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.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.