Spatial Autocorrelation
Spatial Autocorrelation refers to the degree to which data values that are close to each other in space are also similar in value. In other words, it measures the correlation between observations at different locations in space. Spatial Autocorrelation is an important concept in spatial statistics and is used to identify patterns and relationships in spatial data. It is commonly used in fields such as geography, ecology, and epidemiology to analyze the spatial distribution of phenomena. Spatial Autocorrelation can be measured using various statistical methods, such as Moran's I and Geary's C. A high degree of Spatial Autocorrelation indicates that there is a spatial pattern in the data, while a low degree of Spatial Autocorrelation indicates that the data is randomly distributed in space.
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