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Multischaal ruimtelijke autocorrelatie×Ruimtelijke Autocorrelatie×
VakgebiedRuimtelijke analyseRuimtelijke analyse
FamilieRegression modelRegression model
Jaar van ontstaan20021950
GrondleggerBorcard & Legendre; Csillag & KabosP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
TypeSpatial autocorrelation decompositionSpatial statistic / exploratory spatial data analysis
Oorspronkelijke bronBorcard, D., & Legendre, P. (2002). All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecological Modelling, 153(1-2), 51-68. DOI ↗Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
Aliassenmulti-scale spatial autocorrelation, scale-decomposed spatial autocorrelation, multiscale Moran analysis, MSAspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Verwant65
SamenvattingMultiscale spatial autocorrelation extends classical spatial autocorrelation analysis by computing and comparing autocorrelation statistics (such as Moran's I) across a range of spatial scales simultaneously. This reveals at which geographic distances or resolutions spatial clustering or dispersion is strongest, providing a richer picture than a single global measure.Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.
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ScholarGateMethoden vergelijken: Multiscale Spatial Autocorrelation · Spatial Autocorrelation. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare