Creating polygon models for spatial clusters

Abstract

This paper proposes a novel methodology for creating efficient polygon models for spatial datasets. A comprehensive analysis framework is proposed that takes a spatial cluster as an input and generates a polygon model for the cluster as an output. The framework creates a visually appealing, simple, and smooth polygon for the cluster by minimizing a fitness function. We propose a novel polygon fitness function for this task. Moreover, a novel emptiness measure is introduced for quantifying the presence of empty spaces inside polygons. © 2014 Springer International Publishing.