The procedures adopted for analysing patterns of spatial autocorrelation depend on the type of data available. There is considerable difference between: (a) a set of 100 values obtained for a 10x10 grid of (100mx100m) squares which covers a 1000mx1000m region; (b) a set of values obtained for 100 contiguous but arbitrarily shaped polygons which again cover the same region; and (c) a set of data values obtained from 100 arbitrarily distributed sample points in our study region. Each case warrants a slightly different approach, but each utilises the notion of proximity bands as a means of imposing some form of serial behaviour to the data. The idea is then to examine the correlation between areas or points at given levels of separation, to obtain a similar measure to that used within time series analysis.