Interpreting univariate Local Moran statistics
The four quadrants in the Moran scatter plot provide a classification of four types of spatial autocorrelation. Areas that are significant are labelled with these categories in the "High-High/Low-Low" dataset produced in the Moran analysis, and are colored in the Moran scatter plot and Local Moran maps as well (non-significant locations appear gray). The interpretation will be different for the univariate and bivariate Local Moran.
|
category |
scatter plot quadrant |
autocorrelation |
interpretation |
|
high-high |
upper right (red) |
positive |
Cluster - "I'm high and my neighbors are high." |
|
high-low |
lower right (pink) |
negative |
Outlier - "I'm a high outlier among low neighbors." |
|
low-low |
lower left (med. blue) |
positive |
Cluster - "I'm low and my neighbors are low." |
|
low-high |
upper left (light blue) |
negative |
Outlier - "I'm a low outlier among high neighbors." |
The map contains information on only those locations that have a significant Local Moran statistic. While every region in the dataset will be represented in the Moran Scatterplot, only those with Local Moran statistic p-values below 0.05 are be colored red or blue on the example map below. Regions with non-significant Local Moran statistics are colored gray. Any island locations are considered missing values because they have no adjacent neighbors.
