Revealing a spatial autocorrelation with local indicators
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 i...
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| Format: | Article |
| Language: | English |
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Faculty of Economics and Business in Osijek
2009-07-01
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| Series: | Ekonomski Vjesnik |
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| Online Access: | http://hrcak.srce.hr/file/66958 |
| _version_ | 1827363558192578560 |
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| author | Dražen Barković |
| author_facet | Dražen Barković |
| author_sort | Dražen Barković |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T07:51:51Z |
| format | Article |
| id | doaj.art-77e9baebfc0e476f999516f619a057ef |
| institution | Directory Open Access Journal |
| issn | 0353-359X 1847-2206 |
| language | English |
| last_indexed | 2024-03-08T07:51:51Z |
| publishDate | 2009-07-01 |
| publisher | Faculty of Economics and Business in Osijek |
| record_format | Article |
| series | Ekonomski Vjesnik |
| spelling | doaj.art-77e9baebfc0e476f999516f619a057ef2024-02-02T14:40:31ZengFaculty of Economics and Business in OsijekEkonomski Vjesnik0353-359X1847-22062009-07-01XXII12332Revealing a spatial autocorrelation with local indicatorsDražen BarkovićSpatial 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.http://hrcak.srce.hr/file/66958spatial autocorrelationlocal Moran coefficientglobal Moran coefficientGetis-Ord statistics„hot spots“ i „cold spots“ |
| spellingShingle | Dražen Barković Revealing a spatial autocorrelation with local indicators Ekonomski Vjesnik spatial autocorrelation local Moran coefficient global Moran coefficient Getis-Ord statistics „hot spots“ i „cold spots“ |
| title | Revealing a spatial autocorrelation with local indicators |
| title_full | Revealing a spatial autocorrelation with local indicators |
| title_fullStr | Revealing a spatial autocorrelation with local indicators |
| title_full_unstemmed | Revealing a spatial autocorrelation with local indicators |
| title_short | Revealing a spatial autocorrelation with local indicators |
| title_sort | revealing a spatial autocorrelation with local indicators |
| topic | spatial autocorrelation local Moran coefficient global Moran coefficient Getis-Ord statistics „hot spots“ i „cold spots“ |
| url | http://hrcak.srce.hr/file/66958 |
| work_keys_str_mv | AT drazenbarkovic revealingaspatialautocorrelationwithlocalindicators |