After data preprocessing, boundary detection is the next step in the exploratory analysis of geographic boundaries. The detection and placement of artificial and natural boundaries are well described in the cartographic literature (reviewed in Coleman 1980, Burrough 1986). BoundarySeer allows you to use a variety of methods for finding boundaries of different types (areal or difference, open or closed, crisp or fuzzy) from spatial data sets comprising one or more variables. These are:
The first category is designed to locate difference boundaries; it requires some estimate of the amount of change in the variables over space. The second method, spatially constrained clustering, detects areal boundaries by locating areas of relative homogeneity and then drawing boundaries between adjacent areas. The third approach, fuzzy classification, is fairly new to the field of spatial analysis. Technically, fuzzy classification is not a boundary detection method. Yet, boundaries can be delineated from fuzzy classes through other methods, such as wombling.
How do I select the right detection method?