Development of a component-based interactive visualization system for the analysis of ocean data

IF 4.2 3区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Big Earth Data Pub Date : 2021-11-18 DOI:10.1080/20964471.2021.1994362
Yanjun Wang, Fuchao Li, Bin Zhang, Xiaofeng Li
{"title":"Development of a component-based interactive visualization system for the analysis of ocean data","authors":"Yanjun Wang, Fuchao Li, Bin Zhang, Xiaofeng Li","doi":"10.1080/20964471.2021.1994362","DOIUrl":null,"url":null,"abstract":"ABSTRACT With the continuous development of various types of fixed marine observation equipment, satellite remote sensing technology and computer simulation technology, modern marine scientific research has entered the era of big data. Interactive ocean visualization has become ubiquitous owing to the use of ocean data in studies of marine disasters, global climate change and fisheries. However, the primary challenge in analyzing large amounts of ocean data originates from the complexity of the data themselves. Therefore, an interactive multi-scale, multivariate visualization system with dynamic expansion potential is needed for analyzing larger volumes of ocean data. In this study, a unified visual data service was constructed, and a component-based interactive visualization structure for multi-dimensional, spatiotemporal ocean data is presented in this paper. Based on this structure, users can easily customize the system to visualize other types of scientific data.","PeriodicalId":8765,"journal":{"name":"Big Earth Data","volume":"10 1","pages":"219 - 235"},"PeriodicalIF":4.2000,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Earth Data","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/20964471.2021.1994362","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 5

Abstract

ABSTRACT With the continuous development of various types of fixed marine observation equipment, satellite remote sensing technology and computer simulation technology, modern marine scientific research has entered the era of big data. Interactive ocean visualization has become ubiquitous owing to the use of ocean data in studies of marine disasters, global climate change and fisheries. However, the primary challenge in analyzing large amounts of ocean data originates from the complexity of the data themselves. Therefore, an interactive multi-scale, multivariate visualization system with dynamic expansion potential is needed for analyzing larger volumes of ocean data. In this study, a unified visual data service was constructed, and a component-based interactive visualization structure for multi-dimensional, spatiotemporal ocean data is presented in this paper. Based on this structure, users can easily customize the system to visualize other types of scientific data.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于组件的交互式可视化海洋数据分析系统的开发
随着各类固定海洋观测设备、卫星遥感技术和计算机模拟技术的不断发展,现代海洋科学研究已进入大数据时代。由于在海洋灾害、全球气候变化和渔业研究中使用了海洋数据,交互式海洋可视化已经变得无处不在。然而,分析大量海洋数据的主要挑战来自数据本身的复杂性。因此,需要一个具有动态扩展潜力的交互式多尺度、多变量可视化系统来分析更大量的海洋数据。本文构建了统一的可视化数据服务,提出了一种基于组件的多维时空海洋数据交互可视化结构。基于这种结构,用户可以很容易地定制系统来可视化其他类型的科学数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Big Earth Data
Big Earth Data Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
7.40
自引率
10.00%
发文量
60
审稿时长
10 weeks
期刊最新文献
A dataset of lake level changes in China between 2002 and 2023 using multi-altimeter data The first 10 m resolution thermokarst lake and pond dataset for the Lena Basin in the 2020 thawing season A high-resolution dataset for lower atmospheric process studies over the Tibetan Plateau from 1981 to 2020 An application of 1D convolution and deep learning to remote sensing modelling of Secchi depth in the northern Adriatic Sea A mediation system for continuous spatial queries on a unified schema using Apache Spark
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1