Spatial Autocorrelation

Spatial autocorrelation is a spatial measure that evaluates how dispersed or clustered points are distributed in space and whether or not this distribution has occurred by chance. Unlike other spatial methods for detecting spatial patterns of point distribution without considering their attributes, such as Quadrat analysis and the Nearest Neighbor method, spatial autocorrelation also characterizes how similar these points are with respect to their attribute values. There are two typical spatial autocorrelation statistics: Moran's I and Geary's C. Both Moran's I and Geary's C measure the proximity of locations and evaluate the similarity of attributes.

If the statistics show more positive correlation than would be expected from a randomly distributed pattern, points with similar attribute values are closely distributed in space (Figure 1A), whereas negative spatial ...