A Novel Spatial Fuzzy Clustering using Delaunay Triangulation for Large Scale GIS Data (NSFCDT)

This paper proposed a novel fuzzy clustering method on spatial data based on Delaunay Triangulation. Given a set of points in a two dimensional space, the objective is to group the data into several sets. The model uses two passes. In the first pass, the underlying model used a Delaunay Triangulation method for initial spatial clustering. The clustering, in this pass, is done on the notion of proximity of points. The Fuzzy method is applied as a post processing refinement of the clusters in the second pass. The underlying mathematical backbone of the proposed model along with the correctness of the algorithm has also been conformed.