Authors: Klippel, Alexander; Hardisty, Frank; Li, Rui

Source: Annals of the Association of American Geographers, Volume 101, Number 5, 1 September 2011 , pp. 1011-1031(21)

Publisher: Routledge, part of the Taylor & Francis Group

Abstract:

The characterization, identification, and understanding of spatial patterns are central concerns of geography. Deeply rooted in the notion that geographic location matters, one testable assumption is that near things are more related than distant things-a concept often referred to as Tobler's first law of geography. One means of quantifying this assumption is using measures of spatial autocorrelation. Several such measures have been developed to test whether a pattern is indeed clustered, or dispersed, or whether it is, from a statistical perspective, random. To shed light on how spatial patterns are understood from a cognitive perspective, this article reports results from studies of spatial pattern interpretation represented in maps. For the purpose of experimental validation, we used a two-color map. We systematically varied the ratio of the colors as well as the level of significance of clustering and dispersion; we targeted two groups: experts and nonexperts. The task for both experts and nonexperts was to sort patterns according to five specified categories of spatial autocorrelation structures. The results show clearly that patterns are understood on the basis of the dominant color, by both experts and nonexperts. A third experiment, using a free classification paradigm, confirmed the dominance of the color effect. These results are important, as they point to critical aspects of pattern perception and understanding that need to be addressed from the perspective of spatial thinking, especially how people relate concepts of randomness with spatial patterns (represented in maps).

Keywords: interpretation of spatial patterns; spatial autocorrelation; Tobler's first law; interpretación de patrones espaciales; autocorrelación espacial; primera ley de Tobler

Document Type: Research article

DOI: http://dx.doi.org/10.1080/00045608.2011.577364

Affiliations: 1: Department of Geography, GeoVISTA Center,The Pennsylvania State University,

Publication date: 2011-09-01

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