Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1179224
Título: Mapping banana and peach palm in diversified landscapes in the Brazilian Atlantic Forest with Sentinel-2.
Autoria: SOARES, V. B.
PARREIRAS, T. C.
FURUYA, D. E. G.
BOLFE, E. L.
NECHET, K. de L.
Afiliação: VICTÓRIA BEATRIZ SOARES, UNIVERSIDADE ESTADUAL DE CAMPINAS; TAYA CRISTO PARREIRAS, UNIVERSIDADE ESTADUAL DE CAMPINAS; DANIELLE ELIS GARCIA FURUYA; EDSON LUIS BOLFE, CNPTIA; KATIA DE LIMA NECHET, CNPMA.
Ano de publicação: 2025
Referência: Agriculture, v. 15, n. 19, 2052, Oct. 2025.
Conteúdo: Mapping banana and peach palm in heterogeneous landscapes remains challenging due to spatial heterogeneity, spectral similarities between crops and native vegetation, and persistent cloud cover. This study focused on the municipality of Jacupiranga, located within the Ribeira Valley region and surrounded by the Atlantic Forest, which is home to one of Brazil’s largest remaining continuous forest areas. More than 99% of Jacupiranga’s agricultural output in the 21st century came from bananas (Musa spp.) and peach palms (Bactris gasipaes), underscoring the importance of perennial crops to the local economy and traditional communities. Using a time series of vegetation indices from Sentinel-2 imagery combined with field and remote data, we used a hierarchical classification method to map where these two crops are cultivated. The Random Forest classifier fed with 10 m resolution images enabled the detection of intricate agricultural mosaics that are typical of family farming systems and improved class separability between perennial and nonperennial crops and banana and peach palm. These results show how combining geographic information systems, data analysis, and remote sensing can improve digital agriculture, rural management, and sustainable agricultural development in socio-environmentally important areas.
Thesagro: Agricultura
Comunidade Rural
Banana
Musa sp
NAL Thesaurus: Agriculture
Vegetation index
Time series analysis
Rural communities
Palavras-chave: Agricultura digital
Índice de vegetação
Vale do Ribeira
Digital agriculture
Ribeira Valley
Multitemporal
ISSN: 2077-0472
Digital Object Identifier: https://doi.org/10.3390/ agriculture15192052
Tipo do material: Artigo de periódico
Acesso: openAccess
Aparece nas coleções:Artigo em periódico indexado (CNPTIA)

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