Final answer:
The Local Indicator of Spatial Association (LISA) measures the degree of spatial autocorrelation in a spatial dataset to identify clustered or dispersed patterns.
Step-by-step explanation:
The Local Indicator of Spatial Association (LISA) specifically calculates b) Spatial autocorrelation. LISA identifies regions of a map where similar values cluster together, indicating either clustered or dispersed patterns across a space, often visualized on a choropleth map. By definition, spatial autocorrelation is a measure of the degree to which a set of spatial features and their associated data values tend to be clustered together in space (positive autocorrelation) or dispersed (negative autocorrelation). The widely known Moran's I statistic is an example of a measure used to determine the degree of clustering or spatial autocorrelation, which is what LISA also aims to quantify. This is integral to various geographic analyses such as hot spot analysis, which is a spatial analysis technique used to determine areas of high incidence of phenomena such as crime.