Salīdzināt metodes

	Globālā telpiskā autokorelācija	Lokālā telpiskā autokorelācija
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1950	1995
Autors	P. A. P. Moran (Moran's I, 1950); generalized by Luc Anselin	Luc Anselin
Tips	Spatial statistic / hypothesis test	Spatial association analysis
Pirmavots	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.
Citi nosaukumi	global spatial dependence, global Moran's I, GSA, global spatial clustering measure	local spatial association, local SA, LISA methods, local spatial clustering
Saistītās	6	6
Kopsavilkums	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.