A spatial rough set for locating the periurban fringe

The distinction among urban, periurban and rural areas represents a classical example of uncertainty in land classification. Satellite images, geostatistical analysis and all kinds of spatial data are very useful in urban sprawl studies, but it is important to define precise rules in combining great amounts of data to build complex knowledge about territory. Rough Set theory may be a useful method to employ in this field. It represents a different mathematical approach to uncertainty by capturing the indiscernibility. Two different phenomena can be indiscernible in some contexts and classified in the same way when combining available information about them. Several experiences exist in the use of Rough Set theory in data mining, knowledge analysis and approximate pattern classification, but spatial component lacks in all these research streams. The aim of this paper is to use Rough Set methods in geographical analyses. This approach has been applied in a case of study, comparing the results achieved with both Map Algebra technique and Spatial Rough set. The study case area, Potenza Province, is particularly suitable for the application of this theory, because it includes 100 municipalities with different number of inhabitants and morphologic features.