Global and local spatial autocorrelation in bounded regular tessellations

Barry Boots and Michael Tiefelsdorf
Additional contact information
Barry Boots: Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, Ontario, Canada, N2L 3C5 (bboots@wlu.ca)
Michael Tiefelsdorf: Department of Geography, The Ohio State University, Columbus, OH 43210, USA (tiefelsdorf.1@osu.edu)

Journal of Geographical Systems, 2000, vol. 2, issue 4, 319-348

Abstract: Abstract. This paper systematically investigates spatially autocorrelated patterns and the behaviour of their associated test statistic Moran's I in three bounded regular tessellations. These regular tessellations consist of triangles, squares, and hexagons, each of increasing size (n=64; 256; 1024). These tesselations can be downloaded at http://geo-www.sbs.ohio-state.edu/faculty/tiefelsdorf/regspastruc/ in several GIS formats. The selection of squares is particularly motivated by their use in raster based GIS and remote sensing. In contrast, because of topological correspondences, the hexagons serve as excellent proxy tessellations for empirical maps in vector based GIS. For all three tessellations, the distributional characteristics and the feasibility of the normal approximation are examined for global Moran's I, Moran's I (k) associated with higher order spatial lags, and local Moran's I i. A set of eigenvectors can be generated for each tessellation and their spatial patterns can be mapped. These eigenvectors can be used as proxy variables to overcome spatial autocorrelation in regression models. The particularities and similarities in the spatial patterns of these eigenvectors are discussed. The results indicate that [i] the normal approximation for Moran's I is not always feasible; [ii] the three tessellations induce different distributional characteristics of Moran's I, and [iii] different spatial patterns of eigenvectors are associated with the three tessellations.

Keywords: Key words: Regular planar tessellations; global and local spatial autocorrelation; spatial correlogram; increasing-domain asymptotics; spatial eigenfunctions; JEL classification: C0; C12; C49 (search for similar items in EconPapers)
Date: 2000
References: Add references at CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://link.springer.com/10.1007/PL00011461 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:jgeosy:v:2:y:2000:i:4:d:10.1007_pl00011461

Ordering information: This journal article can be ordered from
http://www.springer. ... ce/journal/10109/PS2

DOI: 10.1007/PL00011461

Access Statistics for this article

Journal of Geographical Systems is currently edited by Manfred M. Fischer and Antonio Páez

More articles in Journal of Geographical Systems from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().