Por favor, use este identificador para citar o enlazar este ítem: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1169127
Registro completo de metadatos
Campo DCValorLengua/Idioma
dc.contributor.authorOLIVEIRA JÚNIOR, J. G. de
dc.contributor.authorESQUERDO, J. C. D. M.
dc.contributor.authorLAMPARELLI, R. A. C.
dc.date.accessioned2024-11-14T11:55:06Z-
dc.date.available2024-11-14T11:55:06Z-
dc.date.created2024-11-14
dc.date.issued2024
dc.identifier.citationISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. X-3-2024, p. 85-92, 2024.
dc.identifier.issn2194-9050
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1169127-
dc.descriptionThis article aimed to determine a workflow for more efficient large-scale crop mapping using a time series of images from the Sentinel-2 Satellite, statistical methods of attribute selection, and machine learning. The proposed methodology explores the best possible combination of spectral variables related to vegetation (16 vegetation indices in the RGB, NIR, SWIR, and Red Edge regions) to characterize different spectro-temporal profiles of Land Use and Land Cover (LULC) in spatially heterogeneous landscapes.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectMonitoramento agrícola
dc.subjectSéries temporais
dc.subjectAprendizado de máquina
dc.subjectCobertura da terra
dc.subjectAgricultural monitoring
dc.subjectRandom forest
dc.subjectSITS
dc.subjectRed Edge
dc.titleOptimum combination of spectral variables for crop mapping in heterogeneous landscapes based on Sentinel-2 time series and machine learning.
dc.typeArtigo de periódico
dc.subject.thesagroSensoriamento Remoto
dc.subject.thesagroUso da Terra
dc.subject.nalthesaurusTime series analysis
dc.subject.nalthesaurusRemote sensing
dc.subject.nalthesaurusLand cover
dc.subject.nalthesaurusLand use
dc.description.notesEdition of proceedings of the ISPRS TC III mid-term symposium “Beyond the canopy: technologies and applications of remote sensing”, Belém, Brazil, 2024.
riaa.ainfo.id1169127
riaa.ainfo.lastupdate2024-11-14
dc.identifier.doihttps://doi.org/10.5194/isprs-annals-X-3-2024-85-2024
dc.contributor.institutionJOSÉ GALDINO DE OLIVEIRA JÚNIOR, UNIVERSIDADE ESTADUAL DE CAMPINAS; JULIO CESAR DALLA MORA ESQUERDO, CNPTIA; RUBENS AUGUSTO CAMARGO LAMPARELLI, UNIVERSIDADE ESTADUAL DE CAMPINAS.
Aparece en las colecciones:Artigo em periódico indexado (CNPTIA)

Ficheros en este ítem:
Fichero Descripción TamañoFormato 
AP-Optimum-combination-2024.pdf1.15 MBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro sencillo del ítem

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace