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. Any general advice would be greatly appreciated, p.s. I´m using ArcGIS 10 and Erdas 2011
THANKS IN ADVANCE FOR ANY SUGGESTIONS, david