用3D图示精准展现向量场不确定性，助力气象灾害研判
Glyph-Based Uncertainty Visualization and Analysis of Time-Varying Vector Fields
- 设计新型3D图示符号表达向量场不确定性
- 通过飓风与山火案例验证工具有效性
- 适合气候模拟、灾害预测等科研人员使用
不确定性是大多数数据（包括向量场数据）固有的特性，但常被可视化忽略。有效的不确定性可视化可提升向量场数据的理解与可解释性。例如，在飓风和山火等严重天气事件中，准确的不确定性可视化能提供火灾蔓延或飓风行为的关键洞察，辅助资源调配与风险防控。传统图示多限于二维，本研究提出一种基于图示的3D向量不确定性表示方法，并构建完整的可视化、探索与分析框架。通过飓风与山火案例，验证了新图示设计与工具在传达向量场不确定性方面的有效性。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。