When doing analysis on spatial data with associated information that is numeric, it is possible to use techniques such as Kriging or Interpolation or Cluster Analysis to find out interesting relationships in your data. Then you can visualise using your choice of poison/GIS. Okay.
Now, I want to do the same type of things with spatial data that has associated non-numeric data, i.e. a "Factor" in R or a "Classification". However I cannot find techniques that allow one to do this.
Does anyone know of methods that can be used to perform this type of analysis? It would also be a bonus you know whether they can be performed in R or QGIS.
I would really love a model to do interpolation with a non-numeric attribute. The set I would use this interpolation on would be lithology or other geological data.
R
, which supports generalized linear models of spatial data. Note, too, that although rasters internally represent data as numbers, that is no different than howR
encodes factors and has the same intention: a so-called "integer" grid can be used to represent a spatial field of factor values (such as land use classes). All raster-based GISes have tools to support such an interpretation. – whuber Jan 21 '13 at 16:47