![]() ![]() Initially we examine the case of nominal-valued data, which helps identify the key concepts involved and focuses our attention on a set of questions regarding such analysis that we then examine in more detail. 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. a set of data values obtained from 100 arbitrarily distributed sample points in our study regionĮach case warrants a slightly different approach, but each utilizes the notion of proximity bands as a means of imposing some form of serial behavior to the data.a set of nominal values (classes) for 100 contiguous but arbitrarily shaped polygons which again cover the same region and.a set of real valued measurements obtained for 100 contiguous but arbitrarily shaped polygons which again cover the same region and. ![]() a set of real valued measurements recorded for a 10x10 grid of 100 (100mx100m) squares that comprise a 1km x 1km square (1000mx1000m region) and.There is considerable difference between: ![]() ![]() The procedures adopted for analyzing patterns of spatial autocorrelation depend on the type of data available. ![]()
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