Paper
24 January 2011 An evaluation of methods for encoding multiple 2D spatial data
Mark A. Livingston, Jonathan Decker, Zhuming Ai
Author Affiliations +
Proceedings Volume 7868, Visualization and Data Analysis 2011; 78680C (2011) https://doi.org/10.1117/12.872576
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
Datasets over a spatial domain are common in a number of fields, often with multiple layers (or variables) within data that must be understood together via spatial locality. Thus one area of long-standing interest is increasing the number of variables encoded by properties of the visualization. A number of properties have been demonstrated and/or proven successful with specific tasks or data, but there has been relatively little work comparing the utility of diverse techniques for multi-layer visualization. As part of our efforts to evaluate the applicability of such visualizations, we implemented five techniques which represent a broad range of existing research (Color Blending, Oriented Slivers, Data-Driven Spots, Brush Strokes, and Stick Figures). Then we conducted a user study wherein subjects were presented with composites of three, four, and five layers (variables) using one of these methods and asked to perform a task common to our intended end users (GIS analysts). We found that the Oriented Slivers and Data-Driven Spots performed the best, with Stick Figures yielding the lowest accuracy. Through analyzing our data, we hope to gain insight into which techniques merit further exploration and offer promise for visualization of data sets with ever-increasing size.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark A. Livingston, Jonathan Decker, and Zhuming Ai "An evaluation of methods for encoding multiple 2D spatial data", Proc. SPIE 7868, Visualization and Data Analysis 2011, 78680C (24 January 2011); https://doi.org/10.1117/12.872576
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Visualization

Composites

Computer programming

Visual analytics

Error analysis

Associative arrays

Multilayers

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