Keywords
spatial autocorrelation
spatial dependence
How to Cite
Abstract
The power of today's computers allows us to perform computation on massive quantities of data on the one hand and produces enormous amounts of analysis output on the other, as noted by Griffith in his 2003 book. Besides, visualisation and spatial filtering (the core of considerations in Griffith's book) have a chance to be widely used in research practice, especially in geosciences and, more precisely, for georeferenced data. Following the idea proposed by Patuelli et al. (2006, 2009), we analysed the labour market in Poland, focusing on metropolitan areas and their surroundings. The analysis was performed on a data set for the unemployment rate in the 2,478 Polish communes. We took into account spatial autocorrelation and used spatial filtering techniques to construct components of an orthogonal map pattern. As shown in Tiefelsdorf & Griffith (2007), the spatial filtering techniques could be employed in both, parametric and semi-parametric approaches. In this paper we adopted a parametric one.
References
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