TOWARDS A SYSTEMS APPROACH TO THE VISUALIZATION OF SPATIAL UNCERTAINTY Phaedon C. Kyriakidis

Abstract

Introduction Uncertainty is endemic in spatial data due to the imperfect means of recording, processing, and representing spatial information (Zhang and Goodchild, 2002). The characterization (modeling and portrayal) of spatial uncertainty, as well as its propagation to geographical modeling and its impact on decision-making, has been identified as a critical research priority in Geographic Information Science (GIScience), e.g., UCGIS (1996). Early cartographic work on the portrayal of spatial uncertainty focused on the adaptation of Bertin's visual variables (location, size, value, shape, texture, color and orientation) for representing uncertainty measures, such as standard errors of predictions in an interpolation setting, or of posterior probabilities of class occurrence in a classification setting. Bertin's variables, along with additional ones such as color saturation, were thus used in the context of static verity visualization, i.e., the simultaneous depiction of the origina