A natural way to check whether there is a dependence between two quantities is to estimate their correlation. For spatial quantities, such an estimation is complicated by the fact that, in general, we measure the values of the two quantities of interest in somewhat different locations. In this case, one possibility is to correlate each value of the first quantity with the value of the second quantity measured at a nearby point. An alternative idea is to first apply an appropriate interpolation to each of the quantities, and then look for the correlation between the resulting spatial maps. Empirical results show that sometimes one of these techniques leads to a larger correlation, and sometimes the other one. In this paper, we provide simple pedagogical examples explaining why sometimes interpolation enhances spatial correlation and sometimes interpolation impedes correlation.