Regression modelGIS / spatial
Local Spatial Autocorrelation
Local Spatial Autocorrelation methods decompose global spatial clustering into location-specific statistics, revealing where in a study area significant clustering or dispersion occurs. Each observation receives its own association score and significance value, enabling the detection of spatial hot spots, cold spots, and spatial outliers rather than reporting a single summary statistic.
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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 ↗
- Indicators of spatial association. Wikipedia. link ↗
Related methods
Referenced by
Bayesian Hot Spot AnalysisBayesian Spatial AutocorrelationGlobal Hot Spot AnalysisGlobal Spatial AutocorrelationLocal Geographically Weighted RegressionLocal Hot Spot AnalysisLocal Kernel Density EstimationLocal Network-Based Spatial AnalysisMultiscale Spatial AutocorrelationPanel Spatial AutocorrelationRobust Spatial AutocorrelationSpace-Time Hot Spot Analysis