Areal boundaries are polygons enclosing homogeneous areas. BoundarySeer defines areal boundaries through spatially constrained clustering. In this process, BoundarySeer delineates the target number of clusters set by the user. As the central problem in clustering is how many clusters to specify, you may wish to perform a goodness of fit analysis to optimize the target cluster number.
The clustering process creates two new data sets: a clusters data set and descriptive statistics. The clusters data set has the same spatial coordinates but all other data are replaced by cluster assignments. The descriptive statistics summarize information about each cluster (number of elements, averages for each variable within the cluster). Boundaries are created around the clusters.
The map shows the new clusters data set and the areal boundary, the edges of the clusters. Viewing a table of the boundary brings up a list of the polygons and which cluster they describe. Most of the important information about clustering is contained in the cluster data set and the descriptive statistics.
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