Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I

Sang-Il Lee
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Sang-Il Lee: Department of Geography, The Ohio State University, 1036 Derby Hall, 154 North Oval Mall, Columbus, OH 43210-1361, USA (e-mail: slee@geography.ohio-state.edu)

Journal of Geographical Systems, 2001, vol. 3, issue 4, 369-385

Abstract: Abstract. This research is concerned with developing a bivariate spatial association measure or spatial correlation coefficient, which is intended to capture spatial association among observations in terms of their point-to-point relationships across two spatial patterns. The need for parameterization of the bivariate spatial dependence is precipitated by the realization that aspatial bivariate association measures, such as Pearson's correlation coefficient, do not recognize spatial distributional aspects of data sets. This study devises an L statistic by integrating Pearson's r as an aspatial bivariate association measure and Moran's I as a univariate spatial association measure. The concept of a spatial smoothing scalar (SSS) plays a pivotal role in this task.

Keywords: Key words: Spatial association; spatial correlation; Moran's I; spatial smoothing; SDA; JEL classification: C13; C15; C49 (search for similar items in EconPapers)
Date: 2001
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:kap:jgeosy:v:3:y:2001:i:4:d:10.1007_s101090100064

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DOI: 10.1007/s101090100064

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