Spatial Outlier Detection Approaches and Methods: A Survey

An outlier is any object which is inconsistent with the remaining objects in a database in data mining the outlier detection plays an interesting and important role because the removal of false outliers may affect the mined results to a greater extent if it is important information needed for analysis. The Spatial outliers are locations which are significantly different from their neighborhoods even though they are not much deviated from the entire population. It helps in finding out the local instabilities of objects when compared with other objects in spatial data. The spatial exploration becomes important because it is applied in many applications like weather prediction, clinical traits, geospaced information processing etc.The detection of spatial outliers is necessary for analysis in this area. This paper presents a survey and study of spatial outliers, its approaches, detection methods and algorithms with their complexity along with their pros and cons.