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Vis Inf
Vis Inf  2019, Vol. 3 Issue (3): 113-128    DOI: 10.1016/j.visinf.2019.08.001
论文     
海洋数据可视化分析综述
Cui Xie，Mingkui Li，Haoying wang，Junyu Dong
College of Information Science and Engineering, Ocean University of China, 238 Songling Road, Qingdao, China
A survey on visual analysis of ocean data
Cui Xie，Mingkui Li，Haoying wang，Junyu Dong
College of Information Science and Engineering, Ocean University of China, 238 Songling Road, Qingdao, China
 全文: PDF 
摘要： 海洋大数据分析的主要挑战是数据的复杂性和海洋动态过程的内在复杂性。交互式可视分析可作为一种有效补充方法用来发现数据中蕴含的各种现象或模式，并对研究人员日常工作涉及的多个变量进行关联探索和比较。 本文阐述了由众多测量设备或计算机模拟生成的海洋数据的基本概念，综述了海洋数据的特点和相关的数据处理技术，介绍了海洋数据分析的主要任务。基于海洋领域的主要分析任务，本文重点围绕以下四个方面: 多种海洋环境要素的可视化和多变量分析、海洋现象识别和跟踪、模式或相关性检测、集合和不确定性探索介绍了相关的交互式可视化技术和工具。最后，讨论了未来的研究方向。
关键词： 海洋数据;  可视化 ;  可视分析     
Abstract: A major challenge in analysis of huge amounts of ocean data is the complexity of the data and the inherent complexity of ocean dynamic process. Interactive visual analysis serves as an efficient complementary approach for the detection of various phenomenon or patterns, and correlation exploring or comparing multiple variables in researchers daily work. Firstly, this paper presents a basic concept of ocean data produced from numerous measurement devices or computer simulations. The characteristics of ocean data and the related data processing techniques are also described. Secondly, the main tasks of ocean data analysis are introduced. Based on the main analysis tasks in ocean domain, the survey emphasizes related interactive visualization techniques and tools from four aspects: visualization of multiple ocean environmental elements and multivariate analysis, ocean phenomena identification and tracking, patterns or correlation discovery, ensembles and uncertainties exploration. Finally, the opportunities are discussed for future studies.
Key words: Ocean data    Visualization    Visual analysis
出版日期: 2019-09-02
通讯作者: Junyu Dong     E-mail: spring@ouc.edu.cn
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Cui Xie
Mingkui Li
Haoying wang
Junyu Dong

引用本文:

Cui Xie, Mingkui Li, Haoying wang, Junyu Dong. A survey on visual analysis of ocean data. Vis Inf, 2019, 3(3): 113-128.

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http://www.zjujournals.com/vi/CN/10.1016/j.visinf.2019.08.001    或    http://www.zjujournals.com/vi/CN/Y2019/V3/I3/113

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