Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1185928
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dc.contributor.authorPORTO, M. M.
dc.contributor.authorBOLFE, E. L.
dc.contributor.authorSANO, E. E.
dc.date.accessioned2026-03-30T19:52:43Z-
dc.date.available2026-03-30T19:52:43Z-
dc.date.created2026-03-30
dc.date.issued2025
dc.identifier.citationIn: WORKSHOP CIENTÍFICO DO CENTRO DE CIÊNCIA PARA O DESENVOLVIMENTO EM AGRICULTURA DIGITAL – SEMEAR DIGITAL, 2., 2025, Campinas. Anais [...]. Piracicaba: ESALQ/USP, 2025. p. 320-326.
dc.identifier.isbn978-85-86481-94-9
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1185928-
dc.descriptionThe aim of this study is to apply a decision-level spectral fusion technique to detect agricultural areas in the municipality of Boa Vista do Tupim - BA. The proposed approach is based on combining the probability maps generated from independent classifications of data acquired by the Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 Multispectral Imager (MSI) sensors to assess the performance of classifying seven land use and land cover (LULC) categories present in the study area. Methodology involves image selection and pre-processing, digital classification using the Random Forest algorithm, generation of probability maps, and evaluation of classification results using accuracy, precision and recall metrics. The results showed the potential for combining images from radar and optical sensors to detect LULC classes in Boa Vista do Tupim, BA.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectFusão de imagem
dc.subjectDistrito agrotecnológico de Boa Vista do Tupim
dc.subjectProjeto Semear Digital
dc.subjectSentinel-1 Synthetic Aperture Radar
dc.subjectImage fusion
dc.titleFusion of Sentinel-1 and Sentinel-2 satellite images for detecting agricultural areas in Boa Vista do Tupim - BA.
dc.typeArtigo em anais e proceedings
dc.subject.thesagroSensoriamento Remoto
dc.subject.thesagroAgricultura
dc.subject.nalthesaurusRemote sensing
dc.subject.nalthesaurusAgriculture
dc.description.notesOrganização: Silvia Maria Fonseca Silveira Massruhá, Durval Dourado Neto, Luciana Alvim Santos Romani, Jayme Garcia Arnal Barbedo, Édson Luis Bolfe, Ivan Bergier, Maria Angelica de Andrade Leite, Vitor Del Alamo Guarda, Catarina Barbosa Careta.
riaa.ainfo.id1185928
riaa.ainfo.lastupdate2026-03-30
dc.contributor.institutionMATEUS MENEGOSSI PORTO, UNIVERSIDADE ESTADUAL DE CAMPINAS; EDSON LUIS BOLFE, CNPTIA; EDSON EYJI SANO, CPAC.
Appears in Collections:Artigo em anais de congresso (CNPTIA)

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