====== Detection of Local Spatial Clustering ======

Getis and Ord (1992) introduced a statistic, //Gi*(d)//, that may be used to assess spatial dependence. Currently, we focus on a simple version of the standardized form of this statistic that was further elucidated by Ord and Getis (1995). In a typical exploratory geographic analysis, //Gi*(d)// is calculated for several different values of d in order to detect spatial clustering at different scales. It is clear that //Gi*(d)// is a local measure. As such, it is particularly helpful when applied to datasets for which global measures of spatial dependence, such as Moran’s I (Cliff and Ord, 1973), may fail to reveal the existence of important pockets of clustering.
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We have developed a parallel  algorithm – P-//Gi*(d)// using TeraGrid. This parallel algorithm can solve larger-size problems than //Gi*(d)// sequential algorithms can handle while some super-linear speedups were achieved because memory requirements are significantly decreased by exploiting spatial data parallelism. Grid computing is particularly suitable for support typical exploratory scenarios using the parallel algorithm.
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**Project Team**: Marc Armstrong, Kate Cowles, Shaowen Wang