I'm assessing areas for suitability for species relocations, so essentially I'm looking to quantify how similar a possible relocation site is to a source site in several metrics. The species may travel 10km for example, so I have a point location for a source site, surrounded by a 10km radius. Within the radius I have values for every pixel (arbitrary size), for say altitude, or other numeric variables on a continuous scale that represent the habitat. At the relocation site, I also have a central point and 10km radius, but this may or may not overlap slightly with the source site radius. The pixelated areas within the two radii are not necessarily the same size however, as they can contain coastal areas, so different coastlines means different land area within the radii, and no data for sea area. EDIT: Spatial variability is not so important as habitat variables change more gradually over space, and not like a chess board/mosaic.
I'm looking for a way to quantify the overall similarity between the two areas. Essentially, taking the values of every pixel in each radius, I have two vectors of values of different respective lengths. I've found the Jaccard Similarity Index. EDIT: something like the Jaccard Index would be good but this is inappropriate here.
Would this be the best thing to do or is there a method more commonly used for this sort of spatial comparison? Preferably this would be done in R, otherwise QGIS.