The Spatial autocorrelation (Moran’s I method), works not only on feature locations or attribute values
alone but on both feature locations and feature values simultaneously. Given a set of features and an
associated attribute, it evaluates whether the pattern expressed is clustered, dispersed, or random. Moran’s
I is one of the oldest indicators of global spatial autocorrelation and is still used for determining spatial
autocorrelation [15,20,21,22]. It compares the value of the variable at any one location with the value at
all other locations and can be represented as: