HSpatial autocorrelation

Spatial autocorrelation refers to the degree to which similar measurements or characteristics are clustered together in a geographical area. When positive spatial autocorrelation exists, nearby locations tend to have similar values, like neighboring neighborhoods with similar house prices. Conversely, negative spatial autocorrelation occurs when neighboring areas are dissimilar. Essentially, it measures how much the location of data points influences their values, helping identify patterns of spatial similarity or dissimilarity across a region. This concept is useful in fields like urban planning, ecology, and criminology to understand how phenomena are distributed in space.