M. Sudmanns, H. Augustin, B. Killough, G. Giuliani, D. Tiede, A. Leith, F. Yuan, Adam Lewis
{"title":"Think global, cube local: an Earth Observation Data Cube’s contribution to the Digital Earth vision","authors":"M. Sudmanns, H. Augustin, B. Killough, G. Giuliani, D. Tiede, A. Leith, F. Yuan, Adam Lewis","doi":"10.1080/20964471.2022.2099236","DOIUrl":null,"url":null,"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.","PeriodicalId":8765,"journal":{"name":"Big Earth Data","volume":"44 1","pages":"831 - 859"},"PeriodicalIF":4.2000,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Earth Data","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/20964471.2022.2099236","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: 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.