Understanding Spatial Autocorrelation: An Everyday Metaphor and Additional New Interpretations

Daniel A. Griffith ()
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Daniel A. Griffith: School of Economic, Political and Policy Sciences, University of Texas at Dallas, 800 W. Campbell Road, Richardson, TX 75080, USA

Geographies, 2023, vol. 3, issue 3, 1-20

Abstract: An enumeration of spatial autocorrelation’s (SA’s) polyvalent forms occurred nearly three decades ago. Attempts to conceive and disseminate a clearer explanation of it employ metaphors seeking to better relate SA to a student’s or spatial scientist’s personal knowledge databank. However, not one of these uses the jigsaw puzzle metaphor appearing in this paper, which exploits an analogy between concrete visual content organization and abstract map patterns of attributes. It not only makes SA easier to understand, which furnishes a useful pedagogic tool for teaching novices and others about it, but also discloses that many georeferenced data should contain a positive–negative SA mixture. Empirical examples corroborate this mixture’s existence, as well as the tendency for marked positive SA to characterize remotely sensed and moderate (net) positive SA to characterize socio-economic/demographic, georeferenced data.

Keywords: Moran scatterplot; negative spatial autocorrelation; positive spatial autocorrelation; spatial autocorrelation mixture; spatial autoregression (search for similar items in EconPapers)
JEL-codes: Q1 Q15 Q5 Q53 Q54 Q56 Q57 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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