The Hot Spot Analysis tool examines features and their attributes to identify statistically significant hot spots and cold spots using the Getis-Ord Gi* statistics. It provides a visual clustering of high, low, and not significant values. Each feature is assigned as a hot spot, cold spot, or not significant. To perform the analysis, a neighborhood is defined for each feature. How a neighborhood is defined is critical to the output of the tool as it is the neighborhood that is examined in relation to the study area for assignment of each feature.
At a high level, let's examine what occurs during the hot spot analysis process. Each feature in the dataset has an attribute value that is being measured in the analysis. A neighborhood is assigned to each feature. This neighborhood is critical to the analysis. You must decide how the neighborhood is to be defined as part of the input parameters of the tool. If you don't have...