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

arXiv: https://arxiv.org/abs/2409.00042 · HTML: https://mlsanity.com/paper/2409.00042/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 28 references that are in the map.
- First posted on arXiv 18 Aug 2024.

## Built on by (most cited first, 3 of 3)

- [A General Approach to Visualizing Uncertainty in Statistical Graphics](https://mlsanity.com/paper/2508.00937/) (2025)
- [Uncertainty Tube Visualization of Particle Trajectories](https://mlsanity.com/paper/2508.13505/) (2025)
- [Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty](https://mlsanity.com/paper/2510.01190/) (2025)

## Abstract (arXiv)

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.