title: Visual and statistical assessment of spatial clustering in mapped data.
abstract: Maps have seen increasing use to examine regional variation in health, but there has been little research on the visual perception of spatial patterns in mapped data. Theories of graphical perception suggest that the interpretation of maps is complex relative to other types of graphical material. This paper describes an experiment in which observers assessed a series of maps with respect to their amount of clustering. Maps with various types of spatial pattern were visually distinguishable; comparisons between variants of the same map, however, using different shading and plotting symbols indicated that the method of data representation also had a strong effect on visual perception. There was some evidence for a learning effect in complex maps. The relationship between the visual assessments and a statistical measure of spatial autocorrelation was significant but imperfect.
authors.affiliation: Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada.
authors.forename: S D
authors.initials: SD
authors.lastname: Walter
mesh_terms: D016000:Cluster Analysis; D015350:Contrast Sensitivity; D003430:Cross-Sectional Studies; D003627:Data Interpretation, Statistical; D005260:Female; D005843:Geography; D006801:Humans; D015994:Incidence; D007558:Italy / Q000453:epidemiology; D008297:Male; D008377:Maps as Topic; D009369:Neoplasms / Q000401:mortality*; D009864:Ontario / Q000453:epidemiology; D012606:Scotland / Q000453:epidemiology; D014796:Visual Perception