  Fairness considerations for spatial data often get confounded by the
underlying spatial autocorrelation. We propose hypothesis testing methodology
to detect the presence and strength of this effect, then mitigate it using a
spatial filtering-based approach -- in order to enable application of existing
bias detection metrics.
