Algorithm for Spatial Outlier Detection Based on Outlying Degree

Abstract

A spatial outlier is a spatial object whose non-spatial attribute values are significantly different from the values of its neighborhood. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and useful spatial patterns for further analysis. Major drawbacks of existing methods are that the characteristics of spatial objects aren't considered, normal objects tend to be falsely detected as spatial outliers or true spatial outliers tend to be ignored when their neighborhood contains true spatial outliers, they have poor efficiency, and they depend on a priori given parameters. We proposed a new measure to identify spatial outliers and a novel algorithm of spatial outlier detection based on the outlying degree. The algorithm overcomes those disadvantages and can accurately detect spatial outliers. In addition, using a real-world census data set, we demonstrate that our approach is effective and efficient.