Interactive web mapping application visualizing poverty rate distribution across Kentucky census tracts with spatial clustering analysis using Anselin Local Moran's I to identify statistically significant hot and cold spots.
Classifying poverty rates in a way that reveals meaningful spatial patterns rather than masking them with arbitrary breakpoints.
Applied Jenks natural-breaks classification across five poverty-rate categories, then ran Anselin Local Moran's I to detect spatial clusters (HH, LL, HL, LH) with toggle-able layer display.
Produced a dual-layer web application allowing users to explore both the raw poverty-rate surface and statistically significant spatial clusters simultaneously.