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The Australian Geoscience Data Cube - foundations and lessons learned

Lewis, Adam; Oliver, Simon; Lymburner, Leo; Evans, Benjamin; Wyborn, Lesley; Mueller, Norman; Roberts, Dale; Trenham, Claire; Sixsmith, J; Wu, Wenjun; Tan, K P

Description

The Australian Geoscience Data Cube (AGDC) aims to realise the full potential of Earth observation data holdings by addressing the Big Data challenges of volume, velocity, and variety that otherwise limit the usefulness of Earth observation data. There have been several iterations and AGDC version 2 is a major advance on previous work. The foundations and core components of the data cube are: (1) data preparation, including geometric and spectral radiometric corrections to Earth observation...[Show more]

dc.contributor.authorLewis, Adam
dc.contributor.authorOliver, Simon
dc.contributor.authorLymburner, Leo
dc.contributor.authorEvans, Benjamin
dc.contributor.authorWyborn, Lesley
dc.contributor.authorMueller, Norman
dc.contributor.authorRoberts, Dale
dc.contributor.authorTrenham, Claire
dc.contributor.authorSixsmith, J
dc.contributor.authorWu, Wenjun
dc.contributor.authorTan, K P
dc.date.accessioned2019-12-09T00:33:23Z
dc.date.available2019-12-09T00:33:23Z
dc.identifier.issn0034-4257
dc.identifier.urihttp://hdl.handle.net/1885/188486
dc.description.abstractThe Australian Geoscience Data Cube (AGDC) aims to realise the full potential of Earth observation data holdings by addressing the Big Data challenges of volume, velocity, and variety that otherwise limit the usefulness of Earth observation data. There have been several iterations and AGDC version 2 is a major advance on previous work. The foundations and core components of the data cube are: (1) data preparation, including geometric and spectral radiometric corrections to Earth observation data to produce standardised surface reflectance measurements that support time-series analysis, and collection management systems which track the provenance each data cube product and formalise re-processing decisions; (2) the software environment used to manage and interact with the data, including a minimal relational model that uses ‘not-only-SQL’ to simplify the process of adding new datasets to the data cube, or to simply ‘reference’ external datasets; and (3) the supporting, integrated, high performance computing - high performance data environment (HPC-HPD) provided by the Australian National Computational Infrastructure which supports both large scale analysis within the NCI, and direct access to data using standards-based web services. A growing number of exemplars demonstrate that the data cube approach allows analysts to extract rich new information from Earth observation time series, including through new methods that draw on the full spatial and temporal coverage of the Earth observation archives. To enable easy-uptake of the AGDC, and to facilitate future cooperative development, our code is developed under an open-source, Apache License, Version 2.0. This open-source approach is enabling other organisations, including the Committee on Earth Observing Satellites (CEOS), to explore the use of similar data cubes in developing countries.
dc.description.sponsorshipThis work funded by the Australian Government through Geoscience Australia and the NCI. Funding for the supporting HPC-HPD infrastructure at NCI came from the Australian Government Department of Education, through the National Collaborative Research Infrastructure (NCRIS) and Education Investment Fund (EIF) Super Science Initiatives via the NCI, Research Data Storage Infrastructure (RDSI) and Research Data Services (RDS) projects (particularly the A1.1 National Earth Systems Science Data Services Domain).
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherElsevier
dc.rights© 2017 Published by Elsevier Inc.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceRemote Sensing of Environment
dc.subjectLandsat
dc.subjectTime-series
dc.subjectBig data
dc.subjectData cube
dc.subjectHigh performance computing
dc.subjectHigh performance data
dc.subjectCollection management
dc.subjectGeometric correction
dc.subjectPixel quality
dc.subjectAustralian Geoscience Data Cube
dc.titleThe Australian Geoscience Data Cube - foundations and lessons learned
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume202
dcterms.dateAccepted2017-03-12
dc.date.issued2017-04-12
local.identifier.absfor050206 - Environmental Monitoring
local.identifier.absfor080306 - Open Software
local.identifier.absfor010401 - Applied Statistics
local.identifier.ariespublicationu1027566xPUB57
local.publisher.urlhttps://www.sciencedirect.com/
local.type.statusSubmitted Version
local.contributor.affiliationLewis, Adam, Geoscience Australia
local.contributor.affiliationOliver, Simon, Geoscience Australia
local.contributor.affiliationLymburner, Leo, Geoscience Australia
local.contributor.affiliationEvans, Benjamin, Administrative Division, ANU
local.contributor.affiliationWyborn, Lesley, Administrative Division, ANU
local.contributor.affiliationMueller, Norman, Geoscience Australia
local.contributor.affiliationRoberts, Dale, College of Business and Economics, ANU
local.contributor.affiliationTrenham, Claire, Administrative Division, ANU
local.contributor.affiliationSixsmith, J, Geosciences Australia
local.contributor.affiliationWu, Wenjun, Geoscience Australia
local.contributor.affiliationTan, K P, Geoscience Australia
local.bibliographicCitation.startpage276
local.bibliographicCitation.lastpage292
local.identifier.doi10.1016/j.rse.2017.03.015
dc.date.updated2019-07-28T08:17:19Z
local.identifier.scopusID2-s2.0-85017413041
dcterms.accessRightsOpen Access
dc.provenanceThis is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
dc.rights.licenseCreative Commons Attribution 4.0 International (CC BY 4.0)
CollectionsANU Research Publications

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