I am somewhat of a newbie to geostatistical analyses, but pretty familiar with GIS and remote sensing packages. I was wondering if anyone had suggestions on appropriate geostatistical analyses for a particular data set. The data set consists of a large-scale survey at the land plot level consisting of questions related to political participation (an ordinal scale), and raster data from a binary landcover classification of forest cover. The survey data I am envisioning joining to a .shp file of landplot boundaries. I had wondered about either converting the vector to raster and analyzing raster against raster, or converting the landsat landcover map into a vector and analyzing vector x vector.
The research question is whether political participation (potentially plus other variables) affects the presence of forest cover. What I´m imagining is some sort of multivariate linear regression in terms of the survey data, but when it comes to adding in the values from the raster I´m somewhat stymied. In doing some background research on potential approaches, it seems like looking at discrete variation might be the way to go.
I´m using ArcGIS 10 and Erdas 2011.