HES 505 Fall 2024: Session 20
By the end of today you should be able to:
Use the spdep package to identify the neighbors of a given polygon based on proximity, distance, and minimum number
Understand the underlying mechanics of Moran’s I and calculate it for various neighbors
Distinguish between global and local measures of spatial autocorrelation
Visualize neighbors and clusters
Attributes (features) are often non-randomly distributed
Especially true with aggregated data
Interest is in the relationship between proximity and the feature
Difference from kriging and semivariance