
We'll be covering the following topics:
- Testing spatial autocorrelation
- Modeling spatial autocorrelation
- Generalized linear models
- Geostatistics
