The analysis of an overlaid map with different attributes has a very important function in GIS. In an overlaid map, approximately half of the constructed polygons are tiny and only account for less than 5% of the total area. In subsequent analysis of an overlaid map, a tiny polygon may require the same amount of computing time and memory space as any large one. In addition, in most cases it is meaningless to treat such polygons as distinct analysis units. So eliminating the tiny polygons is useful to improve efficiency. Now we often use the methods of “boundary comparison” and “fuzzy discriminance” to merge tiny polygons. But in the boundary comparison method, a polygon may be merged into a neighbor of quite different attribute values. In the second method, when the fuzzy grades of two boundary lines are almost the same and their lengths are different, this can lead to large error. In this paper, the partition principle of fuzzy Voronoi (F V) is proposed based on the characteristic of fuzzy boundary and the contiguity of Voronoi diagram. The bigger tiny polygons are divided by Voronoi diagram, and then are merged to neighbor polygon according to contiguity. The F V principle and arithmetic are presented in detail. In the end, an experiment is given; the result has proved that error in the F V method, compared with the two other methods, is only about 30%.
