Abstract:
Spatial data is typically inferred between reference points using interpolation techniques and communicated to end users through visualisation. It is not well understood ...Show MoreMetadata
Abstract:
Spatial data is typically inferred between reference points using interpolation techniques and communicated to end users through visualisation. It is not well understood yet how different interpolation techniques perform visually and what visualisation attributes impact on the visual communication of spatial maps. In this paper, we present a study to address these issues. We performed a dedicated experiment in which observers judged visual similarity between interpolated maps and reference maps. We could clearly identify the superior interpolation techniques amongst a set of techniques under consideration. We further found a significant effect for the colour map used for visualisation. No interaction, however, was found between the colour maps and specific interpolation technique comparisons. Response times were recorded as a proxy for judging difficulty and were found to be significantly larger for comparisons amongst the best and worst interpolation techniques.
Published in: 2015 Big Data Visual Analytics (BDVA)
Date of Conference: 22-25 September 2015
Date Added to IEEE Xplore: 02 November 2015
ISBN Information: