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A literature review on the use of ESA satellite data for soil organic carbon estimation models with artificial intelligence tools

2024Póster em conferência Acesso aberto
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datacite.subject.fosCiências Agrárias
datacite.subject.sdg15:Proteger a Vida Terrestre
datacite.subject.sdg13:Ação Climática
dc.contributor.authorLima, Arthur A. J.
dc.contributor.authorHernandez Hernandez, Zulimar
dc.contributor.authorLopes, Júlio Castro
dc.contributor.authorGonzález, Antonio
dc.contributor.authorLopes, Rui Pedro
dc.contributor.authorFigueiredo, Tomás de
dc.date.accessioned2026-09-17T13:38:10Z
dc.date.available2026-09-17T13:38:10Z
dc.date.issued2024
dc.description.abstractAgricultural soils play a crucial role in food security and climate change, as the process of accumulation and stabilization of soil organic carbon simultaneously improves the physicochemical properties, such as water retention, aggregate stability, or plant nutrition. For these reasons, knowing the amount of Soil Organic Carbon (SOC) is important to manage climate alarm, but the sampling and subsequent laboratory analyses that are traditionally used for this purpose are expensive and time-consuming, which leads to explore alternative non-degrading and environmentally friendly methods. Remote Sensing (RS) arises in this sense, seeking to reduce time consumption and cost . However, the amount of data needed for this type of evaluation requires advanced computer methods for the elaboration of SOC predict models . A Literature Review (LR) was conducted with the aim of finding tools, advances, and gaps in the literature. Using the PRISMA method, 30 articles that used RS and Artificial Intelligence (AI) to estimate SOC were selected to LR .The keywords and synonyms chosen for this research were: “Deep learning” and “Neural network”; “Remote sensing”; “Soil organic carbon” and “Organic matter”. The period covered by this work is from 2021 to August 2023.eng
dc.description.sponsorshipOs autores agradecem à Fundação para a Ciência e a Tecnologia (FCT, Portugal) e aos fundos nacionais FCT/MCTES (PIDDAC) pelo apoio financeiro ao CIMO (UIDB/00690/2020 e UIDP/00690/2020), CeDRI (UIDB/05757/2020 e UIDP/05757/2020) e SusTEC (LA/P/0007/2020). E, também, ao financiamento nacional pela FCT, Fundação para a Ciência e a Tecnologia, no âmbito da bolsa de doutoramento 2022.14010.BD de Arthur Aparecido Janoni Lima.
dc.identifier.citationLima, Arthur A. J.; Hernandez Hernandez, Zulimar; Lopes, Júlio Castro; González, Antonio; Lopes, Rui Pedro; Figueiredo, Tomás de (2024). A literature review on the use of ESA satellite data for soil organic carbon estimation models with artificial intelligence tools. In ESA Symposium on Earth Observation for Soil Protection and Restoration. Frascati.
dc.identifier.urihttp://hdl.handle.net/10198/37146
dc.language.isoeng
dc.peerreviewedno
dc.relationMountain Research Center - UIDB/00690/2020
dc.relationCentro de Investigação em Digitalização e Robótica Inteligente - UIDB/05757/2020
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
dc.relationSoil organic carbon assessment using remote sensing data through deep learning techniques
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectSoil organic carbon
dc.subjectRemote sensing
dc.subjectArtificial intelligence
dc.subjectDeep learning
dc.subjectNeural networks
dc.titleA literature review on the use of ESA satellite data for soil organic carbon estimation models with artificial intelligence toolseng
dc.typeconference poster
dspace.entity.typePublication
oaire.awardNumberUIDB/00690/2020
oaire.awardNumberUIDB/05757/2020
oaire.awardNumberLA/P/0007/2020
oaire.awardNumber2022.14010.BD
oaire.awardTitleMountain Research Center - UIDB/00690/2020
oaire.awardTitleCentro de Investigação em Digitalização e Robótica Inteligente - UIDB/05757/2020
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
oaire.awardTitleSoil organic carbon assessment using remote sensing data through deep learning techniques
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
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oaire.awardURIinfo:eu-repo/grantAgreement/FCT//2022.14010.BD/PT
oaire.citation.conferenceDate2024
oaire.citation.conferencePlaceFrascati, Italia
oaire.citation.titleESA Symposium on Earth Observation for Soil Protection and Restoration
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameLima
person.familyNameHernandez Hernandez
person.familyNameLopes
person.familyNameLopes
person.familyNameFigueiredo
person.givenNameArthur A. J.
person.givenNameZulimar
person.givenNameJúlio Castro
person.givenNameRui Pedro
person.givenNameTomás de
person.identifier1297327
person.identifier.ciencia-id741A-E55B-257A
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person.identifier.ciencia-idCC12-FD7E-D0BC
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person.identifier.ciencia-id961D-607D-51CC
person.identifier.orcid0000-0002-5636-022X
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person.identifier.orcid0000-0003-3354-8956
person.identifier.orcid0000-0002-9170-5078
person.identifier.orcid0000-0001-7690-8996
person.identifier.scopus-author-id36084226300
person.identifier.scopus-author-id54790554500
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project.funder.nameFundação para a Ciência e a Tecnologia
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