Detalhes bibliográficos
| Resumo: | Abstract: MODIS time series carries valuable long-term data essential to support several studies such as biogeochemical modelling. However, there is a lack of validation studies applying MODIS data at a fine-scale to monitor pasture management practices. In this study, we assessed the potential of MODIS sensor in monitoring at a fine-scale four intensively managed mixed-pastures fields located in São Paulo State, Brazil. The MODIS spectral response was compared with Sentinel-2, and the ability of the two sensors in predicting aboveground biomass (AGB) and canopy height (CH) was assessed using the Random Forest algorithm. EVI images from MODIS and Sentinel-2 were correlated with field measurements of AGB and CH. The prediction performance of AGB (R2: Sentinel-2?=?38%; MODIS = 42%) and CH (R2: Sentinel-2?=?69%; MODIS = 85%) models was superior using EVI data from MODIS than Sentinel-2, highlighting MODIS ability to monitor small and intensively managed pasture fields |
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| Autores principais: | Silva, Yane de Freitas da, 1990- |
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| Outros Autores: | Reis, Aliny Aparecida dos; Werner, João Paulo Sampaio, 1993-; Valadares, Rafael Vasconcelos; Lamparelli, Rubens Augusto Camargo, 1955-; Magalhães, Paulo Sergio Graziano, 1957-; Figueiredo, Gleyce Kelly Dantas Araújo, 1984- |
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| Assunto: | Floresta aleatória Random forest Aboveground biomas Scanopy height Sentinel-2 Pasture management Pre-print |
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| Ano: | 2021 |
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| País: | Brasil |
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| Tipo de documento: | artigo |
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| Tipo de acesso: | acesso aberto |
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| Instituição associada: | IBICT |
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| Idioma: | inglês |
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| Origem: | Oasisbr |
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