Think global, cube local: an Earth Observation Data Cube’s contribution to the Digital Earth vision

IF 4.2 3区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Big Earth Data Pub Date : 2022-07-21 DOI:10.1080/20964471.2022.2099236
M. Sudmanns, H. Augustin, B. Killough, G. Giuliani, D. Tiede, A. Leith, F. Yuan, Adam Lewis
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引用次数: 13

Abstract

ABSTRACT The technological landscape for managing big Earth observation (EO) data ranges from global solutions on large cloud infrastructures with web-based access to self-hosted implementations. EO data cubes are a leading technology for facilitating big EO data analysis and can be deployed on different spatial scales: local, national, regional, or global. Several EO data cubes with a geographic focus (“local EO data cubes”) have been implemented. However, their alignment with the Digital Earth (DE) vision and the benefits and trade-offs in creating and maintaining them ought to be further examined. We investigate local EO data cubes from five perspectives (science, business and industry, government and policy, education, communities and citizens) and illustrate four examples covering three continents at different geographic scales (Swiss Data Cube, semantic EO data cube for Austria, DE Africa, Virginia Data Cube). A local EO data cube can benefit many stakeholders and players but requires several technical developments. These developments include enabling local EO data cubes based on public, global, and cloud-native EO data streaming and interoperability between local EO data cubes. We argue that blurring the dichotomy between global and local aligns with the DE vision to access the world’s knowledge and explore information about the planet.
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全球思考,立方体本地化:地球观测数据立方体对数字地球愿景的贡献
管理大型地球观测(EO)数据的技术前景包括从基于web访问的大型云基础设施的全球解决方案到自托管实现。EO数据立方体是促进大型EO数据分析的领先技术,可以部署在不同的空间尺度上:本地、国家、区域或全球。已经实现了几个以地理为重点的EO数据集(“本地EO数据集”)。然而,它们与数字地球(DE)愿景的一致性,以及创建和维护它们的好处和权衡,都应该进一步研究。我们从五个角度(科学、商业和工业、政府和政策、教育、社区和公民)研究了当地的EO数据立方体,并举例说明了覆盖三大洲不同地理尺度的四个例子(瑞士数据立方体、奥地利语义EO数据立方体、DE非洲、弗吉尼亚数据立方体)。本地EO数据立方体可以使许多利益相关者和参与者受益,但需要进行一些技术开发。这些发展包括支持基于公共、全局和云原生EO数据流的本地EO数据集,以及本地EO数据集之间的互操作性。我们认为,模糊全球和地方之间的二分法符合DE的愿景,即获取世界知识和探索有关地球的信息。
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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
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