Original scientific paper

Revealing a spatial autocorrelation with local indicators

Dražen Barković

Abstract

Spatial autocorrelation may be defined as the relationship among values of a single variable that comes from
the geographic arrangement of the areas in which these values occur. It measures the similarity of objects
within an area, the degree to which a spatial phenomenon is correlated to itself in space, the level of interdependence
between the variables, the nature and strength of the interdependence, i.e. spatial autocorrelation
is an assessment of the correlation of a variable in reference to spatial location of the variable. Assess if the
values are interrelated, and if so is there a spatial pattern to the correlation, i.e. is there spatial autocorrelation.
Spatial autocorrelation tools test whether the observed value of a variable at one locality is independent of
values of the variable at neighboring localities. Spatial autocorrelation may be classified as either positive
or negative. Positive spatial autocorrelation has all similar values appearing together, while negative spatial
autocorrelation has dissimilar values appearing in close association. map. When no statistically significant
spatial autocorrelation exists, the pattern of spatial distribution is considered random.
Spatial autocorrelation can be measured on local and global level. This study presents both of these measures
and ilustrates them on a practical example.

Keywords

spatial autocorrelation; local Moran coefficient; global Moran coefficient; Getis-Ord statistics; „hot spots“ i „cold spots“

Hrčak ID:

42853

URI

https://hrcak.srce.hr/42853

Publication date:

10.7.2009.

Article data in other languages: croatian

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