Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1186756
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dc.contributor.authorNOGUEIRA, S. F.
dc.contributor.authorSANTOS, T. T.
dc.contributor.authorBAYMA, G.
dc.contributor.authorSANTOS, P. M.
dc.contributor.authorSANO, E. E.
dc.contributor.authorBOLFE, E. L.
dc.date.accessioned2026-05-11T20:00:37Z-
dc.date.available2026-05-11T20:00:37Z-
dc.date.created2026-05-11
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. 360-366.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1186756-
dc.descriptionThis study identifies the optimal period for using unmanned aerial vehicle (UAV) imagery to assess pasture conditions in the municipality of Lagoinha, São Paulo State, Brazil. It combines long-term precipitation data (1948‒2024) and NDVI time series derived from Sentinel-2 satellite (2017‒2024) for 15 partner properties of the Science Center for the Development of Digital Agriculture - Semear Digital. The results show that the transition from rainy to dry season, especially in May and June, provides the best pasture contrast conditions for UAV monitoring. During this time, intermediate NDVI values (0.45‒0.55) enhance the differences between well-managed and degraded pastures, while lower precipitation and cloud cover conditions improve the radiometric quality of images. Farms with higher technology adoption show more stable NDVI profiles, facilitating the vegetation condition detection. This study provides a framework for planning UAV-based pastureland assessments to support better pastureland monitoring and management decisions.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectVeículo aéreo não tripulado
dc.subjectNDVI
dc.titleTemporal optimization of UAV-based pasture monitoring using multi-year NDVI and precipitation data in Lagoinha/SP, Brazil.
dc.typeArtigo em anais e proceedings
dc.subject.thesagroPastagem
dc.subject.thesagroPrecipitação Pluvial
riaa.ainfo.id1186756
riaa.ainfo.lastupdate2026-05-11
dc.identifier.doihttps://doi.org/10.1590/S1678-3921.pab2026.v61.03851
dc.contributor.institutionSANDRA FURLAN NOGUEIRA, CNPMA; THIAGO TEIXEIRA SANTOS, CNPTIA; GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPMA; PATRICIA MENEZES SANTOS, CPPSE; EDSON EYJI SANO, CPAC; EDSON LUIS BOLFE, CNPTIA.
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