Geographic Data Science

Local Spatial Autocorrelation Dani Arribas-Bel

Local Spatial Autocorr.

“Clusters”

Pockets of spatial instability

Portions of a map where values are correlated in a particularly strong and specific way

[High-High] + SA of high values (hotspots)

[Low-Low] + SA of low values (coldspots)

[High-Low] - SA (spatial outliers)

[Low-High] - SA (spatial outliers)

LISAs

Local Indicators of Spatial Association

Statistical tests for spatial cluster detection → Statistical significance

Compares the observed map with many randomly generated ones to see how likely it is to obtain the observed associations for each location

$I_i = \frac{Z_i}{m_2} \sum_j W_{ij} Z_j \; \; ; \; \; m_2= \frac{\sum_i Z_i^2 }{N}$

A course on Geographic Data Science by Dani Arribas-Bel is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.