I have 3 maps representing spatial distribution in hunting pressure. These maps were derived using different methods and I am now interested in comparing them to assess how they might differ/agree with each other and whether there are some similar spatial patterns (i.e. areas with higher vs lower hunting pressure). I have converted all 3 maps to a common comparable index but am not sure what the best approach would be to compare them.
There seems to be a lot of different suggestions but none that quite fit what I'm trying to look at:
Initially I was thinking of computing a confusion matrix and looking at the kappa level of agreement but this only makes sense for categorical variables.
For continuous ones a lot of people suggest doing a correlation but I read that this would make sense for a time-series but not for comparing just 2-3 individual raster maps to each other.