When people talk about evictions, the conversation usually focuses on numbers. We hear about eviction rates, percentages, and housing statistics. But those numbers rarely show where these problems are happening. That is where Geographic Information Systems (GIS) become useful. GIS helps us move beyond simple statistics and see the geography behind social issues. By mapping eviction rates, we can start
Tag: spatial autocorrelation
Introduction In a recent lab exercise, I worked with GeoDa, developed by the University of Chicago Center for Spatial Data Science, to examine spatial structure in geographic data. The objective was not simply to map values, but to determine whether patterns were statistically clustered, dispersed, or random. A map shows distribution. Spatial analysis tests whether that distribution has structure. What