Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Glyph-Based Uncertainty Visualization and Analysis of Time-Varying Vector Fields

Timbwaoga A. J. Ouermi, Jixian Li, Zachary Morrow, Bart van Bloemen Waanders, Chris R. Johnson

TL;DR

Uncertainty is inherent in vector field data but often omitted in visualizations, reducing interpretability for critical applications such as hurricanes and wildfires. The authors propose a 3D squid glyph to accurately encode magnitude and direction uncertainty, along with vector depth as a nonparametric centrality measure in spherical space, integrated in an interactive visualization framework. They demonstrate improved differentiation of magnitude and directional dispersion over existing glyphs in hurricane Isabel and wildfire wind analyses. The work offers a concrete methodology for more reliable uncertainty communication in 3D vector fields with potential impact on risk assessment and decision support.

Abstract

Uncertainty is inherent to most data, including vector field data, yet it is often omitted in visualizations and representations. Effective uncertainty visualization can enhance the understanding and interpretability of vector field data. For instance, in the context of severe weather events such as hurricanes and wildfires, effective uncertainty visualization can provide crucial insights about fire spread or hurricane behavior and aid in resource management and risk mitigation. Glyphs are commonly used for representing vector uncertainty but are often limited to 2D. In this work, we present a glyph-based technique for accurately representing 3D vector uncertainty and a comprehensive framework for visualization, exploration, and analysis using our new glyphs. We employ hurricane and wildfire examples to demonstrate the efficacy of our glyph design and visualization tool in conveying vector field uncertainty.

Glyph-Based Uncertainty Visualization and Analysis of Time-Varying Vector Fields

TL;DR

Uncertainty is inherent in vector field data but often omitted in visualizations, reducing interpretability for critical applications such as hurricanes and wildfires. The authors propose a 3D squid glyph to accurately encode magnitude and direction uncertainty, along with vector depth as a nonparametric centrality measure in spherical space, integrated in an interactive visualization framework. They demonstrate improved differentiation of magnitude and directional dispersion over existing glyphs in hurricane Isabel and wildfire wind analyses. The work offers a concrete methodology for more reliable uncertainty communication in 3D vector fields with potential impact on risk assessment and decision support.

Abstract

Uncertainty is inherent to most data, including vector field data, yet it is often omitted in visualizations and representations. Effective uncertainty visualization can enhance the understanding and interpretability of vector field data. For instance, in the context of severe weather events such as hurricanes and wildfires, effective uncertainty visualization can provide crucial insights about fire spread or hurricane behavior and aid in resource management and risk mitigation. Glyphs are commonly used for representing vector uncertainty but are often limited to 2D. In this work, we present a glyph-based technique for accurately representing 3D vector uncertainty and a comprehensive framework for visualization, exploration, and analysis using our new glyphs. We employ hurricane and wildfire examples to demonstrate the efficacy of our glyph design and visualization tool in conveying vector field uncertainty.
Paper Structure (10 sections, 3 equations, 4 figures)

This paper contains 10 sections, 3 equations, 4 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Methods
  4. Uncertainty Glyph Design
  5. Vector Depth
  6. Vector Field Uncertainty Visualization Tool
  7. Results and Discussion
  8. Hurricane Isabel
  9. Wildfire
  10. Conclusion

Figures (4)

  • Figure 1: Uncertainty squid glyph design: The visualization on the left side illustrates calculating the first ($\sigma_{0}$) and second ($\sigma_{1}$) PCA principal components used to represent the directional spread and scale of the superellipse semi-minor axis. The diagram on the right side shows the squid glyph design with its parameters. The magnitude and magnitude variation are represented along the glyph direction. The minimum magnitude, magnitude variation, and maximum magnitude are represented with $h$, $\Delta h$, $h + \Delta h$, respectively.
  • Figure 2: The arrows on the left side show the explicit visualization of the vector distribution. The squid glyph approximation for this distribution is shown in the center. The squid glyph representation without the outlier is shown on the left side.
  • Figure 3: Vector uncertainty analysis interface. The outlined black rectangles and orange numbers indicate the components. $C_{1}$ and $C_{2}$ are used for global and local visualization of filtered vector data, respectively. $C_{3}$ visualizes the magnitude variations and while $C_{4}$ visualizes the vector depth distribution magnitudes and angular variations at a selected location.
  • Figure 4: Hurricane Isabel and wildfire examples. Both examples show a comparison of the comet, tailed-disc and squid glyphs