Spatial Pattern Analysis Problem In this assignment we are trying to see if spatial clustering is present by looking at confidence intervals and probability, using different statistical methods, and then checking the validity of the clustering. Analysis Procedures Using one scenario as an example that involves 'calls for service,' I determine if spatial clustering exists using the following statistical methods: Average Nearest Neighbor, Getis-Ord General G, Ripley's K Function and Moran's I. After clustering is determined, I examine further if it is clustering in a specific location. Below are descriptions of the statistical methods being used. The Average Nearest Neighbor - This method calculates real data against generated data and measures the difference, which results in a degree of physical clustering
 Getis-Ord General G - This method looks at if similar values are clustered near each other and those values that are similar will show heavy clustering. Ripley's K Function - Looks at nearest multiple features and distances to determine clustering. Moran's I - This determines the validity of the clustering with spatial autocorrelation. Workflow Diagram Results Call priority clustering using General G Proposed new station using General G Spatial cluster analysis using K function Cluster and outlier analysis using Moran's I

 

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