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Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/30018
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dc.contributor.authorMutanga, Onisimoen
dc.contributor.authorKumar, Laliten
dc.date.accessioned2021-02-04T02:00:33Z-
dc.date.available2021-02-04T02:00:33Z-
dc.date.issued2019-03-01-
dc.identifier.citationRemote Sensing, 11(5), p. 1-4en
dc.identifier.issn2072-4292en
dc.identifier.urihttps://hdl.handle.net/1959.11/30018-
dc.description.abstractThe Google Earth Engine (GEE) is a cloud computing platform designed to store and process huge data sets (at petabyte-scale) for analysis and ultimate decision making [1]. Following the free availability of Landsat series in 2008, Google archived all the data sets and linked them to the cloud computing engine for open source use. The current archive of data includes those from other satellites, as well as Geographic Information Systems (GIS) based vector data sets, social, demographic, weather, digital elevation models, and climate data layers.en
dc.languageenen
dc.publisherMDPI AGen
dc.relation.ispartofRemote Sensingen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleGoogle Earth Engine Applicationsen
dc.typeJournal Articleen
dc.identifier.doi10.3390/rs11050591en
dcterms.accessRightsUNE Greenen
local.contributor.firstnameOnisimoen
local.contributor.firstnameLaliten
local.subject.for2008090905 Photogrammetry and Remote Sensingen
local.subject.seo2008960604 Environmental Management Systemsen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emaillkumar@une.edu.auen
local.output.categoryC4en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeSwitzerlanden
local.identifier.runningnumber591en
local.format.startpage1en
local.format.endpage4en
local.identifier.volume11en
local.identifier.issue5en
local.access.fulltextYesen
local.contributor.lastnameMutangaen
local.contributor.lastnameKumaren
dc.identifier.staffune-id:lkumaren
local.profile.orcid0000-0002-9205-756Xen
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/30018en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleGoogle Earth Engine Applicationsen
local.relation.fundingsourcenoteThis work was supported by the DST/NRF Chair in Land use planning and management, Grant No. 84157.en
local.output.categorydescriptionC4 Letter of Noteen
local.search.authorMutanga, Onisimoen
local.search.authorKumar, Laliten
local.open.fileurlhttps://rune.une.edu.au/web/retrieve/10803e3a-d101-4604-a1e8-777c52036e71en
local.uneassociationYesen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2019en
local.fileurl.openhttps://rune.une.edu.au/web/retrieve/10803e3a-d101-4604-a1e8-777c52036e71en
local.fileurl.openpublishedhttps://rune.une.edu.au/web/retrieve/10803e3a-d101-4604-a1e8-777c52036e71en
local.subject.for2020401304 Photogrammetry and remote sensingen
local.subject.seo2020189999 Other environmental management not elsewhere classifieden
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School of Environmental and Rural Science
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