Scalable Multi-resolution Spatial Visualization for Anthropogenic Litter Data
Scalable Multi-resolution Spatial Visualization for Anthropogenic Litter Data
复制标题
人为垃圾数据的可扩展多分辨率空间可视化
DOI：
10.1145/3347146.3359074
复制
发表时间：
2019
期刊：
影响因子：
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通讯作者：
Gray, Andrew
中科院分区：
文献类型：
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作者：
Kang, Yunfan;Zhao, Ziang;Magdy, Amr;Cowger, Win;Gray, Andrew
本文演示了CleanUpOurWorld；一个研究空间数据库，旨在收集、处理、查询和可视化人为凋落物数据。由于其重要的用例，这些数据在环境科学领域具有重要意义。我们通过一个由环境科学家和伙伴组织组成的社区，在世界范围内从不同的来源收集和维护这些数据。随着数据量的增加，现有的软件包（如GIS软件）无法扩展到处理、查询和可视化这些数据。为了克服这个问题，CleanUpOurWorld在一个可扩展的后端中以不同的格式消化来自不同来源的数据集，该后端在关系空间数据库中以结构化的形式清理、集成和统一这些数据集。构建前端应用程序以在多个空间分辨率下可视化垃圾数据。
This paper demonstrates CleanUpOurWorld; a research spatial database that is designed and deployed to collect, process, query, and visualize anthropogenic litter data. Such data has a significant importance in the field of environmental sciences due to its important use cases. We make a major on-going effort to collect and maintain such data worldwide from different sources through a community of environmental scientists and partner organizations. With the increasing volume of data, existing software packages, such as GIS software, do not scale to process, query, and visualize such data. To overcome this, CleanUpOurWorld digests datasets from diferent sources, with different formats, in a scalable backend that cleans, integrates, and unifies them in a structured form in a relational spatial database. Frontend applications are built to visualize litter data at multiple spatial resolutions.
海洋垃圾
DOI：
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发表时间：
2018
期刊：
w/k - Between Science and Art
影响因子：
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作者：
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通讯作者：
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