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A comprehensive review of synthetic image generation methods in remote sensing

2025Artigo científico Acesso aberto
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datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.fosEngenharia e Tecnologia::Outras Engenharias e Tecnologias
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorLopes, Júlio Castro
dc.contributor.authorOliveira, Jose Luis
dc.contributor.authorLopes, Rui Pedro
dc.date.accessioned2026-03-20T11:52:38Z
dc.date.available2026-03-20T11:52:38Z
dc.date.issued2025
dc.description.abstractSatellite images are very useful across several domains since they offer a comprehensive view of the Earth's surface. A typical satellite image processing workflow involves several key steps: acquisition, pre-processing, segmentation, and classification. In the acquisition phase, satellite images are collected from remote sensors, and the pre-processing phase involves enhancing quality and removing distortions in the raw data. Afterwards, segmentation is used to divide the image into meaningful regions, which are then.eng
dc.description.sponsorshipThis work was supported by national funds through FCT/MCTES (PIDDAC): CeDRI, UIDB/05757/2020 (DOI: 10.54499/UIDB/05757/2020) and UIDP/05757/2020 (DOI: 10.54499UIDP/05757/2020); and SusTEC,LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020).
dc.identifier.citationA comprehensive review of synthetic image generation methods in remote sensing. International Journal of Remote Sensing. ISSN 0143-1161. 46:15. p. 5773-5801.
dc.identifier.doi10.1080/01431161.2025.2527373
dc.identifier.issn0143-1161
dc.identifier.urihttp://hdl.handle.net/10198/36164
dc.language.isoeng
dc.peerreviewedyes
dc.publisherInforma UK Limited
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relation.ispartofInternational Journal of Remote Sensing
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/
dc.subjectSatellite images
dc.subjectSynthetic data generation
dc.subjectRemote sensing
dc.subjectComprehensive review
dc.titleA comprehensive review of synthetic image generation methods in remote sensingeng
dc.typejournal article
dspace.entity.typePublication
oaire.awardNumberUIDP/05757/2020
oaire.awardNumberLA/P/0007/2020
oaire.awardNumberUIDB/05757/2020
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.citation.endPage5801
oaire.citation.issue15
oaire.citation.startPage5773
oaire.citation.titleInternational Journal of Remote Sensing
oaire.citation.volume46
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameLopes
person.familyNameLopes
person.givenNameJúlio Castro
person.givenNameRui Pedro
person.identifier.ciencia-idCC12-FD7E-D0BC
person.identifier.ciencia-id8E14-54E4-4DB5
person.identifier.orcid0000-0003-3354-8956
person.identifier.orcid0000-0002-9170-5078
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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relation.isAuthorOfPublicatione1e64423-0ec8-46ee-be96-33205c7c98a9
relation.isAuthorOfPublication.latestForDiscoveryab47fc12-ad28-436e-8bc6-a7f6359750e2
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