posted on 2023-05-23, 18:42authored byEnglke, U, Susanto, F, de Souza Junior, P, Marendy, P
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.
History
Publication title
Big Data Visual Analytics, BDVA 2015
Editors
U Engelke, T Bednarz, J Heinrich, K Klein, QV Nguyen
ISBN
978-146737343-2
Department/School
School of Information and Communication Technology
Publisher
Institute of Electrical and Electronics Engineers Inc.
Place of publication
United States
Event title
Big Data Visual Analytics, BDVA 2015
Event Venue
Hobart, Tasmania
Date of Event (Start Date)
2015-09-22
Date of Event (End Date)
2015-09-25
Repository Status
Restricted
Socio-economic Objectives
Information systems, technologies and services not elsewhere classified