Regression modelGIS / spatial
Local Indicators of Spatial Association (LISA)
LISA, introduced by Luc Anselin in 1995, decomposes a global spatial autocorrelation index into a location-specific statistic for every observation. It identifies where statistically significant spatial clusters and outliers occur on a map, enabling researchers to move beyond a single global summary and pinpoint the geographic sources of spatial dependence.
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Sources
- Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI: 10.1111/j.1538-4632.1995.tb00338.x ↗
- Anselin, L. (2010). Local Spatial Autocorrelation. In A. S. Fotheringham & P. A. Rogerson (Eds.), The SAGE Handbook of Spatial Analysis (pp. 255–275). SAGE Publications. link ↗
Related methods
Referenced by
Bayesian Local Indicators of Spatial AssociationBayesian Moran's IBayesian Spatial AutocorrelationGeary's CGlobal Getis-Ord Gi*Global Moran's IHot Spot AnalysisLocal Geary's CLocal Getis-Ord Gi*Local Hot Spot AnalysisLocal Moran's ILocal Spatial AutocorrelationMoran's IMultiscale Moran's IMultiscale Spatial AutocorrelationPanel Hot Spot AnalysisPanel Local Indicators of Spatial AssociationRemote Sensing ClassificationRobust Local Indicators of Spatial AssociationRobust Spatial AutocorrelationSpace-Time Local Indicators of Spatial AssociationSpace-Time Moran's ISpatial Autocorrelation