Spatial Structures and Scale in Categorical Maps

Spatial variability is typically represented by categorical maps or by samples taken at specific locations (point data). The regions or patches represented in categorical maps are intuitive and consistent with much geographical (and ecological, pedological, etc.) theory, but point data are more amenable to geostatistics and other approaches which allow examination of scales of variability and of spatial structure. The state probability function (SPF) is introduced as a tool for evaluating the spatial structure of landscapes represented as categorical maps. The SPF is based on the degree of similarity between mapped units or classificatory categories a given distance apart. A plot of the SPF vs. distance produces a graph which can be interpreted similarly to a variogram. The method is tested/illustrated using detailed soil map data from eastern North Carolina. The SPF is shown to be appropriately sensitive to major landscape boundaries across which the suite of soil types changes, and to the degree of clustering of similar units.