Sammenlign metoder

	Global rumlig autokorrelation	Lokal rumlig autokorrelation
Fagområde	Rumlig analyse	Rumlig analyse
Familie	Regression model	Regression model
Oprindelsesår	1950	1995
Ophavsperson	P. A. P. Moran (Moran's I, 1950); generalized by Luc Anselin	Luc Anselin
Type	Spatial statistic / hypothesis test	Spatial association analysis
Oprindelig kilde	Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.	Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115.
Aliasser	global spatial dependence, global Moran's I, GSA, global spatial clustering measure	local spatial association, local SA, LISA methods, local spatial clustering
Relaterede	6	6
Resumé	Global Spatial Autocorrelation measures the degree to which similar values cluster together across an entire study area. Rather than identifying where clusters occur, it yields a single summary statistic — most commonly Moran's I — that quantifies whether spatial proximity coincides with value similarity, dissimilarity, or randomness across all observations simultaneously.	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.