Spatial Autocorrelation

Spatial Autocorrelation measures the degree to which similar values occur at nearby locations in space. It quantifies the relationship between the value of a variable at one location and the values of the same variable at neighboring locations, following Tobler's First Law of Geography.

This statistical concept is fundamental to spatial analysis, helping identify whether spatial patterns are random, clustered, or dispersed. Positive spatial autocorrelation indicates that similar values cluster together, while negative autocorrelation suggests that dissimilar values are adjacent, and zero autocorrelation implies random spatial distribution.

Practical Applications

• Real estate market analysis examining property value clustering
• Epidemiological studies investigating disease transmission patterns
• Environmental monitoring assessing pollution concentration patterns
• Economic geography analyzing regional development similarities
• Social research studying neighborhood characteristic patterns

Related Terms

• Moran's I
• Spatial Statistics
• Neighborhood Analysis
• Spatial Dependence
• Tobler's Law