Multi-Variant Spatial Outlier Approach to Detect Less Developed Sites in Given Region

The term “outlier" can generally be defined as an observation that is significantly different from the other values in a data set. The outliers may be instances of error or indicate events. The task of outlier detection aims at identifying such outliers in order to improve the analysis of data and further discover interesting and useful knowledge about unusual events within numerous applications domains. A Spatial Outlier (SOutlier) is an object whose non-spatial attribute value is significantly different from the values of its spatial neighbors Spatial Outlier detection techniques may be used in many real life applications like geographical information system (GIS), climate prediction, fire detection and etc.In this paper we have discussed how the spatial outlier detection technique may be used to detect less developed sites in given region. We have used multiple non-spatial attributes of many spatially distributed sites. We have applied two very popular mean and median based spatial outlier detection technique on a real data set of twenty one sites in the state of Haryana. Results of these techniques may be used by development planners to make effective and efficient decisions. Strategic planners will have an idea regarding less developed spatially distributed sites, where they may put special attention for development.