The Library
Map LineUps : effects of spatial structure on graphical inference
Tools
Beecham, Roger, Dykes, Jason, Meulemans, Wouter, Slingsby, Aidan, Turkay, Cagatay and Wood, Jo (2017) Map LineUps : effects of spatial structure on graphical inference. IEEE Transactions on Visualization and Computer Graphics, 23 (1). pp. 391-400. doi:10.1109/TVCG.2016.2598862 ISSN 1077-2626.
Research output not available from this repository.
Request-a-Copy directly from author or use local Library Get it For Me service.
Official URL: http://dx.doi.org/10.1109/TVCG.2016.2598862
Abstract
Fundamental to the effective use of visualization as an analytic and descriptive tool is the assurance that presenting data visually provides the capability of making inferences from what we see. This paper explores two related approaches to quantifying the confidence we may have in making visual inferences from mapped geospatial data. We adapt Wickham et al.'s `Visual Line-up' method as a direct analogy with Null Hypothesis Significance Testing (NHST) and propose a new approach for generating more credible spatial null hypotheses. Rather than using as a spatial null hypothesis the unrealistic assumption of complete spatial randomness, we propose spatially autocorrelated simulations as alternative nulls. We conduct a set of crowdsourced experiments (n=361) to determine the just noticeable difference (JND) between pairs of choropleth maps of geographic units controlling for spatial autocorrelation (Moran's I statistic) and geometric configuration (variance in spatial unit area). Results indicate that people's abilities to perceive differences in spatial autocorrelation vary with baseline autocorrelation structure and the geometric configuration of geographic units. These results allow us, for the first time, to construct a visual equivalent of statistical power for geospatial data. Our JND results add to those provided in recent years by Klippel et al. (2011), Harrison et al. (2014) and Kay & Heer (2015) for correlation visualization. Importantly, they provide an empirical basis for an improved construction of visual line-ups for maps and the development of theory to inform geospatial tests of graphical inference.
Item Type: | Journal Article | ||||||
---|---|---|---|---|---|---|---|
Divisions: | Faculty of Social Sciences > Centre for Interdisciplinary Methodologies | ||||||
Journal or Publication Title: | IEEE Transactions on Visualization and Computer Graphics | ||||||
Publisher: | Institute of Electrical and Electronics Engineers | ||||||
ISSN: | 1077-2626 | ||||||
Official Date: | January 2017 | ||||||
Dates: |
|
||||||
Volume: | 23 | ||||||
Number: | 1 | ||||||
Page Range: | pp. 391-400 | ||||||
DOI: | 10.1109/TVCG.2016.2598862 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |