Spatial autocorrelation is considered an Exploratory Spatial Data Analysis (ESDA) method where the concern is to visualize different patterns and clusters through geovisualization and formal statistical tests. Here, the intent is to highlight and explore the similarity of any given value in a dataset to similarity in terms of locations. Therefore, the concept of spatial autocorrelation relates to the combination of similarity between attributions and location.
In contrast to traditional statistical correlations, it does not target the relation of two variables and the change of one value in relation to the other. But spatial autocorrelation focuses on the value of the interested variable in relation to its location and surrounding locations. In other words, spatial autocorrelation allows us to study and understand the spatial distribution and structure...