I am not going to lie... spatial interpolation, whatever tool you use, is complicated and messy. Not the least of the problems is that you are going back and forth between point data (the control points) and field data (the interpolated surface output).
This is particularly bad right now because of changes in the management of coordinate reference systems (projections) which have made moving data back and forward between vector and raster formats in R a bit flakey at the moment. You may as a result see more than the usual number of warnings when you are trying to comlplete this assignment! If you'd prefer not to see those warnings, you can issue this command in a session:
options("rgdal_show_exportToProj4_warnings"="none")
which will suppress them, but it's probably better to just go with it.
The materials for interpolation extend across two weeks of lab sessions, with a single assignment asking you to perform interpolation on some data provided and comment on the results and process in the usual way. You'll find all the materials you need bundled in this zip archive which you should unpack and set as your working folder in RStudio. I've provided .Rmd files this time, which you may find more useful even than usual.
The steps along the way are described in the instructions below. You'll get the most out of these working through them in order:
- The overall approach to interpolation in R using
gstat - The example dataset
- Preparing for interpolation by making an output layer, etc.
- Near neighbour and inverse-distance weighted interpolation
- Trend surfaces and kriging
- Splines
- Other R packages and platforms
And then of course...